In this video I share how a founder really found me (it was not my content), what actually won the project, and the simple test I would use if I were hiring a product designer today.

A profile or portfolio helps you screen for relevance. It cannot show you how someone thinks. Before we started working together, I did a product audit: problems, recommendations, the reasoning in a document, and a walkthrough explaining how I got there. That audit is what the founder pointed to when I asked him why he chose me.

So if you are a founder comparing designers, give them a small, real problem from your product. Watch which questions they ask first, whether they can separate an important problem from a cosmetic one, and whether they give you a clear recommendation or ten options. After you read their work, are you clearer about your product, or more confused?

A story went round an old workplace of mine that one of Atlassian’s founders was an early Arc enthusiast, and had handed the team a long list of suggestions. I have no idea whether that part is true. What is on the record is that Atlassian later bought The Browser Company outright for $610 million, and that the browser they ship now is Dia, not Arc.

Almost every designer and engineer I know went through a period of loving Arc. That is the part I keep turning over. How does a browser that good, admired by exactly the people who care most about their tools, never get anywhere?

Arc was one of the best-looking browsers anyone has built, and it never reached the mainstream. Both of those facts have the same root, and it shows up before the first click.

The first filter is how it looks

Open Arc’s old website and ignore the words for a moment. The personality arrives immediately. Warm, soft, artistic, generous rounded corners, light animation, a slightly vintage handmade texture. Visually it belongs to the same family as Notion, Substack and Linktree.

Those products tend to appeal to creators and individual users, people who enjoy shaping and organising their digital lives.

The communities where Arc actually took hold looked nothing like that. They were engineers, designers, product managers, heavy knowledge workers who found it through technology media and colleagues. They cared about speed, keyboard shortcuts, multitasking, and whether a browser could survive a complicated professional workflow.

Visual design does not decide adoption on its own. It does answer one question within a few seconds, before anyone has understood a single feature.

Was this made for someone like me?

Linear is the useful contrast. Its interface is restrained, dense and deliberately cool, and it reads as a professional instrument. Roughly the same audience, an opposite invitation.

The second filter is how much you have to remember

A traditional browser asks you to understand two things: tabs and bookmarks.

Arc introduced Profile, Space, Folder, Easel, Boost, Tab, Command Bar and Pinned Tab.

From a designer’s point of view none of that was badly organised. Each concept had a clear purpose and the relationships between them were coherent. The information architecture was arguably elegant.

That is exactly the trap. A concept being understandable does not mean anyone wants to hold it in their head alongside seven others.

Spaces were one of Arc’s most important ideas: separate environments for work, personal life or a project, each with its own tabs and state. Genuinely useful for complicated workflows. By the team’s own figures, only about 5 to 12 per cent of users ever adopted multiple Spaces. Calendar Preview reached 0.4 per cent.

Years of differentiation never became part of most people’s behaviour.

Two notes that sharpened this

Most portfolios fail before the first scroll. Not because the work is weak, but because the presentation treats finished screens as the story when the decisions behind them are the story. Anyone reviewing at an early-stage company is not asking whether you shipped something. They are asking whether you can think through a problem and make a call. Polished screens do not answer that, and the same logic applies to a landing page.

A deadline teaches a tool faster than a tutorial does. I had seen the word “Skills” float past in articles for months and filed it under things to look into later. The moment I had a real friction point I wanted solved, the concept landed in about a minute. Concepts do not stick because they are explained well. They stick when someone needs them.

Try this on your own product

Two questions, and take them in order.

Look at your landing page with the copy blurred out. Who does the visual language invite, and is that the person who eventually pays you? Then count the invented concepts a new user meets in week one, and for each of them ask what it would take for that concept to be needed rather than learnt.

Anything that has to be memorised before it is needed is a bill you are sending before you have delivered anything.

Also from me

A few other things I have written, outside the teardown.

The portfolio gap is not about skill

Most designers I know are more capable than their portfolio suggests.

That gap is not about skill. It is about evidence. The work exists, the judgement is there, the taste is real. But nothing in the portfolio shows it, because the portfolio was last touched two years ago and the case studies read like project reports.

I have been thinking about this differently lately. A portfolio piece is less like documentation and more like a single by a musician. It is not a record of what happened. It is a made thing that carries your current thinking and taste, in a form someone else can actually hold.

The question is not “do I have enough projects to show?” It is whether anything you have made recently reflects who you are now.

For most of us, it does not. And the gap is smaller to close than we think.

A shopping street borrowed the London Underground

A shopping district in Tauranga is using the London Underground wayfinding system to direct people to shops. Not inspired by it. Literally adapted from it. And it works perfectly.

The London Underground visual language, designed in the early 20th century, has outlived nearly every design trend that followed it. Clear hierarchy, high contrast, consistent iconography, ruthless reduction of noise. It was built for one of the busiest transit systems in the world, where decisions need to happen in seconds under pressure.

That last part is the key. Good wayfinding design solves for cognitive load at the moment of decision. A shopper in a busy retail precinct faces the exact same problem as a commuter at Bank station: too much information, not enough time, one choice to make. The context is completely different. The problem is structurally identical.

This is the real test of a design system. Not whether it looks good in a controlled environment, but whether it still holds up when someone drags it into a context it was never meant for. The London Underground system passes that test every time someone borrows it.

There is a useful parallel here for product work. When you are designing onboarding flows, navigation, or any moment where a user needs to make a decision quickly, the question is not “what is the right pattern for this industry?” The question is “what is the cognitive load at this exact moment, and what does the user need to do next?” Answer that clearly, and you are probably already most of the way there.

The best design systems are not precious about their original context. They solve human problems, and human problems travel.

The bottleneck is finishing friction, not drawing skill

Hand-drawn diagrams are fast to make but painful to read. That friction was bothering me, so I ran a quick experiment.

I’ve been using hand-drawn illustration comics to explain product concepts, the kind you sketch out in ten minutes to capture a thought before it disappears. The problem: rough lines and no colour make them harder to scan than they should be.

So I fed one into GPT’s image tool and asked it to clean up the line style and add simple colour. No anime transformation, no dramatic overhaul. Just enough polish to make the visual easier to follow at a glance.

The result was noticeably better. Lines read crisper, the hierarchy was clearer, and the whole thing felt more intentional without losing the hand-drawn energy that makes these feel approachable rather than corporate.

What I took from this: the bottleneck in quick visual communication isn’t always your drawing skill, it’s finishing friction. Most people abandon rough sketches before they publish them because the gap between “good enough to understand” and “good enough to share” feels too wide. A tool that closes that gap in two minutes changes the calculus on what’s worth making.

I’m not suggesting AI polish replaces good visual thinking. But for practitioners who sketch to think, not to impress, this kind of light post-processing is genuinely useful. It lowers the bar for shipping a visual explanation, which means more ideas actually make it out of the notebook.

Where to next

The full Arc teardown is on the site, including what the team carried into Dia and what users later demanded back: bearliu.com/blog/arc-the-moving-list

How many new concepts does your product ask for in the first week? Hit reply with the number. I read everything that comes back.

Hello, I’m Bear.

I’m a product designer in Auckland, New Zealand. Most of my work is as a Fractional Design Partner, which usually means being the design lead a small team cannot yet hire full time.

Design Decisions is where I take one product apart each week and write up the decisions behind it. I make videos and record a bilingual podcast for much the same reason. I like working things out in the open.

• bearliu.com · the full teardown library, and what I do for teams

• hi@bearliu.com · the old fashioned way, and I read every reply

• youtube.com/@Bearliu · a video is worth a thousand words

• x.com/bearliu · shorter thoughts, as they happen

I talk to AI every day now. Sometimes it is a terminal, sometimes the ChatGPT window, sometimes my phone, sometimes an app on the desktop. Sometimes I type it. Sometimes I just say it out loud. The whole thing has become completely ordinary.

Then I worked out how recent all of it is. ChatGPT arrived a few years ago, and that is the entire history of the habit. The part that interests me is not how fast we learned to use it. It is how fast we stopped finding it remarkable.

Almost every AI feature I am asked to look at has the same shape: a competent chat box with very little on either side of it. That gap is what this issue is about.

The chat box is becoming table stakes

The chat interface in Google Health is not new. You ask, it answers, the conversation continues. That pattern now shows up in almost every category of software.

The more interesting parts sit on either side of it. How does the conversation start, and what happens after one ends? I find it useful to split an AI conversation into three stages.

Before: someone has to speak first

Before you type anything, the system has to find something worth discussing and turn it into a question that is easy to answer.

Google Health is good at this. It reads your sleep and activity and produces something like: “Going to bed around midnight seems to be working well for you. Does keeping that schedule feel manageable as you head into the weekend?” Underneath sit a few answers you can tap.

You never face an empty input field. That matters more than it sounds. A blank box holds unlimited possibility and still leaves most people with no idea where to begin, which is one of the quietest ways a capable AI feature dies.

Google speaks first and you only have to tap. From your side the coach feels attentive. From Google’s side, the cost of getting one more signal out of you has dropped to a single interaction.

During: the part that will commoditise

Google Health reads personal data, draws charts, cites external sources, and keeps things moving with follow-up questions. It does all of that competently.

It will also stop being a differentiator. Any company with enough model access, data and engineering will eventually ship a reasonable chat experience. The chat box is on its way to becoming infrastructure.

After: where retention actually lives

Will it summarise what changed a week later? Will it notice your sleep drifting and raise it before you ask? Will it remember the goal from last time and check on it in a few days?

Across three weeks, almost none of that happened. No automatic weekly report, and the coach rarely picked up an earlier thread. Nearly every interaction still started with me opening the app.

Some of that is fair. The product is new, and unsolicited health advice carries real risk. One wrong or unnecessarily alarming notification could do lasting damage to trust.

The pattern still holds well beyond Google. Before decides whether people start. During is table stakes. After is what turns a feature into a relationship.

Two notes that sharpened this

Month one is not the signal. Most teams hit peak AI productivity in the first month and then quietly plateau. The early weeks feel like finding a new gear, because the obvious inefficiencies go first. What is left after that are capability gaps and knowledge gaps, and those are not prompting problems. AI stops multiplying and starts maintaining.

Bolting on is not the same as redesigning. Most teams still use humans as glue, copying out of one tab and into another so the next system can catch up. It looks like coordination, and it is friction wearing a lanyard. The steam engine did not transform manufacturing when it was invented. It transformed manufacturing when factory owners stopped bolting it onto the existing floor plan and redesigned the floor.

Try this on your own product

Take your AI feature and split it in three.

Before: what makes someone start? If the answer is an empty box and a hopeful tooltip, that is your weakest layer. During: is there anything here a competitor could not ship in two quarters? After: what happens between sessions, without the user doing anything at all?

Most products I look at have a strong middle and almost nothing on either side.

Also from me

A few other things I have written, outside the teardown.

Thinking is not a step you can hand off

I switched to a new research workflow a few months ago. Perplexity for discovery, Obsidian for notes, Claude for synthesis. It works. The output is faster and usually pretty good.

But somewhere in that chain I noticed something: I felt oddly distant from the work. Like I had supervised it rather than done it.

So I pulled out a notepad for the next project. Slower, messier, nothing shareable at the end of it. But when I sat down to actually write, the thinking was already there. I had not just gathered it, I had done it.

I do not think that part has an equivalent in any tool I have found. Not because the tools are bad. Because the thinking is not a step you can hand off without handing off the thing itself.

Now the default is sameness

There is a quiet irony happening in product design right now.

For years, the smart move was to borrow from the big players. Apple’s visual language lowered the trust barrier. Familiar felt safe. So everyone pulled from the same shelf.

AI has made that instinct dangerous.

Build something with Claude or any of the popular tools, and you will get a pale, clean, slightly washed-out interface almost by default. Not because you chose it. Because the tool steered you there before you even noticed. A lot of products launching right now look like cousins.

This is where a designer earns their fee. Not by making things look good, but by making deliberate choices that put distance between your product and the AI house style, while still making sense to your specific audience.

Differentiation used to be hard. Now the default is sameness. The gap is the opportunity.

MVP vs MLP: why most products stay minimum and never lovable

Most products get to “it works” and stop there. Eric Ries never said an MVP should be low quality, but that is what it became in practice: ship the function, promise the rest later, never come back.

