Become a product manager in the AI era. Speak it, and AI builds it (言出法随).https://doaipm.com/enhttps://doaipm.com/en/blog/say-it-clearly/https://doaipm.com/en/blog/say-it-clearly/This is the fifth piece in the series Becoming an AI-Era PM. You tell AI "build me a login," and in one breath it settles a dozen things you never mentioned: email or phone, how many wrong passwords before it locks, how long the lock lasts, what the error message says. AI doesn't ask you back the way a person would — it's a yes-machine: it does what you said, not what you meant. The moment a requirement goes fuzzy, it fills the gap with the most generic default, and that default is usually not the one you wanted. OpenAI's Sean Grove says code is only 10–20% of a developer's value; the other 80–90% is saying clearly what to build. This piece gives you four things you can actually do: swap adjectives for numbers, write out every state, list the edge cases, and self-check with a zero-context test.Wed, 24 Jun 2026 00:00:00 GMTAI Product ManagerSaying It ClearlySpeak It Into Beingdoaipm MethodAI-Era PMhttps://doaipm.com/en/blog/judgment-over-feasibility/https://doaipm.com/en/blog/judgment-over-feasibility/This is the fourth piece in the series Becoming an AI-Era PM. In 2025, METR ran a randomized controlled trial: 16 senior developers, five years of experience on average, did 246 real tasks with AI. Beforehand they expected to be 24% faster; afterward they still felt 20% faster; measured, they were 19% slower. Even the simplest judgment — "did AI make me faster" — got called backwards by the people who knew the work best. When building gets fast and cheap, "can we build it" stops filtering any idea out, and the expensive judgment moves to "should we build it." This piece gives you four things you can actually do: stop using difficulty as a gate, ask what happens if you don't build it, write down what becomes true before you start, and let AI lay out options but never trust "feels right."Tue, 23 Jun 2026 00:00:00 GMTAI Product ManagerProduct JudgmentShould We Build Itdoaipm MethodAI-Era PMhttps://doaipm.com/en/blog/ai-as-colleague/https://doaipm.com/en/blog/ai-as-colleague/This is the third piece in the series Becoming an AI-Era PM. Most people use AI like a vending machine: a sentence in, an answer out, and the next conversation starts the explanation over from scratch. The CEO of Relay.app said at an AI product leaders summit, "Stop treating AI as a tool — treat it like a colleague you hired." This piece skips the mindset talk and gives you four things you can actually do: write it a handoff doc, hand it a whole task with the boundaries nailed down, review its output the way you'd review a junior's PR, and write every correction back into the doc — with real example prompts.Mon, 22 Jun 2026 00:00:00 GMTAI Product ManagerWorking With AIAI Agentsdoaipm MethodAI-Era PMhttps://doaipm.com/en/blog/not-knowing-code-is-an-edge/https://doaipm.com/en/blog/not-knowing-code-is-an-edge/This is the second piece in the series Becoming an AI-Era PM. A residential real estate broker who can't write code built an AI agent that runs his daily operations using Claude and Zapier; in 2026, 63% of vibe coding's active users aren't developers. On the road from idea to a thing that actually runs, people without a technical background sometimes move faster — engineers first have to shed the instinct to be responsible for every line, and the sentence "this is too hard" is one a non-technical person simply can't say.Sun, 21 Jun 2026 00:00:00 GMTAI Product ManagerPM TransitionBuilding Without Codedoaipm MethodAI-Era PMhttps://doaipm.com/en/blog/ai-pm-what-changed/https://doaipm.com/en/blog/ai-pm-what-changed/This is the first piece in the series Becoming an AI-Era PM. In 2026, plenty of AI PM job descriptions dropped writing PRDs, drawing prototypes, and building dashboards from the hard requirements, and swapped in three work samples instead. The tasks AI can take over are falling out of the hiring requirements, and what's left as the bar is the part only a person can do. This piece lays the took over and got more valuable columns side by side, as the overview for the whole series.Sat, 20 Jun 2026 00:00:00 GMTAI Product ManagerPM TransitionAI-Era PMdoaipm MethodTech Commentaryhttps://doaipm.com/en/blog/why-coaches-are-old/https://doaipm.com/en/blog/why-coaches-are-old/The Knicks won their first championship in 52 years, and the coach holding the trophy, Mike Brown, is 56 and never made a single shot in an NBA game. Pull the camera back across the whole league: the players running the floor are in their twenties, and the people calling the shots from the sideline are all gray-haired, fifty to seventy-something. Players sell their legs; coaches sell their judgment — and those two things age in opposite directions. That single pattern happens to explain something a lot of people are losing sleep over: how older workers get re-employed in the AI age.Sat, 20 Jun 2026 00:