I spent a second pass on CUBE, a small isometric type tool I built. The interesting part is what I did first. I did not add features. I cut them. Then I spent the time on the typing feel, the cursor, the transitions between views, and the sound.

The feature list did not change at all. The feeling did.

Brian de Haaff has a good line for this: you could eat a can of cat food if you had to, but you would not ask for a second serving. Jussi Pasanen puts it better as a model, build a slice across functional, reliable, usable and delightful, instead of one layer at a time.

What is new is that designers can now do this without waiting for an engineer. I did the motion in this thing with prompts.

Honest limit: CUBE does not solve a real problem. If yours does, you still need an MVP, and it still has to be good.

Where to next

The full Google Health teardown is on the site, including how many collection points fit on a single card and what its citation habits give away: bearliu.com/blog/google-health-extraction-by-design

Which of the three layers is thinnest in what you are building? Hit reply and tell me. I read everything that comes back.

Hello, I’m Bear.

I’m a product designer in Auckland, New Zealand. Most of my work is as a Fractional Design Partner, which usually means being the design lead a small team cannot yet hire full time.

Design Decisions is where I take one product apart each week and write up the decisions behind it. I make videos and record a bilingual podcast for much the same reason. I like working things out in the open.

• bearliu.com · the full teardown library, and what I do for teams

• hi@bearliu.com · the old fashioned way, and I read every reply

• youtube.com/@Bearliu · a video is worth a thousand words

• x.com/bearliu · shorter thoughts, as they happen

A client project I have been working on is about to reach the App Store. It is a fitness product that a startup team has been building for a while, and I have taken more from it than I expected to.

Most of my work before this was with large teams. A startup is a different shape entirely. There are fewer people, so there are fewer places for a decision to hide, and anything you choose to build lands on someone’s plate that same week. You feel the cost of a yes much faster.

Most teams can tell you who their product is for. Far fewer can tell you who it is not for, and say those people out loud.

Linear can. That turns out to be a large part of how it reached more than $100 million in annual recurring revenue without spending much on marketing.

The list of things Linear does not do

Linear supports one level of sub-issues. There is no deep task hierarchy. One of the teams I work with is genuinely unhappy about this.

The default interface has almost no decorative graphics. The mobile experience is thin, because keyboard shortcuts and hover tooltips do not translate to a touchscreen. It also refuses to stack concepts the way Jira does with Boards, Sprints, Epics, Components and Versions.

Every one of those omissions costs it a group of users. Large enterprises that need complex permissions and approval chains go to Jira. Project managers who live in nested hierarchies pick something else. People who work mainly from a phone never get the full product. A non-technical founder opens it, sees few visible features, and decides it is not serious enough.

Linear accepts that all of those people will leave.

Losing the right customers is cheaper than keeping them

That sounds like giving up revenue. It is also cutting cost.

A badly matched customer brings more than a subscription. They bring longer sales conversations, more training, more complicated support, and a stream of feature requests that matter to almost nobody else. If they only discover the mismatch after adopting the product, you have already paid to acquire and support them.

Linear’s design lets those people leave early. They open it, try a few things, and see quickly that it is not their tool. Linear loses the subscription, and avoids everything that would have come attached to it.

That is where restraint stops being a design preference and starts shaping the business. A leaner team, a simpler sales process, and growth that runs mostly on recommendations between teams that already fit.

Two notes that sharpened this

Scope creep does not announce itself. Working on someone else’s product I flag it reflexively: this changes the scope, is that the direction we agreed? Then I built my own thing with AI tools and caught myself doing exactly what I warn clients about. No single bad decision, just a quiet drift, one “while I am in here anyway” at a time. What helped was using the assistant to interrogate features rather than generate them: what problem does this solve, what does it cost in focus, does it serve the original intent.

Shipping used to be the filter. The effort of building something did the work of saying no for you. If it was not worth three weeks, it probably was not worth building. Now that the distance between a vague idea and a working thing has collapsed, that filter is gone, and you end up optimising for output instead of direction. The teams I see holding their shape are the ones where a real brief and a real deadline do the job friction used to do.

Try this on your own product

Name the customer you are prepared to lose. Not the one you have not got around to serving yet. The one you would turn away.

Most teams can describe their target customer in a sentence. Very few will say out loud who they are willing to disappoint. When nobody says it, features keep accumulating, the visual language keeps getting more neutral, the copy keeps getting broader, and eventually everyone finds the product quite good while nobody feels it was built for them.

Where to next

The full Linear teardown is on the site, including the first-run experience and why its most important feature does not appear on day one: bearliu.com/blog/linear-the-restraint-tax

Who is the customer you have decided not to serve? Hit reply and tell me. I read everything that comes back.

It turns out most of my day no longer needs that precision. Voice input handles a lot of it now, and a great deal of the mouse work is a single click rather than a careful drag. The constraint that ruled the walking pad out had quietly stopped applying.

Maybe half the day still needs a steady hand, and that half is the part I enjoy most. Worth noticing. When the tooling changes, what is left standing is usually the part that was the real work all along.

Ask a product team which features matter and most of them will say all of them. Ask the same team to rebuild from scratch and the answer gets honest very quickly.

The Browser Company gave that answer in public. Arc never broke through, and never held more than 0.1 per cent of the browser market. Dia, built by the same people, launched in June 2025, and three months later the company sold to Atlassian for $610 million. What changed between the two products is a list, and the list is the useful part.

The moving list

Arc asked a lot of a new user. Profile, Space, Folder, Easel, Boost, Command Bar, Pinned Tab. Tabs and pinned tabs needed no explanation. Almost everything else was invented, and each invention arrived with its own logic.

Every one of them had a reason to exist. Put together, they stopped being a set of features and became a new product language.

Attention is the budget here. Say someone will spend ninety minutes in their first week working out how a product behaves. Six invented concepts at ten minutes each eats most of that. By the time they reach the part that makes the product worth switching for, the patience has gone.

When the team rebuilt as Dia, they carried the Command Bar, Split View, the sidebar structure and the tab lifecycle that quietly archives what you stopped using. They left Spaces, Folders, Easel and Boost, along with several of the AI features added late to Arc.

The Command Bar is the one that matters. In Arc it had already become the single place you expressed intent: open a page, search, run a command, ask something. Dia kept it and made it the main way you reach AI. It has now survived two generations of the same team’s thinking, which is about as strong a signal as a product asset can give you.

Read the list twice

There is a second list, and most people stop before they get to it.

Around six months after launch, Dia began bringing Arc features back, starting with a sidebar mode. Some things had been cut too fast.

So a moving list is worth reading twice. What survives the rebuild tells you what a team believes is core under pressure. What comes back later tells you where users actually felt the value. The gap between those two lists is where the first judgement was too aggressive.

You can run this without a rebuild. Asking a team what is not working invites explanation and defence. Asking them to keep only half forces a ranking, and the ranking is what you were after.

Two notes that sharpened this

Most products lose people before the value arrives. The gap between someone’s first interaction and the moment they think this is worth my time is a growth variable, not a soft UX concern. Two habits quietly widen it: the feature tour, which asks for trust before giving a reason to trust, and configuration friction, which bets on willpower instead of product quality.

Arc’s ideas were not bad. The bill for learning them simply came due before the payoff did.

Subtraction is the skill. A good illustrator strips reality down to the fewest marks that carry the idea, and the deciding is where the craft lives. Early teams often have the opposite instinct: more features, more onboarding steps, tooltips explaining the tooltips. The product ends up a detailed sketch of everything the team knows rather than a clear signal of what a user needs to see right now.

Try this on your own product

If you had to rebuild tomorrow and could keep only half of what you have, which half survives?

Write that list before you look at your roadmap, so the roadmap does not answer for you. Then ask the harder second question. Of the things you would cut, which would users ask you to bring back within six months? If you cannot answer that one, you may not yet know where the value is actually felt.

Where to next

The full Dia teardown is on the site, including why a $610 million acquisition still does not settle the product-market fit question: bearliu.com/blog/dia-the-budget-transfer

If you have run your own moving list, I would like to see it. Hit reply and tell me what survived.

I just finished 100 Things Every Designer Needs to Know About People. It is old by internet standards and almost all of it still holds. Most of it is not about screens at all. It is about attention, memory, and how much a person can actually hold at once.

That turned out to be useful for this issue, which is about a product running straight into those limits.

Raycast is one of the smoothest tools on macOS. Two keystrokes carry the whole product. Enter runs the main action, Cmd+K shows everything else you could do with the thing in front of you. Learn that once and you can operate more than two thousand extensions.

Then AI arrived, and the same two keystrokes started to look like a ceiling.

What have you been reading lately? Hit reply if something has stayed with you. I am always after the next one.

Two keystrokes, and where they stop working

Open Raycast and type three letters. A list appears. Enter runs the top result, Cmd+K opens the other things you could do with it. Launching an app, finding a file, running an extension a stranger wrote, it is all the same rule.

That is why 2,500 extensions do not feel like 2,500 things to learn. You learn one grammar, and every extension after that is nearly free.

I have turned this into a check I now run on other products. What is the user’s main action? When they need more choices, what do they reach for? Does that rule cover every feature? Then go looking for the place the rule stops holding, because that place is usually the ceiling of the product’s structure.

On system tools and quick actions, Raycast passes almost perfectly. It stops holding at AI.

The command bar has one rhythm. Appear, act, disappear. You summon it, type, run something, and it is gone within seconds.

AI has a different rhythm. Persist, iterate, build up context. The first answer is a starting point. You add a file, change the tone, compare a few options, keep going from what came before.

So Raycast now has two doors. Quick AI in the command bar for a single answer, and AI Chat in its own window for a conversation. Before you ask anything, you have to decide which one you are in.

It looks like a tiny choice. It also undoes the thing Raycast was best at. The product that removed the cost of operating has quietly put one back.

Glaze is the receipt

In March, Raycast shipped Glaze, which generates native desktop apps by talking to an AI. The interesting part is not what it does. It is where they put it.

Glaze is not inside the command bar. It is a separate product, with its own engineering, its own brand and its own budget.

A standalone product costs far more than a strategy statement. When a company is willing to pay that, it is telling you something about the old product that no press release will. The team already knows the command bar cannot hold what they want AI to do.

Worth borrowing next time a company ships a new surface. Put the vision aside and ask a narrower question. What could the old product not do, that forced them to build a new one? The answer usually sits closer to the real strategy than the positioning does.

Two notes that sharpened this

The model is rarely the problem. Most poor chat experiences fail on interaction design, not intelligence. Three layers decide it: input, where an empty text box asks too much of someone who cannot yet articulate what they want; output, where plain prose is usually the wrong format; and refinement, where teams make people re-describe an edit in a sentence instead of handing them a slider or letting them click the part they want changed. AI bolted on as a feature behaves differently from AI woven into the work, and users feel that difference long before they can name it.

The window for new patterns is closing. We are in the short phase where the limits of the old interaction model are obvious and the new one has not settled. Phases like that do not last. Teams paying attention now get to shape what these interactions become, and everyone else inherits whatever the large platforms standardise first.

Try this on your own product

Three questions, in order.

What is the main action in your product, and what do people reach for when they need more than that? Does the rule still hold at the edges, or is there a feature that already needs its own window? And if there is, is that feature the one you charge for?

Raycast’s answer to the last one is uncomfortable. The free tier already covers most of what people use daily. The clearest reason to pay is AI, which is the part that fits the original design least.

Where to next

The full Raycast teardown is on the site, with the screens, the extension ecosystem numbers and what they suggest about the moat: bearliu.com/blog/raycast-the-interaction-model

If you are adding AI to something that was not designed around it, hit reply and tell me where it stopped fitting. That is the part I find most useful to hear.

It is August already, which in AI time feels like it should be next year.

What strikes me lately is how much has not moved. I started drawing again this month, something I did constantly as a teenager and then put down for years. Picking it back up, almost none of it needed relearning. The tools around it have changed completely. The thing itself has not.

That gap is what this issue is about. Some products are built to be noticed. Others are built to keep working while you forget they are there. We tend to grade both with the same ruler.

Apple Health ships on every iPhone. It sits at a 3.0 rating, and that number grades it as a product people chose. Almost nobody chose it. You bought a phone, and it was already there.

Nobody downloads Apple Health

Most of what I take apart is something people actively went and got. Apple Health is unusual. Buy an iPhone and it is already installed. Start wearing a Watch and it quietly begins collecting steps, heart rate, sleep and workouts in the background.

It sits closer to Settings or Contacts than to Fitbit. We do not open those because they are exciting. We expect them to be reliable, and to be there when we need them.

People still judge it against Fitbit and Whoop. Open Fitbit and you get a sleep score, recovery information and a suggested action for today. Open Apple Health and you get a Summary page of pinned metrics and trends, then a Browse tab covering activity, body measurements, hearing, heart, medications, nutrition, sleep, symptoms and vital signs.

The usual complaint is that there are too many categories. That is not quite the problem. Those categories run on three different logics at the same time.

Heart, respiratory and hearing are body systems. Activity, sleep and nutrition are behaviours. Symptoms, medications and vital signs are clinical records. You are being asked to hold three competing maps in your head at once.

Two scorecards

Consumer products are measured by engagement, retention and time spent. The team wants you back tomorrow, staying a little longer.

Infrastructure is measured by the opposite. We do not open cloud backup each morning to check it still works. We do not turn on a tap to admire the plumbing. Infrastructure earns its keep by being stable, trustworthy and unobtrusive, and most of the time you should barely notice it.

Apple Health was built to the second scorecard and is being graded on the first.

It has to hold more than 150 kinds of health data arriving from the iPhone, the Watch, third-party devices, fitness apps, manual entry and medical institutions, all funnelling into HealthKit on the device. That is what buys the compatibility. A hospital record, a heart-rate reading from a Watch and a weight you typed in yourself can all live in the same place.

The cost is that it cannot give you Fitbit’s tidy, composed dashboard. Most of Fitbit’s data comes from Fitbit hardware, so Fitbit gets to decide what matters and in what order it appears. Apple Health has to stay neutral. It cannot organise the whole experience around one device, one goal or one idea of wellbeing.

So the capability that makes Apple Health valuable is also what produces its most visible usability problem. Sometimes an interface is simply the structure underneath becoming visible.

Two notes that sharpened this

You are probably not the target user. I watched the new Mario film with my daughter and thought it was loud, shallow and basically plotless. IMDB agreed with me. Then I caught the mismatch: the audience is six to fourteen year olds, and very few of them leave reviews.

The people buying tickets were exhausted parents whose kid would not stop asking. Box office and critic scores have almost nothing to do with each other when your buyer is a child and your decision-maker is a tired adult. Founders in their forties building for Gen Z make the same error with their own taste.

The layer underneath stays invisible until it fails. Roughly 70 to 80 per cent of daily work already happens inside a browser, and almost nobody treats the browser as a product decision. We spend our energy choosing between apps and ignore the layer all of them run on. Infrastructure has that problem permanently. It gets noticed on the day it breaks and taken for granted every other day.

Try this on your own product

Which scorecard is your product actually built for, and which one are you being graded on? When those differ, the gap shows up in your reviews long before it shows up in your revenue.

Then the harder question. Who is leaving your reviews, and are they the same people who get the value? If they are not, you may be tuning the product for an audience that never had to live with your decisions.

Where to next

The full Apple Health teardown is on the site, including the two design cracks I do think are real and why most companies should not copy this kind of restraint: bearliu.com/blog/apple-health-infrastructure-by-design

If something you are building is being measured with the wrong scorecard, hit reply and tell me which one. I read everything that comes back.

This newsletter went quiet for a few months. The honest reason is that I could not answer a simple question about it. Who was it for, and what was it about?

I have an answer now. It is back, it is much narrower than it used to be, and it has a new name. If you subscribed to this as Bear Academy, you are in the right place.

Design Decisions is about the choices behind digital products. The question is rarely whether a product is good. It is what a team decided, what they gave up to get it, and which constraints they were working inside. The main format is the product teardown. I pick a real product, use it properly for a few weeks, and take it apart in public.

Teardowns earn that place because they are the one format where the decision is still visible. A case study shows you the outcome after the fact. A teardown lets you reason backwards from the interface to the choice that produced it, and the choice is the part you can reuse.

If you are building something early, this is written for you. Founders, designers, product managers, engineers, people working alone or in small teams. What you have in common is that you are deciding before all the answers are in.

Here is the kind of thing that turns up.

Apple asks you for almost nothing. Google asks you on every screen.

I spent three weeks wearing a Fitbit so I could study Google Health properly, with Apple Health as a control.

Most of what lands in Apple Health arrives on its own. The Watch and third-party devices write in the background, and the app rarely asks you anything at all. It does not chase feedback or check whether a recommendation helped.

Google Health does the opposite. Open it and the AI coach may comment on last night’s sleep, a recent workout or a change in your heart rate, then ask how you feel about it.

I asked mine what my resting heart rate actually meant. It pulled thirteen days of my data, showed a range of 59 to 68 beats per minute, drew a chart I could inspect day by day, and backed the explanation with external health sources. Then it asked me something back: does that overview give you the peace of mind you are looking for? When I mentioned I was taking heart medication, it carried that into the next reply. When I switched to Chinese halfway through, it followed.

As a piece of interaction design, the coach is genuinely well made. The more interesting question is why it is so eager to keep the conversation going.

My first instinct was to grade them. One of these had to be the better design. That instinct was wrong, and correcting it was the most useful thing I took from the whole exercise.

Apple’s health strategy runs on the iPhone and the Watch. It needs you to believe that years of sensitive records can sit safely inside its ecosystem, because that trust is part of what keeps you buying the hardware. Fewer questions, fewer interruptions and more on-device processing are not restraint for its own sake. They are part of the offer.

Google’s strengths were built around data and machine learning. Health data carries tighter restrictions, and Google says it does not use it for advertising. It still needs behavioural feedback to improve its products and its models. So a good coach does two jobs at once. It helps you understand your body, and it collects the kind of signal a passive tracker can never reach.

Same job, same data, opposite interfaces, and both of them right.

Try this on your own product

Take your most visible design choice. The free tier, the constant prompt, or the thing you pointedly refuse to ask users for. Read it back to how you make money. Does it hold up as a business decision, or only as taste?

Then the harder version. If a competitor copied that choice without your revenue model underneath it, what would it cost them?

What happens from here

One issue a week. One question about how a product got its shape, and one thing you can take back to whatever you are building.

Six complete teardowns are already on the site, each with the full argument and the screens attached: Apple Health, Google Health, Linear, Arc, Dia and Raycast. The two behind this issue are The Restraint of Apple Health and Why Does Google Health Keep Asking You Questions?

If something you are building runs into this, hit reply and tell me about it. I read everything that comes back.

Lately, I’ve been reflecting on a familiar feeling: the anxiety of missing out on the AI wave.

Even as someone who stays close to tech, I sometimes wonder — am I falling behind? A recent trip back to China made that feeling stronger. Surrounded by relentless hustle and pressure, it was easy to feel like everyone else was moving faster, grabbing every opportunity, while I was standing still.

But I’ve felt this before. Years ago, after moving to New Zealand and starting from scratch, I watched peers back home building companies, raising funding, making waves. That same FOMO crept in.

What I’ve learned is: this fear never fully goes away. But we can learn to live with it. Real calm doesn’t come from chasing every wave, but from finding one or two things that matter deeply — and doing them well.

Staying well, focused and grounded in a fast-moving world might just be the success that counts.

Goodies for this week

When Life Interrupts Your Projects: Lessons From Balancing Family and Building a Startup

Life doesn’t ask when you’re ready.
Sometimes it just interrupts everything.

I disappeared from YouTube for a month to take care of my dad.
That pause forced me to rethink how I work, how I create, and how I balance two worlds.

In this video, I share five lessons that helped me recalibrate.
Time as a portfolio.
Redefining progress.
Building redundancy in life.
Flexible creative rhythm.
Identity that survives disruption.

If you’re building a career while juggling real life, this might help you think differently.

Building a Website in 15 Minutes with Framer AI

I recently watched FrameSpace’s video “I made a website in 15 minutes (Framer AI Features)”, which introduces two new AI-powered functions in Framer: WireFramer and AI Components. Both features are highly practical, especially for designers who need to move quickly from concept to prototype without leaving the Framer environment.

The WireFramer tool allows users to generate a full wireframe layout from a simple text prompt. What makes it powerful is that everything happens within Framer—no exporting, importing, or switching between tools. Once the wireframe is generated, it can be edited directly: you can replace text, swap images, and adjust layout details until it forms a working prototype. For many small projects or early-stage ideas, this drastically shortens the time from concept to presentation.

The second feature, AI Components, extends this idea into interactivity. It lets users describe a desired component—such as a countdown timer—and the AI automatically builds a functional version of it. In the demo, the creator uploads an image of a clock, asks Framer to turn it into a working timer, and the system produces it within seconds. While it’s likely that the showcased examples were carefully selected and that more complex components still require manual work, the potential is evident: Framer is evolving from a web design tool into an integrated, AI-driven creation platform.

For independent designers and content creators, these tools could reshape how digital products are prototyped and shared. I plan to test these features in real projects to see how well they perform in practice and may later create a tutorial or mini-course to explore their practical impact on design workflows.

Original video:

👉 I made a website in 15 minutes (Framer AI Features) - YouTube (FrameSpace)

Can AI Be Used in Design?

Can AI Be Used in Design? Absolutely. But not in the way where you just toss in a prompt and expect magic. The real power of AI in design is in breaking things down.

Here’s a recent example. I was working on the landing page for JAM and needed to define the typography styles. After discussing with AI, I decided the fonts ( a Chinese and an English font) and the styles. Then I asked ChatGPT to generate a JSON file for those styles. I used a Figma plugin to import that as design tokens and instantly apply the styles in Figma.

With AI, the whole process took maybe 5 minutes. Without it, doing the same manually would’ve taken around 30, so time saved, a lot.

That’s how I see AI in design. It’s a tool - like a knife, scissors, or screwdriver. Use it with precision, stay focused on the task, let it do what it’s good at, and move on.

I Tried Every AI Design Tool — Here’s What I Found

I watched Paavan, a London-based designer, run a fascinating experiment in his video “I tried every AI design tool. Here are the results.” He used the same web design prompt across nearly all major AI website builders to compare how each tool performs. The outcome confirms what many of us might already suspect.

The clear winners are Lovable, V0, and Mocha — all three tools deliver relatively consistent, high-quality outputs. Lovable stands out for its speed and layout intelligence, producing pages that look like they were structured by a human designer. V0 handles component logic well, generating cleaner HTML and hierarchy. Mocha also performs solidly, balancing speed with clarity.

In contrast, other tools such as Google Stitch, Firebase Studio, and Canva fall short — either creating cluttered layouts or visually outdated designs that are far from usable.

Interestingly, Paavan didn’t test Figma or Framer, likely because they’re not full “one-click generation” systems. But the larger takeaway here is clear: no single AI tool is enough. Just like with large language models, designers will increasingly need to combine tools — one for generation, another for refinement — to achieve reliable results.

For designers like us, that’s actually exciting. It means our role is shifting from “using tools” to “orchestrating intelligent workflows.”

Original video:

👉 I tried every AI design tool. Here are the results. - YouTube (Paavan — Designer in London)

When should you start promoting your product?

Here’s the short answer: not at launch, but when it’s ready.

Before you pour time or money into growth, ask yourself:

1. Is the core product stable?

If key features are still buggy or missing, fix that first.

2. Is there early product–market fit?

Not perfect, but are users coming back? Giving feedback? Sharing it? That’s a green light.

3. Do you have real acquisition channels?

Website, socials, YouTube, podcast, newsletter — something that brings people in without always paying for ads.

4. Does onboarding actually work?

Can new users understand your product and reach value quickly? If not, fix the funnel before filling it.

Promotion works when the product’s ready to keep the attention you earn.

Not earlier.

The newsletter is sponsored by JAM

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Hello, I’m Bear—a product designer, UX mentor and an award‑winning bilingual podcast host, currently living in Auckland, New Zealand. I enjoy sharing insights from my work, life, and study, helping all of us grow together.

Bear Academy Newsletter is my weekly email packed with thoughts on technology, design, and productivity—featuring book breakdowns, learning tips, and career reflections. Subscribe for free at bear.academy

💬 Contact

• Youtube.com/@Bearliu - A video is worth a thousand words

• bear@beartalking.com - The old fashion email way

• LinkedIn.com/in/bearliu - My professional life

• Beartalking.com - all my posts, in English and Chinese

• https://twitter.com/bearbig - Majorly I post in Chinese

Earlier this month, I caught up with a friend who’s keen to start an AI-focused business, but still figuring out what exactly to build.

We talked about a bunch of things, some tough questions, some honest advice.

Here are a few points I thought were worth writing down:

⸻

1. If you don’t have a tech background, should you learn to code or find a technical co-founder?

My take: both. It’s not an either-or decision.

• Start by building your own rough demo. Even if it’s held together with no-code tools, AI wrappers, or vibe coding, get something out there. Share it with friends. Post it on social. See if anyone cares enough to ask questions, give feedback, or follow up.

• Then look for a technical co-founder to help with what comes next. Don’t fall into the trap of trying to do everything yourself forever.

There’s a kind of pain worse than failure: knowing exactly what’s wrong with your product but not having the skills to fix it. That’s what happens when you stretch yourself too thin for too long.

⸻

2. Can two people realistically build something meaningful?

I’m a realist. I constantly ask myself: what resources do I have right now?

And based on that, I decide: what’s the most valuable thing I can do with them?

Lately, due to family stuff, I only get 2–3 hours of focused work per day. So I force myself to prioritise brutally: what’s the one thing I can do now that moves the needle?

That’s the rational side.

But there’s an emotional side too. Sometimes I just tell myself: It’s okay if I can’t get everything done. The world won’t end.

⸻

3. What if the idea isn’t flashy — like it’s not AI infra, not consumer, and not “sexy”?

This was a concern my friend voiced:

“What if what I’m building just isn’t cool enough? Will anyone care?”

Here’s my take: If you don’t come from a technical background, your edge is probably domain insight.

That’s your moat.

It’s like The Alchemist, the treasure isn’t in some faraway land, it’s probably under your feet.

You may not build the next-gen AI model, but you can embed AI into the workflows of industries you already understand.

Others don’t know the pain points, you do.

Others can build the tech, but you know where it actually fits.

⸻

4. How do you convince a technical co-founder to work with you?

Start by being honest with yourself:

If your idea is something a developer could just build on their own, why should they work with you?

You need to be able to show what you bring to the table:

• Real user insights or domain knowledge

• The ability to define and shape the product

• You can handle market, content, GTM, and storytelling

• And most importantly, you’re not looking for someone to “build your idea” — you’re looking for a partner

Also, understand how engineers think.

They’re not sales reps or marketers, they’re more like skilled builders.

Think of them like contractors: bricklayers, carpenters, electricians.

They don’t want to hear about “massive TAM” or “category-defining strategy.”

They want to see:

• Clear specs

• Thought-through designs

• Confidence that the project isn’t just fluff

Respect that mindset, and collaboration becomes a lot easier.

⸻

Let me know if any of this resonated, especially if you’re in a similar place. Would love to hear how you’re thinking about AI + indie product building right now.

Goodies for this week

Psychological Design: 7 Tactics to Turn Leads into Customers

This article by Outcrowd Studio is a gem — it reminds us that good design isn’t decoration; it’s psychology in action.

It breaks down seven core principles that help convert attention into action.

Key takeaways:

1. Reduce cognitive load – confusion kills conversion. Keep the page simple, the navigation intuitive, and forms short.

2. Manage attention – focus on one main goal per page. Every design element should either lead toward that goal or disappear.

3. Apply Gestalt principles – proximity, similarity, symmetry, and figure-ground relationships guide the eye naturally.

   For example, symmetrical layouts feel cohesive, but a single asymmetric element nearby becomes a perfect focal point.

4. Humanise your brand – show real people behind it. “Let them peek backstage” — authenticity builds trust.

5. Teach, don’t sell – people love being helped, not pushed. Educate first, and conversion follows.

Ultimately, great psychological design reduces friction, directs attention, and connects emotionally.

It doesn’t shout — it guides.

Original article:

👉 Psychological Design: 7 Tactics to Convert Leads into Customers (Medium)

The Smartest Way to Capitalize on the AI Gold Rush

I recently watched Iman Gadzhi’s video on how to make the most of the AI wave.

It’s not revolutionary, but it hits a key truth: AI isn’t the destination — it’s leverage.

Here are the main takeaways:

1. AI is infrastructure.

   It’s the electricity, not the factory. What matters is what problem you’re solving and what value you’re creating with it.

2. The window won’t stay open forever.

   The current AI advantage is temporary. In a few years, using AI will be as normal as using Google.

   So the best move now is to take what you already know — your craft, your niche — and amplify it with AI.

He also made a solid point about focusing on specific, embedded tools, not general ones.

Don’t chase hype. Find the AI tools that truly speed up your own workflow.

In short, this gold rush isn’t about who digs faster — it’s about who digs smarter.

AI is leverage, not luck.

Original video:

👉 The SMARTEST Way to Capitalize on the AI Gold Rush - YouTube (Iman Gadzhi)

Hello, I’m Bear—a product designer, UX mentor and an award‑winning bilingual podcast host, currently living in Auckland, New Zealand. I enjoy sharing insights from my work, life, and study, helping all of us grow together.

Bear Academy Newsletter is my weekly email packed with thoughts on technology, design, and productivity—featuring book breakdowns, learning tips, and career reflections. Subscribe for free at bear.academy

💬 Contact

• Youtube.com/@Bearliu - A video is worth a thousand words

• bear@beartalking.com - The old fashion email way

• LinkedIn.com/in/bearliu - My professional life

• Beartalking.com - all my posts, in English and Chinese

• https://twitter.com/bearbig - Majorly I post in Chinese

Lately, I’ve been thinking, maybe as we get older, we finally realise the mind needs care and training, not just rest.
We hear this in our twenties, but it really sinks in later.
That “inner child” in us does need looking after.

This came up after I saw some harsh comments on social media.
I’ve been doing content for years and can handle it, but some words still sting.

While walking yesterday, I had a good chat with ChatGPT and started to understand myself better.
So I made a “Feedback Gallery” in Notion.

It has three parts:

1. Action, feedback I can use to improve

2. Energy, both praise and criticism. I save the positive ones for when I feel low, and only glance at the negative when needed

3. Inspiration, ideas or comments that spark creativity

I’ve tried this before, but lost the habit when switching tools.
This time, I’m bringing it back, especially the “Energy” part.
When I’m doubting myself, reading kind words really helps.

As a designer and creator, it’s easy to wonder,
“Is my work good enough, does it matter?”
In those moments, this little jar becomes a quiet reminder,
yes, it does.

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It’s Time to Strengthen My Mental Capacity

I’ve decided to start intentionally taking care of my mental capacity.

We all understand the importance of physical health. If your body breaks down, your energy follows, and energy itself is a kind of capability.

But what I mean by mental capacity isn’t just willpower or some kind of motivational talk.
It’s not the same as intelligence or logic, either.

In the AI era, skills like analysis, memory, and even decision-making aren’t rare anymore.
AI can often do those faster and better than us.

What can’t be replaced is your ability to
know which thoughts are worth following,
decide what really matters,
stay curious and go deeper when others stop at the surface,
and see the essence of a situation through the noise.

That’s what I call mental capacity — the ability to stay calm, focused, and clear in a world full of distractions.

We may no longer be “knowledge workers” in the traditional sense.
Knowledge is cheap now. Search engines and AI can pull it up in seconds.

The real challenge is whether you can make sense of all that noise,
whether you can direct your attention, manage your thoughts, and stay steady without being swept away by everything around you.

That’s what we need more of,
not more information,
not faster responses,
but a mind that sees clearly, acts with intention, and stays grounded.

In this age, being smart is no longer enough.
What’s rare, and truly powerful, is having mental capacity.

Where Do Hairstylists Keep Their Portfolios?

The other day I got a haircut and chatted with the stylist — or “Tony老师” as we say in China. He told me people in their industry often switch jobs, and I asked, “Do you have an app to find jobs or manage clients?”

He said, “Not really, but we all use Dianping’s pro version.”

Turns out, Dianping (like Yelp) has a “professional mode” for service workers like hairstylists and massage therapists.
It shows their reviews, ratings, and work history — and the data follows the person, not the salon.
So when they move jobs, their record moves with them.

In short, their Dianping profile is their portfolio.

After the haircut, he asked me to leave a review.
He even helped: took my phone, used voice input to say, “Nice cut, great service,” added a photo, and done.
Smooth, practiced, and effective.

That’s a real-world testimonial system.
We product people can learn a lot from it.

An Investor’s Take on Small Projects, and What It Made Me Think About

A few days ago, I joined an event as a guest speaker about building products.

The first speaker was an investor who shared what she looks for in small, independent projects. Her points really made me think.

Here’s what she said investors like to see:

1. A working product demo, even if it’s early

2. Some value validation, a little revenue helps

3. A full-time team, not just one person

4. At least six months of operation

When I heard this, I thought, maybe our product JAM actually checks all those boxes.

It might be a good time to think about raising funds.

But I kept wondering, why did she highlight “six months”?

Later I realised it’s about retention.

Getting lots of users at launch looks great,

but if 90 percent leave the next month, it’s not sustainable.

A product with steady retention, like losing only 30 percent, is much more solid and safer to invest in.

That got me thinking more seriously about JAM and growth.

If you’re building something too,

are you planning to raise money?

How do you think about timing?

A Reminder to Look Up from the Internet

Spending too much time online, it’s easy to forget to check in with the real world. Social platforms, especially places like Twitter, often distort reality: magnifying fringe opinions until they feel like universal truths.

Take this comment I saw recently:
“Surely no one goes to photo studios for ID photos anymore? AI headshots are so realistic now.”

That’s a classic example of being disconnected from how things actually work offline. It’s a projection from a small bubble, not a reflection of the broader world.

So here’s a gentle reminder: step outside, pay attention to the real world. It’s often very different from what your feed is telling you.

Code ≠ Software

Writing code is not the same as building software.
Just like sketching a design by hand is not the same as launching a real product.

A quick self-reminder: once it gets down to pushing pixels, there’s still a lot of detailed work to be done.

The Amazing Art of the Video Game Marquee

I came across a wonderful post by Dan Sinker titled “The Amazing Art of the Video Game Marquee.” He visited an arcade museum in Chicago that houses more than 800 playable machines — the largest collection in the world. For just $25, visitors can play all day, surrounded by the glowing nostalgia of 1980s arcade culture.

But the real story isn’t about the games themselves; it’s about the artwork that crowned them. In the pre-Internet era, every arcade cabinet had a backlit marquee — a single static image that had to grab your attention from across a noisy room. With no trailers, screenshots, or influencer reviews, the marquee was the only advertisement a game had. Designers relied on vibrant colour, heavy contrast, and wild typography to make players stop, look, and spend a coin.

Sinker photographed dozens of these marquees, and they look astonishingly like the spiritual ancestors of modern YouTube thumbnails. Before social media, this was how attention was engineered — through pure, analogue design.

What struck me most was the irony: I’ve never actually played any of the games shown in those marquees, yet the images still hit me with a sense of recognition. It’s a reminder that strong visual storytelling transcends time and technology — whether it’s a glowing sign on a 1980s arcade cabinet or a thumbnail on today’s feed.

Original article:

👉 The Amazing Art of the Video Game Marquee — dansinker.com

Hello, I’m Bear—a product designer, UX mentor and an award‑winning bilingual podcast host, currently living in Auckland, New Zealand. I enjoy sharing insights from my work, life, and study, helping all of us grow together.

Bear Academy Newsletter is my weekly email packed with thoughts on technology, design, and productivity—featuring book breakdowns, learning tips, and career reflections. Subscribe for free at bear.academy

💬 Contact

• Youtube.com/@Bearliu - A video is worth a thousand words

• bear@beartalking.com - The old fashion email way

• LinkedIn.com/in/bearliu - My professional life

• Beartalking.com - all my posts, in English and Chinese

• https://twitter.com/bearbig - Majorly I post in Chinese

If you follow me on Twitter, you probably know that I’ve just made a sudden trip back to China because my father has been unwell. As with last time, it all happened quite abruptly, so the first half of October was a bit of a blur, with lots to juggle. Work naturally went on pause, including this newsletter.

The good news is that my father’s surgery went smoothly and his recovery is going well. For me, that means I can finally take a breather and ease back into a work rhythm.

So, the newsletter is back.

Recently, I also shared a few thoughts about this trip home and caring for family at a “出海去” community event. I’ll include some of that in this issue as well.

Right then, let’s get started.

How I Restarted My Life in 2025: Three Stories

When “stability” turns into a trap.

In 2025, I left a large company, navigated a family health crisis, and truly began building from scratch.

This isn’t a swashbuckling quest for freedom. It’s the discipline of rebuilding a system.

In this episode, I share three honest stories that changed my course —

about work, life, and the courage to stay clear‑headed in the midst of chaos.

If you’re at a crossroads too, I hope this gives you a measure of strength.

The train of midlife hasn’t stopped. It has simply switched tracks

Flying back to care for my dad, it hit me: this is a turning point. Ageing parents, hospitals, paperwork and bedside hours arrive all at once. On paper we’re more capable and earn more than in our twenties, yet the stakes are higher too. The real challenge is holding up both ends, caring upwards and downwards, while not dropping yourself.

These years have nudged me closer to Stoicism: first separate what I can and can’t control, then look for something to learn from the experience, even if it isn’t obvious yet. I thought this trip had no “meaning”. In time I realised it pulled me back to a simple question: what am I living for?

Those days in the ward made one thing crystal clear: my family in New Zealand is my anchor. Projects, achievements and titles I once clung to, however shiny, all take a bow eventually. Some end neatly. Some end abruptly. We do not get to script every scene.

So I’m calling this my “midlife calibration”. It forces a refocus: what is worth my time, money and care, and what isn’t. Close the taps that drain you. Keep what truly matters.

Midlife is not a crisis. It is a chance to set off again on a better line.

Can AI Make Design Faster?

AI has already proven it can make programming way more efficient. The real question is—can it do the same for design? Some people think it’s impossible. Others believe AI will take over design completely.

From what I’ve seen, the truth is somewhere in the middle. If you get comfortable with AI tools, you can definitely work three to five times faster while keeping the same quality.

Here’s a recent example from my own work. Our spoken English training app, JAM, is adding its most important feature yet: themed practice packs. Before, the app was pretty basic. With themed packs, it feels like a proper learning tool, which allows users to pick a topic and practice speaking around it.

This project took me about three days, around 20 hours of work. I handled everything:
• Research
• Building the course plan
• Designing the themed training content
• Creating the theme cards
• Finishing the UI design

If I hadn’t used AI, this would have been a team job. At least a UI designer, a content designer, and a copywriter working two to three weeks—and maybe even an education consultant. This time, I pulled it off solo.

The tricky part is knowing the details, just like in programming:
• When it makes sense to let AI generate images
• Which tool to use: ChatGPT, NanoBanana, or something else
• How to make sure the course content is accurate
• How to keep everything stable and consistent

That’s where experience comes in. And that’s also why I see a shift happening. Programmers who adapt to AI and know how to use it well are becoming more valuable, not less. I think the same applies to designers. The key is knowing when to step in yourself, and when to let AI take over.

ChatGPT Operator & Agents: The First Official Demo

I recently revisited OpenAI’s official video, Introduction to Operator & Agents.

There are tons of tutorials on YouTube already, but when it comes to brand-new features like this,

I always think the best way to understand them is to go straight to the source.

In this session, Sam Altman and three product leads demonstrate how the new Operator system allows ChatGPT to actually do things — like ordering food, booking tickets, or buying stuff online.

It’s not just about conversation anymore; it’s about execution.

A few key takeaways:

1. It runs on real integrations.

   Each Operator needs access to external APIs or services — it’s not magic, it’s infrastructure.

2. It confirms before acting.

   Whenever money or booking is involved, ChatGPT explicitly asks for user confirmation. That’s an important safety layer.

3. It feels more like an assistant than a chatbot.

   You talk, it acts. The line between “AI chat” and “digital assistant” is getting thinner.

I once built a simple Operator myself that sent ChatGPT outputs straight into Google Sheets — it worked pretty well.

But after I stopped my Pro subscription, I shelved it.

Now I’m curious what others are using to create similar automated workflows today.

Original video:

👉 Introduction to Operator & Agents - YouTube (OpenAI)

Hello, I’m Bear—a product designer, UX mentor and an award‑winning bilingual podcast host, currently living in Auckland, New Zealand. I enjoy sharing insights from my work, life, and study, helping all of us grow together.

Bear Academy Newsletter is my weekly email packed with thoughts on technology, design, and productivity—featuring book breakdowns, learning tips, and career reflections. Subscribe for free at bear.academy

💬 Contact

• Youtube.com/@Bearliu - A video is worth a thousand words

• bear@beartalking.com - The old fashion email way

• LinkedIn.com/in/bearliu - My professional life

• Beartalking.com - all my posts, in English and Chinese

• https://twitter.com/bearbig - Majorly I post in Chinese

I’ve had plenty of failed projects before I started JAM. The difference this time is that I actually used those past mistakes to guide me -- and so far, it seems to be working out.

The first big lesson: don’t just build something because I think it’s cool. I used to create projects around my personal interests without ever checking if they mattered to anyone else. For example, I once built a website where I shared AI tips and little tech experiments. I loved writing about how to build, distribute, and collect information. But the truth? Nobody else really cared. I had no idea who the site was for or who the audience was supposed to be.

With jam, I flipped the script. I validated the idea first. One of my tweets about improving spoken English blew up, and that was the signal. People actually wanted it, they engaged with it, they needed it. That became rule number one: validate first. I’ll share the other rules later.

The second big shift was thinking about monetization from day one. In the past, I’d make something just for fun and then scramble to figure out who might pay for it. This time, I built a super rough prototype, sent it to real people, and included a survey. More than half said they’d pay if it became a polished product. That was my green flag.

So yeah, JAM is basically built on the back of all my past failures. And honestly, I’m curious to see what lessons come out of this one.

It’s hitting $300 MRR in under a month - so the ride is just getting started.

Weekly goodies

How I Use 12 Words to Get 10x Better AI Answers (My Simple Prompt System)

Do you ever get frustrated with AI giving you unreliable, messy, or off-target answers? This video will show you how to fix that. I’ll share the three simple prompts—just 12 words in total—that I use every day to get accurate, logical, and perfectly aligned results from any AI model.

In this comprehensive guide, you’ll learn the core principles of effective prompting. Discover how to turn your AI into a reliable collaborator rather than just a “magic box” that gives you noise. I’ll break down the what, why, and how of using prompts like:

“Fact check this”: To turn your AI into a critical internal editor that flags shaky or nonsensical claims. This is a key principle for ensuring accuracy and transparency in your output.

“Think step by step”: To force the model to slow down and show its reasoning, leading to more structured and accurate answers. This is also known as Chain-of-Thought (CoT) prompting.

“Ask me questions to clarify”: To get your AI to collaborate with you by asking questions that can improve the final result and align it with your goals.

Don’t just use AI; learn how to talk to it. These simple principles will help you handle 80% of your tasks, from writing and coding to research and business planning.

[Ad] Build Confidence in Speaking English—Start with JAM

JAM is a one-minute speaking practice app: random topics, 60 seconds of nonstop talking, and an AI coach named Jammy who corrects you instantly and shows better phrasing. One minute a day is enough to go from “too shy to speak” to “speaking naturally.”

Newsletter readers get an exclusive bonus: 1 month free membership (worth $5). Start your 30-day challenge now, and in a month you’ll be surprised by how much smoother your English sounds.

👉 Join the challenge

Vibe Coding and the Future of Development (Alex P)

Original link

A reflection on vibe coding: AI agents execute, engineers approve. Core practices like TDD, code reviews, and CI remain essential. A notable prediction is Prompt Management Systems to version prompts, track impact on code, and tag AI‑generated sections. It also nudges designers to co‑create with AI rather than only execute.

The Secret Science of Perfect Spacing (Chainlift)

Original video

Three takeaways: what looks symmetrical often isn’t mathematically; visual weight matters; and related elements should live closer. Typography and spacing drive most of the perceived quality. The video also mentions a handy tool called Lift Kit.

Re‑post Your Old Videos to Blow Up Your Business (Ed Lawrence)

Original video

Repost proven content 6–12 months later with a new title and thumbnail, and film a fresh intro to modernize it. Optionally prune low‑retention segments based on the old retention graph. Most of your current audience never saw the original, so this is efficient reach.

Hello, I’m Bear—a product designer, UX mentor and an award‑winning bilingual podcast host, currently living in Auckland, New Zealand. I enjoy sharing insights from my work, life, and study, helping all of us grow together.

Bear Academy Newsletter is my weekly email packed with thoughts on technology, design, and productivity—featuring book breakdowns, learning tips, and career reflections. Subscribe for free at bear.academy

💬 Contact

• Youtube.com/@Bearliu - A video is worth a thousand words

• bear@beartalking.com - The old fashion email way

• LinkedIn.com/in/bearliu - My professional life

• Beartalking.com - all my posts, in English and Chinese

• https://twitter.com/bearbig - Majorly I post in Chinese

Every time someone asks why I quit my job, I usually share a list of reasons.
Here’s just one, along with some advice.

If you’re working full-time today, there are only three ways to guard against an uncertain future:
• Your money makes money (investments)
• You have a side project or business
• You were born into wealth

Which one are you?

The corporate ladder is not what it was 10 or 20 years ago. The old model of steady job and steady promotion is broken.
Sooner or later, your cost-to-value ratio will not beat algorithms and machines.

Companies are clear about this: AI is here to cut costs. And in that equation, you are the cost.

If you have alternative income, you are safer.
If not, the day will come when you either leave on your own terms or you are forced out.
And the higher your position, the bigger the impact.

We are no longer in a black swan era.
We are living in a black swan farm.
Unpredictable shocks are constant: industry shifts, geopolitics, identity politics. Our parents never had to think about these things. We do.

My advice: even if you think your job is stable, use at least 20 percent of your time to invest in yourself.
Learn new skills.
Protect your health.

The next three to five years will reshape entire industries.
Most people will not notice until it is too late, like the frog sitting in the pot while the water gets hotter.

Weekly goodies:

“How I Turned a $150 Month into a $1M Challenge” - Florin Pop’s Indie Hacker Story

What does it really take to go from a $150 side hustle to building a $1M challenge in public?

In this episode of BearTalk, I sit down with Florin Pop, an indie hacker and creator who left his developer job in 2019 with just six months of savings. Florin shares how he built his audience, launched viral challenges, sold his first startup, and now tracks his ambitious $1M journey live on the internet.

You’ll learn:
• Why building in public creates accountability—and pressure
• The frameworks Florin uses to validate ideas quickly
• How to turn small MVPs into real revenue
• The psychology behind pricing and why “water costs $1 or $4” is the best analogy
• Why long-term consistency beats burnout sprints

Whether you’re a product designer, developer, or aspiring indie hacker, this episode will show you the mindset, tools, and strategies to start your own journey.

[Ad] Build Confidence in Speaking English—Start with JAM

JAM is a one-minute speaking practice app: random topics, 60 seconds of nonstop talking, and an AI coach named Jammy who corrects you instantly and shows better phrasing. One minute a day is enough to go from “too shy to speak” to “speaking naturally.”

Newsletter readers get an exclusive bonus: 1 month free membership (worth $5). Start your 30-day challenge now, and in a month you’ll be surprised by how much smoother your English sounds.

👉 Join the challenge

A Practical Guide to Motion in Product Design

Original link

I came across a super practical article by Bryan Maniotakis called “How I Approach Motion in Product Design.” It’s packed with simple, actionable advice on how to use motion to create a better user experience. Instead of getting bogged down in technical details, he focuses on the core principles: using motion to guide attention, add a sense of delight, and improve navigation. It’s a great reminder that animation isn’t just a decoration; it’s a critical part of the design.

I think this is exactly what product designers need. It feels like a lot of designers, including myself, get intimidated by motion. But this article breaks it down into easy, fundamental stuff that anyone can apply right away. For instance, he points out that a good default animation time is around 300ms, and that bigger elements should move slower, just like in the real world. I’ve been exploring Rive to get my feet wet with animation, and these principles are a perfect guide for a beginner like me. A little motion can go a long way.

AI Generates Design Systems in Seconds?

Original video

Designer Andres The Designer dives into Relume’s AI tool that promises to generate full websites with design systems in just seconds. The real magic comes afterwards: you can take that system straight into Figma via the Relume plug-in, tweak the details, then export it into Framer through another plug-in, and publish live instantly. The flow looks almost surreal—AI-powered generation, human fine-tuning, and smooth handoff all the way to a working site.

From my perspective, this is exactly the kind of workflow I want to try. It could be game-changing for building landing pages quickly, especially when tied to my Jam project. Seeing a pipeline of Relume → Figma → Framer → Publish makes me think this might soon become the new normal for solo designers.

Is AI the Future of Design Systems? (by Arnau Ros)

Original video

In this video, designer Arnau Ros explores Relume’s AI-powered Style Guide Generator. The tool can build a complete design system in just seconds, starting from your chosen colour palette. Traditionally, designers spend hours setting up grids, colours, and typography, but here the process is almost instant. Once generated, the system can be taken into Figma for further design work, and then pushed to Webflow to create live websites. It’s a neat workflow for anyone working under tight deadlines or exploring rapid prototyping.

I could feed Jam’s colour palette into Relume and get a ready-made design system. That becomes both a starting point for Jam’s landing page and a hands-on tutorial I can share. Watching the tool spin up a system so quickly feels like a productivity boost I wish I had years ago.

Hello, I’m Bear—a product designer, UX mentor and an award‑winning bilingual podcast host, currently living in Auckland, New Zealand. I enjoy sharing insights from my work, life, and study, helping all of us grow together.

Bear Academy Newsletter is my weekly email packed with thoughts on technology, design, and productivity—featuring book breakdowns, learning tips, and career reflections. Subscribe for free at bear.academy

💬 Contact

• Youtube.com/@Bearliu - A video is worth a thousand words

• bear@beartalking.com - The old fashion email way

• LinkedIn.com/in/bearliu - My professional life

• Beartalking.com - all my posts, in English and Chinese

• https://twitter.com/bearbig - Majorly I post in Chinese

Today, let’s talk about how AI is changing the way we design.

No one argues anymore about AI making coding faster—it clearly does. But what about design? Some people say it’s impossible. Others think AI could even replace designers altogether. From my experience, if you know how to use the right AI tools, you can get three to five times faster while keeping the same quality.

Take a recent project of mine: our English-speaking app JAM is rolling out its most important new feature—topic packs. Before, practice was one-size-fits-all. With topic packs, it feels like a proper language-learning app: users can pick a theme and practise conversations around it.

This design took me about three days—roughly 20 hours. Here’s what was involved:

• Research

• Mapping the curriculum

• Writing the training content

• Generating topic cards

• Finalising the UI design

Without AI, this would’ve taken at least three people—a UI designer, a content designer, and a copywriter—two to three weeks, plus input from an education consultant. This time, I did it solo.

The trick, just like in coding, lies in the details:

• When to generate images with AI

• Whether to use ChatGPT, NanoBanana, or another tool

• How to keep the course content accurate

• How to ensure the overall project stays consistent and stable

These decisions need someone with hands-on experience. That’s why we’re seeing a shift: older developers who can master AI aren’t being left behind—they’re in higher demand because they deliver more. I believe the same applies to designers. The key is knowing when to step in yourself, and when to hand things over to AI.

This Week’s Video

How I Made AI 10× Smarter with Just 12 Words (My Minimal Prompting Framework)

Still frustrated by messy AI answers? The problem isn’t the AI—it’s the prompt.

In my latest video, I share three simple prompts—just 12 words in total—that completely changed how I use AI in design, tech, and productivity. Learn them once, and you can turn any AI into a reliable teammate that gives structured, accurate, logical answers.

[Ad] Build Confidence in Speaking English—Start with JAM

JAM is a one-minute speaking practice app: random topics, 60 seconds of nonstop talking, and an AI coach named Jammy who corrects you instantly and shows better phrasing. One minute a day is enough to go from “too shy to speak” to “speaking naturally.”

Newsletter readers get an exclusive bonus: 1 month free membership (worth $5). Start your 30-day challenge now, and in a month you’ll be surprised by how much smoother your English sounds.

👉 Join the challenge

[Ad] In the Age of AI, What’s Your Human Superpower?

AI is coming like a tidal wave. Those who just stand on the beach will get swept away. But those who learn to surf will see farther from the crest of the wave.

AI brings speed, scale, and efficiency. Humans bring empathy, creativity, and connection. In our Bear with AI community, we explore how to combine the best of both worlds—human and machine—so you can ride the wave instead of being crushed by it.

Courses: 10+ hands-on classes balancing AI skills with human strengths
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Join the waitlist today, and you’ll be first to know when early access opens.

https://bearwith.AI

This Week’s Picks

1) The 3-2-1 Speaking Trick: Cut the Rambling

Original video

Ever freeze up when called on to speak? Or ramble without structure? Communication coach Vinh Giangshares a simple framework: 3-2-1.

1. One core idea

2. Two perspectives or counterpoints

3. Three practical steps

This gives your speech a “skeleton” that makes it sharper and easier to follow.

It fits perfectly with the JAM app—especially for one-minute random topic practice. I could easily see this framework becoming part of JAM’s resource library or a future course pack.

2) The Simple Formula for $100K a Month (@tibo_maker)

Original post

How do you hit $100K monthly revenue? In theory, it’s simple: sell a $50 subscription to 2,000 people. The hard part is finding those 2,000.

Tibo’s approach: spend 50% of your time building, 50% finding customers. “Content isn’t marketing—it’s your lifeline.”

That matches my own experience: success doesn’t just come from the product itself, but from consistent sharing, building in public, and engaging honestly with users. That’s why I stick with newsletters, YouTube, and Twitter.

3) YouTube Growth Hacks from Noah Kagan

Original PDF

Plan thumbnails before filming—shoot 50+ if needed to find the best. Use KeywordTool.io and AnswerThePublic for ideas. If one video spikes in subscribers, make a follow-up fast. Start with a click-worthy title, then swap to an SEO-optimised one after the algorithm picks it up.

Grassroots tactics work too: offer giveaways (Noah once gave away a $1,300 MacBook Pro and gained ~400 subscribers—about $3 each). Use YouTube Community posts. Keep titles at 30–45 characters with numbers or brackets. Naturally weave in keywords during the video. Mix in screenshots and B-roll. Use “teasers” mid-video to keep people watching. And don’t be shy about cold-emailing other creators—you can find contacts on their About page.

Hello, I’m Bear—a product designer, UX mentor and an award‑winning bilingual podcast host, currently living in Auckland, New Zealand. I enjoy sharing insights from my work, life, and study, helping all of us grow together.

Bear Academy Newsletter is my weekly email packed with thoughts on technology, design, and productivity—featuring book breakdowns, learning tips, and career reflections. Subscribe for free at bear.academy

💬 Contact

• Youtube.com/@Bearliu - A video is worth a thousand words

• bear@beartalking.com - The old fashion email way

• LinkedIn.com/in/bearliu - My professional life

• Beartalking.com - all my posts, in English and Chinese

• https://twitter.com/bearbig - Majorly I post in Chinese

Everyone reading this has lived through at least one black swan event: COVID. I was no exception.

Back in 2019, I had just broken into the field I’d been dreaming about for years—product design—when I joined Les Mills International in New Zealand. You’ve probably heard of Les Mills: it started as a gym brand, but its real business became creating fitness content and licensing it to gyms and instructors worldwide. For a long time, the model was rock solid.

I joined the digital products team that served gyms and instructors. The work was exciting, fresh, and full of learning. We ran workshops, launched new projects, and even had team-building sessions led by world-class trainers. Honestly, I was riding high. I even considered getting certified as a Les Mills instructor myself—an employee perk.

(That’s a photo from our annual company meeting, with Philip Mills speaking. Sixty-something, still built like an athlete, one of the best NZ CEOs. I really admire him)

At the end of 2019, the outbreak began in China. By early 2020, things still felt normal in New Zealand, but we were glued to the news from home—it was surreal. During one workshop on future risks and challenges, I suggested “a global pandemic.” The whole room, including my manager, laughed it off. Someone joked I’d just watched too many zombie movies—maybe I was expecting World War Z to start.

By March, New Zealand closed its borders and went into an unprecedented level-four lockdown. A full month at home. The black swan had arrived. Our team was cut, and the company came close to collapse.

But here’s where things turned. A few years earlier, Les Mills had planted a small seed (a side project): an online fitness content service. It had been limping along, never really taking off. Then in that single month, subscriptions to Les Mills On Demand skyrocketed, matching the growth from the previous five years combined. Global license fees dried up, cash flow took a beating, but that little side project kept the company alive.

What’s true for companies is just as true for individuals. Building a side project, a small venture on the edge, can be the thing that saves you when a black swan lands.

And that product manager who once laughed at my “zombie-movie” comment? He later sent me a message apologizing. Respect.

So, in an age of Black Swans, what’s your lifeline project?

Weekly Goodies

"How I Turned a $150 Month into a $1M Challenge" - Florin Pop’s Indie Hacker Story

What does it really take to go from a $150 side hustle to building a $1M challenge in public?

In this episode of BearTalk, I sit down with Florin Pop, an indie hacker and creator who left his developer job in 2019 with just six months of savings. Florin shares how he built his audience, launched viral challenges, sold his first startup, and now tracks his ambitious $1M journey live on the internet.

AI is a Floor Raiser, not a Ceiling Raiser

I recently came across an interesting article by the Elroy Team titled "AI is a Floor Raiser, not a Ceiling Raiser." What I found most valuable were the simple charts in the post that perfectly illustrated AI's role in the learning process. It really made me reconsider how we should be leveraging AI.

My Take:

The core insight is this: the traditional learning curve starts slow, but with AI, that initial hump can be massively accelerated.

Picture it like this: when you start a new skill, the beginning is always the hardest. But with AI's help, it can meet you at your exact skill level, answer your specific questions, and even handle the rote, repetitive work for you. This essentially raises the "floor," giving you a powerful boost right out of the gate.

However, the article also brought up a crucial warning: after that initial speed boost, if you just passively "cheat" and let AI do all the heavy lifting, you'll hit a plateau. You won't make any real progress because you're not putting in the human effort. It's like using a cheat code in a video game—you advance quickly at first, but you're not actually improving your own skills.

This is exactly why I created the JAM app. My goal was to build a tool that uses AI as an accelerator, not an excuse for laziness. It can help us focus on the more valuable parts of learning, but it still demands our own thinking and effort to truly internalize the knowledge.

That's how we move from simply using AI to actually leveraging it to become a better version of ourselves.

Original article: https://elroy.bot/blog/2025/07/29/ai-is-a-floor-raiser-not-a-ceiling-raiser.html

How to Design for Short Attention Spans

Let’s be honest: people don’t read websites anymore. They scan, they swipe, and they scroll like their thumbs are training for the Olympics. So how do we, as designers, capture their attention in this “Attention Deficit Era”? Ryan Almeida, in his article on Muzli, shares some fantastic, no-nonsense principles for designing with this reality in mind. The core idea? Embrace the chaos and design for clarity, not cleverness.

My Two Cents:

As a product designer, I’ve been thinking about this a lot. The article hits on so many things that feel incredibly true right now. We all know that feeling of being overwhelmed, and as designers, our job is to make sure our users feel empowered, not frustrated.

Here are the biggest takeaways that resonated with me:

• One job per screen: This is a big one. It's so easy to cram everything onto a single page, but that just creates decision paralysis. One clear call-to-action per section is a game-changer.

• Immediate feedback: When a user taps or clicks, they need to know it worked instantly. That little visual cue isn’t just a nice-to-have; it's a critical part of the user journey.

• Predictable doesn't mean boring: This is a phrase I’m going to start using. We often chase novelty, but predictability builds trust. A familiar button layout or icon helps users feel comfortable and in control.

• Test on real devices: No excuses here. Emulators are great for a quick check, but there’s nothing like seeing your design on a real phone or tablet in a real-world context.

This is a great reminder that good UX is all about empathy. We're not just moving pixels around; we're crafting an experience for real people with real lives and very little time to spare.

Original article: https://medium.muz.li/how-to-design-for-short-attention-spans-34369615827a

[ AD ] Speak English with confidence — in just 1 minute a day

JAM is the one-minute speaking app: pick up a random topic, talk for 60 seconds, and get instant AI feedback from Jammy. Fast, fun, and confidence-boosting.

Newsletter bonus: grab 1 month free (worth $5) and join the 30-day speaking challenge. One minute a day — see how fluent you sound in just a month.

👉 Start the challenge

Hello, I’m Bear—a product designer, UX mentor and an award‑winning bilingual podcast host, currently living in Auckland, New Zealand. I enjoy sharing insights from my work, life, and study, helping all of us grow together.

Bear Academy Newsletter is my weekly email packed with thoughts on technology, design, and productivity—featuring book breakdowns, learning tips, and career reflections. Subscribe for free at bear.academy

💬 Contact

• Youtube.com/@Bearliu - A video is worth a thousand words

• bear@beartalking.com - The old fashion email way

• LinkedIn.com/in/bearliu - My professional life

• Beartalking.com - all my posts, in English and Chinese

• https://twitter.com/bearbig - Majorly I post in Chinese

Not long ago, I had a conversation with a developer friend about a problem every indie maker secretly fears: what if someone copies your product?

I tweeted a few initial thoughts of my own:

1. Go vertical — pick a niche too small or boring for big players to care.

2. Build user lock-in — the more data and habits people create, the harder it is to leave.

3. Relying on technical moats is almost impossible in the AI era.

4. Put your personality into the product — copying features isn’t the same as copying a person.

That tweet sparked a lively discussion. I’ve pulled together some of the best insights, along with a few real-world cases that show how copycats work — and how you might survive them.

1. The Harsh Reality

The first point many people made: you can’t really prevent copying.

In tech, technical moats vanish quickly. If your idea shows traction, larger players with bigger teams and more resources can replicate it fast.

Think of Snapchat’s Stories feature. It was novel when it launched, but soon Instagram, WhatsApp, and Facebook all rolled out their own versions. Snapchat didn’t disappear, but its growth ceiling was capped.

So the question isn’t “how do I stop them from copying?” It’s “what can I do that makes copying less damaging?”

The newsletter is sponsored by JAM

Learning English isn’t about memorising words—it’s about speaking out loud.

JAM is a one-minute speaking practice app: pick a random topic, talk for 60 seconds, and get instant AI feedback on pronunciation, grammar, and fluency. Just one minute a day takes you from “too shy to speak” to “ready to express yourself.”

Special for newsletter readers: claim 1 month free membership (worth $5) and start your 30-day speaking challenge. One minute a day—see how fluent you can become.

👉 Join the challenge

2. Common Survival Strategies

Go Niche

One way is to build in markets too small or too weird for giants to care.

CAD plugins are a classic example: obscure, technical, but enough to sustain small teams.

Notion is another: it didn’t try to be a universal Word or Excel killer. It built a modular, flexible workspace that appealed to a niche of knowledge workers and slowly expanded outward.

Build User Lock-in

If users accumulate data, history, or workflows in your product, leaving becomes painful.

Evernote, at its peak, had this power. Even when Microsoft made OneNote free, many users stuck around because moving years of notes wasn’t worth it.

Outrun the Copycats

Speed is often the only real moat. Indie teams can ship faster than giants.

One founder in my mentions put it bluntly: “By the time a competitor copied one of our features, we’d already launched three new ones.”

Contrast that with Clubhouse. When it exploded in 2020, Twitter, Facebook, and Spotify all launched audio rooms within months. Clubhouse couldn’t ship fast enough, and the hype evaporated.

Personality and Brand

Features can be copied. Personality can’t.

Basecamp (formerly 37signals) is a great case. Its project management software has always been simple, even minimal. But its contrarian brand voice and “less is more” philosophy built a loyal user base that Microsoft Project could never touch.

Community and Story

Another strategy is to build around people, not just features.

TikTok is the obvious case. Instagram and YouTube copied its short video format, but TikTok’s algorithm, culture, and creator community made it irreplaceable.

Users don’t just want features — they want the vibe, the story, and the people behind them.

3. Alternative Plays

Not every solution is about fighting. Some creators suggested taking the opposite route:

• Sell early: If a giant wants to copy you, maybe being acquired is the cleanest exit.

• Lean into being small: A product that only makes “enough” money can still be a sustainable indie business, even if it’s not defensible at scale.

• Get funding: If your idea is truly big, raising capital before launch can create a moat that scares copycats away.

And of course, there’s the zen approach: don’t care too much. If someone copies you, it means you were onto something.

4. My Take

As indie makers, we’re almost guaranteed to face copycats at some point. But the game isn’t about stopping them. It’s about making yourself harder to replace.

That could mean:

• Picking niches too weird or too deep for big players.

• Shipping so fast that competitors are always behind.

• Putting yourself, your personality, and your brand into the product.

• Building a community around your work, not just a feature set.

Copycats can steal your idea, but they can’t steal you.

If your product gets cloned tomorrow, what’s your move: fight back head-on, or run faster than everyone else?

Video version:

Goodies this week

A Landing Page Design with Premium Feel

Basit A. Khan shared the first look at his new landing page design on X. Designers call it “clean,” clients call it “premium,” and he simply calls it “done.”

The highlight here is in the hero section — an abstract animated background combined with blur and glass transparency effects, giving it an instant sense of elegance and futurism. It’s deceptively simple, though the glass effect likely requires code to implement so it maintains both visual quality and performance.

My personal take:

I love this “less is more” approach to achieving a premium look. For tech brands especially, the clean + futuristic visual language works beautifully. Often, it’s not about piling on elements, but about using a few precise visual techniques to convey the brand’s essence. If you’re working on a website and want to communicate innovation and forward-thinking, this style is absolutely worth exploring.

Original link (post): https://x.com/basit_designs/status/1953476697497452933

Diagram-to-Vid: A Creative Way to Use Veo3

This post from Rory Flynn shows a super creative way to use Veo3 for video creation. Instead of just typing a prompt, he demonstrates a "Diagram-to-Vid" approach where you can draw directly on an image to specify exactly how you want the motion to look. He gives examples like pulling the camera back, applying a motion brush effect, and sequencing different actions, showing how you can get incredibly specific results from a simple visual guide.

My Take:

This is just too cool. What I love about this approach is that it makes me feel less like a prompt engineer and more like an actual creative director. In a traditional agency, a creative director would often sketch out a storyboard or draw arrows on an image to brief the team. This "Diagram-to-Vid" method with Veo3 feels exactly like that, but the AI is your motion graphics artist.

You find an image, add some notes and diagrams directly on it, and then get a result that feels like you've really "directed" it. It gives you so much more control and creative freedom than just a text prompt. This isn't just about making things; it's about giving a creative vision a tangible, executable form in a way that’s incredibly intuitive and powerful. This is the kind of AI-assisted creativity I get really excited about.

Original Post: https://x.com/Ror_Fly/status/1950352402416115788

How to MARKET a Viral App in 2025

Blake Anderson, an entrepreneur who has scaled apps to millions of downloads, breaks down his playbook for marketing a viral app in 2025. This YouTube video is the fourth part of a series, and it's full of practical, no-fluff advice. He boils it down to three core principles and three key methods, all designed to help you get your app in front of the right people.

My Take:

Watching this video felt like a wake-up call. We, as entrepreneurs and creators, spend so much time perfecting our product and maybe 20% on marketing. But Blake flips that idea on its head, advocating for an 80/20 split: 80% doing, 20% learning. That really hit home for me.

Here’s what resonated the most:

• Don't tell me how good your app is; tell me it can make my life better. He emphasizes that good marketing taps into basic human desires like social status and self-improvement. It’s not about features; it’s about the emotional benefit. This is a game-changer for how I think about pitching my own work.

• Rapid Iteration is key. The idea of testing four different hooks, finding the best one, and then doubling down is a powerful, practical strategy. It’s a scientific approach to creative work, which I love.

• Marketing is a skill you can learn and practice. I’ve always viewed marketing as something that “other people” do. But Blake's message is clear: every entrepreneur needs to be a marketer. I’m committing to spending at least an hour every day on social media marketing to practice this skill, because it’s a practical skill, and you only get better by doing.

This video is a great reminder that marketing isn't just a department; it's a core function of building a successful product. And the best way to get good at it is to just start doing it.

Original video:

The "Everything at Once" Approach

When you open a Chinese super app, you're not just accessing a single service; you're entering a full ecosystem. This design philosophy is known as progressive aggregation, which involves bringing many different services together onto a single screen and trusting the user to filter what they need. For example, the home screen for the Didi app isn't just for booking a taxi; it also offers grocery delivery, intercity buses, freight services, and even a finance tab where you can get a microloan or buy insurance. This is a stark contrast to Western apps like Uber or Google Maps, which use a sparse interface and guide you through a simple, three-step process. While this "all-in-one" approach may seem chaotic to Western users, it's considered efficient and familiar to local users.

The Reasons Behind the Design

So, why do these super apps look the way they do? There are three main reasons:

• Super app economics: In China, the cost of getting users to download an app is very high. Once a company secures that valuable space on a user's phone, they try to maximize the lifetime value of that user by cramming in as many services as possible. As one entrepreneur said, the goal is to be the one app that a user can't delete.

• Infrastructure and policy: China's unified QR payment system and real-name ID policies make it simple for companies to add new services on top of existing user data. For instance, an app like Didi already knows a user's commute habits and spending, which makes it easy to offer services like microloans or insurance within the same app.

• Culture: In many high-context cultures across China and Southeast Asia, an information-rich layout is seen as useful, not cluttered. This contrasts sharply with the Western ideal of minimalism. The more options available, the more it can feel like abundance and care, similar to how having twenty dishes on a table at a Chinese banquet or a Korean buffet is a sign of hospitality.

A New Perspective on Design Principles

The primary lesson here is that minimalism is a market preference, not a universal virtue. Before you decide a product's design is "too busy," consider your audience's culture, context, and their tolerance for density on a screen. In situations where customer acquisition costs are high and cross-service data can shorten a user's journey, a packed user interface may actually be more effective than a minimalist one, as long as the primary task remains clear.

This highlights a key difference between Western and Chinese design principles. Western design often uses progressive disclosure, where features are hidden until a user requests them. In contrast, Chinese super apps use progressive aggregation, putting all features upfront and trusting users to find what they need. Neither approach is better than the other; they are simply different adaptive strategies. The goal is to design for people, not for dogma.

So, the next time you see a super app with what seems like a chaotic design, remember that it's a reflection of unique economics, infrastructure, and a culture that creates abundance with care.

Watch video here:

Weekly Goodies

10 Principles for Designers in the Age of AI

Ryo Lu’s post on X reads like a “new age designer manifesto” for the AI era. Each point is short but loaded with intent:

• Don’t build slot machines

• Don’t fake humans

• Don’t hide the messy truths

• Don’t create black boxes

• Don’t make people feel stupid

• Don’t extract value or attention one-way

• Don’t optimize for vanity metrics

• Don’t gatekeep knowledge

• Don’t make tools that divide

• Don’t sacrifice agency for convenience

My personal take:

When I saw this post, one thought flashed in my mind: “This is exactly the manifesto of a designer in the AI age.”

Every “don’t” resonated deeply with me. As product designers, it’s easy to get seduced by features designed to boost engagement or vanity metrics, but this post reminds us to put human value first.

“Don’t build slot machines” — a blunt reminder to avoid creating “dark patterns” that exploit human weaknesses and cause addiction.

“Don’t hide the messy truths” and “Don’t create black boxes” — in the AI era, this is about transparency. Users deserve to know how a product works and why it makes certain decisions.

“Don’t make people feel stupid” — a good product should empower users, not leave them feeling helpless. It should respect their intelligence and agency.

Original link (post): https://x.com/ryolu_/status/1953112152199581742

The Future of AI in the Creative Industry

In this episode of The Futur, the conversation compares AI’s role in the creative field to the 1990s design “rule-breaking” era — when young designers reinvented how images were made. Today, AI is rewriting the rules again, speeding up creation, compressing timelines, simplifying workflows, and handling tedious tasks so creatives can focus on the ideas that matter.

Kevin Lau stress that thriving in the AI era means keeping both passion and detachment, embracing new tools, creating tangible and marketable ideas, collaborating effectively, and pushing for constant growth and innovation. AI can accelerate creativity, but its impact on jobs and the human experience is still uncertain.

I relate strongly to this perspective — AI is a booster, not a replacement for the core of creativity. Just as better tools don’t automatically make better art, the real value is in using the time and energy AI frees up to think deeper and craft better. In my own creative work, AI has stripped away repetitive chores, but the story and vision still need my own hands.

Original link (video):

A Landing Page Design with Premium Feel

Basit A. Khan shared the first look at his new landing page design on X. Designers call it “clean,” clients call it “premium,” and he simply calls it “done.”

The highlight here is in the hero section — an abstract animated background combined with blur and glass transparency effects, giving it an instant sense of elegance and futurism. It’s deceptively simple, though the glass effect likely requires code to implement so it maintains both visual quality and performance.

My personal take:

I love this “less is more” approach to achieving a premium look. For tech brands especially, the clean + futuristic visual language works beautifully. Often, it’s not about piling on elements, but about using a few precise visual techniques to convey the brand’s essence. If you’re working on a website and want to communicate innovation and forward-thinking, this style is absolutely worth exploring.

Original link (post): https://x.com/basit_designs/status/1953476697497452933

Hello, I’m Bear—a product designer, UX mentor and an award‑winning bilingual podcast host, currently living in Auckland, New Zealand. I enjoy sharing insights from my work, life, and study, helping all of us grow together.

Bear Academy Newsletter is my weekly email packed with thoughts on technology, design, and productivity—featuring book breakdowns, learning tips, and career reflections. Subscribe for free at bear.academy

💬 Contact

• Youtube.com/@Bearliu - A video is worth a thousand words

• bear@beartalking.com - The old fashion email way

• LinkedIn.com/in/bearliu - My professional life

• Beartalking.com - all my posts, in English and Chinese

• https://twitter.com/bearbig - Majorly I post in Chinese

Over the past month, I’ve been refining a new tool to improve spoken English: JAM. It officially launched two weeks ago, and today I’d like to share the story and the thinking behind it.

When I arrived in a new country at the “mature” age of 35, I had no connections, no work experience locally, and my English was clumsy at best. A few years later, I was working in one of the top tech firms and invited to speak on stage at international forums — all in English. How did that transformation happen? One simple method made the biggest difference. That method is now distilled into this app. I believe it can help others make the same leap.

One-Minute Practice Broke My Communication Barrier

When I first moved to New Zealand, I managed to find a job — but speaking was a real hurdle. My words were slow, heavily accented, and hesitant. Worst of all, I often resorted to saying nothing but “yes”, because I simply didn’t catch what people were asking.

Once, at the bank, the clerk asked if I wanted to cancel my card. I didn’t understand, felt embarrassed to ask again, and said “yes”. Walking out, I discovered my card had actually been closed. I had to shuffle back in to re-apply, red-faced.

That was when I realised the real barrier wasn’t vocabulary, but having the courage and fluency to speak out loud.

Later I joined a Toastmasters club, where I learned a simple but powerful exercise: pick a random topic and speak for one minute without stopping. The content didn’t matter — the point was to keep talking.

I began recording myself two or three times a day. After about a hundred rounds, something clicked: I stopped fearing mistakes. My English became more fluid. This single exercise helped me crush the biggest mental block — the fear of being wrong.

Traditional English learning is a bit like trying to master swimming on dry land — you might know the strokes, but the moment you get in the pool, you panic.

Most learners cram vocabulary and grammar, but when it’s time to speak, the mind goes blank. It’s not a lack of knowledge. It’s a lack of practice in real situations.

So I turned the method that worked for me into a tool: JAM (short for Just a Minute).

JAM is designed to prioritise speaking over memorising. Each session is just 60 seconds of talking, training your courage to speak and your improvisation skills. No need to wrestle with grammar first — you can start straight away. Afterwards, the AI gives you tailored feedback on what you actually said. With repeated practice, you break down that invisible wall of fear around speaking English.

And now, with a full English-language interface, JAM also works as a quirky speaking warm-up for native speakers — a way to stretch your improvisation muscles. Of course, it’s still most transformative for learners who want to finally break through.

Many people assume their English isn’t “good enough”, but often it’s already better than they think. What’s missing is the chance — and the nerve — to speak. JAM exists to create that chance. Each 60-second burst is a small but powerful step forward.

From “too shy to speak” to “speaking whenever you want” — that’s the shift JAM aims to make possible.

How JAM Helps You Build Spoken Confidence

JAM is a speaking practice app that turns spare minutes into mini speeches. Open the app, get a random topic, and talk for one minute. When you’re done, your AI coach, Jammy, instantly analyses your pronunciation, grammar, vocabulary, and fluency — and offers a polished example answer. Do it daily, and you’ll find yourself speaking with confidence in real conversations.

How it works

1. Open JAM, get a random prompt (e.g. “Describe your favourite travel memory”), and speak non-stop for 60 seconds.

2. Receive your score and a clear visual report.

3. Read Jammy’s corrections and model response, then practise shadowing it.

4. Repeat daily — just one minute — and your fluency will climb naturally.

Who it’s for

• People living, studying, or working abroad — anyone who needs to adapt quickly to an English-speaking environment.

• Professionals — for meetings, presentations, or client calls.

• Exam candidates — sharpening speaking skills for IELTS, TOEFL, or PTE.

• Travellers — wanting smooth, stress-free exchanges on the road.

JAM is a paid app, but it costs less per month than two cups of coffee. Compare that to private tutoring — a single session with a native speaker might set you back hundreds of pounds. Jammy, your 24/7 AI coach, is there whenever you want, at a fraction of the cost.

A Gift for Newsletter Readers

For subscribers of this newsletter, I’ve set aside a special treat: a free one-month JAM membership(worth £4). Practise as many times as you like, wherever you are, with instant AI feedback.

It’s more than just a free code — it’s a 30-day speaking challenge. Before claiming, you’ll write down a pledge: to practise at least once a day, and to leave yourself a short note of encouragement. The app will generate a unique “learning contract” just for you.

In other words, I’ll cover the cost — you bring the consistency. Stick to it for 30 days, and your English confidence will leap forward.

Click to join the challenge. A month from now, you’ll thank your past self.

Link: https://Jamtalk.co/free

On the App Store: search “JAM English Speaking” or download directly here: https://apps.apple.com/nz/app/jam/id6749299926

Fluency doesn’t come from perfection — it comes from speaking. Your first 60 seconds start today.

Hello, I’m Bear—a product designer, UX mentor and an award‑winning bilingual podcast host, currently living in Auckland, New Zealand. I enjoy sharing insights from my work, life, and study, helping all of us grow together.

Bear Academy Newsletter is my weekly email packed with thoughts on technology, design, and productivity—featuring book breakdowns, learning tips, and career reflections. Subscribe for free at bear.academy

💬 Contact

• Youtube.com/@Bearliu - A video is worth a thousand words

• bear@beartalking.com - The old fashion email way

• LinkedIn.com/in/bearliu - My professional life

• Beartalking.com - all my posts, in English and Chinese

• https://twitter.com/bearbig - Majorly I post in Chinese

Last week, I launched my new product: JAM, an AI speaking coach.

It has been live for just 10 days. With only two of us building, every step feels worth celebrating.

✅ 500+ downloads

✅ $80+ in monthly revenue

✅ 3 versions shipped (bugs fixed + smoother experience)

✅ Chinese + English UI supported

We also launched a campaign for Chinese-speaking users: Free monthly code → 30-day English challenge. 100+ downloads in the first 12 hours.

On the backend, we built a notification system, internal tools, and push notifications in just a couple of days. At my previous role, that same setup took 3 teams months.

The biggest win? I’m closer than ever to business and product decisions. Design thinking helps me connect everything I’ve learned and put it straight into JAM.

Next step: marketing. I’ll be spending half my time there, and I’m excited to see where it takes us.

Check on App Store:

https://apps.apple.com/us/app/jam/id6749299926

How I Built and Launched an AI-Powered App in 20 Days (as a Designer)

From idea to App Store in just 20 days — see exactly how I built an AI-powered iOS app as a designer, without being a full-time coder.

Transform your ideas into real products faster than ever - I'll show you exactly how I went from concept to App Store launch in just 20 days using AI tools like Cursor, with zero coding experience as a designer.

I'll walk you through my process, from using ChatGPT to validate the concept and building a functional prototype with Cursor, to collaborating with a developer and submitting the final product. This video isn't about code; it's about leveraging AI tools to turn your creative ideas into reality, even if you don't have a technical background.

This is a real-world case study for designers and tech professionals who want to explore how modern AI tools can accelerate their workflow, validate product ideas, and build functional prototypes faster than ever.

Other Goodies of the week

11 lessons from a year of using AI in my daily work

In his UX Collective article, Jan Takacs shares what he learned from a year of heavy AI use — aptly titled “From Hype to Habit.” Several points stood out to me:

• In multilingual work, English as the input language still delivers the highest-quality output.

• Great input = great output — the better you feed the AI, the better the results.

• The best outcomes often come when there’s almost a 1:1 ratio between input and output, rather than expecting the AI to spin gold from a vague prompt.

• Increasingly, he prefers speaking to AI over typing, especially as model quality improves.

• To get the most from AI long-term, you need to stay sharp — read, learn, think deeply, explore — and resist offloading too much, or your mental “muscle” will weaken.

For me, this reinforces one key adjustment: even though Chinese is my native language, keeping English as my primary input to AI can immediately improve quality. It’s a simple yet impactful change I’ll adopt as a long-term habit, treating AI as a thought partner, not a substitute.

Another point that really resonated with me is the importance of resisting the temptation to hand over all your work to AI. This kind of dependency can cause your “mental muscles” to atrophy over time. The most powerful way to use AI isn’t to have it do everything for you, but to treat it as a partner — one that broadens your perspective and deepens your thinking. We have to stay sharp and keep learning, rather than getting too comfortable, because once our thinking skills deteriorate, rebuilding them becomes incredibly hard.

Original link: https://uxdesign.cc/11-lessons-from-a-year-of-using-ai-in-my-daily-work-f03c18c7f861

5 AI Tools That Save Me 100+ Hours of Editing!

I just watched a video from Think Media that shared 5 AI tools for supercharging your editing workflow. For creators who are constantly producing content, these tools are like having a powerful production assistant that drastically cuts down on repetitive tasks. They handle everything from visuals and audio to carving out the best moments from long videos, giving us more time to focus on the creative side of things.

Here's a quick rundown of the 5 tools:

• CapCut: Beyond standard editing features, its powerful AI background removal and video upscaling can clean up your footage with a single click, saving a ton of post-production work.

• Adobe Podcast Enhance: This tool is made specifically for audio optimization. It takes bad recordings and makes them sound crisp and clear, giving your podcasts and voice-over videos a professional feel.

• Opus: Perfect for short-form content. Just upload a video, and it automatically finds the most engaging clips, adds captions, titles, and descriptions, making the repurposing process incredibly simple.

• VideoLeap: It can automatically slice a long video into 2-minute or 5-10 minute shorts, allowing you to easily pick and export the best parts for different platforms.

• Descript: This is a text-based video editor that lets you quickly search for highlights in a transcript and generate clips that are ready to use.

My Take:

I find this "tool combo" approach perfect for a high-volume, time-crunched creator like myself. When I'm promoting a product like JAM, I often need to distribute content across different platforms in multiple formats. These AI tools not only save me a ton of effort but also speed up my production cycle. The best part is that they have a low barrier to entry, so as a creative, I can handle most of the editing myself without needing to be a pro.

These tools reinforce my belief that AI isn't here to replace us; it's here to empower us. It automates the repetitive and mechanical tasks, giving us more time to think and, most importantly, to create.

Original video:

Hello, I’m Bear—a product designer, UX mentor and an award‑winning bilingual podcast host, currently living in Auckland, New Zealand. I enjoy sharing insights from my work, life, and study, helping all of us grow together.

Bear Academy Newsletter is my weekly email packed with thoughts on technology, design, and productivity—featuring book breakdowns, learning tips, and career reflections. Subscribe for free at bear.academy

💬 Contact

• Youtube.com/@Bearliu - A video is worth a thousand words

• bear@beartalking.com - The old fashion email way

• LinkedIn.com/in/bearliu - My professional life

• Beartalking.com - all my posts, in English and Chinese

• https://twitter.com/bearbig - Majorly I post in Chinese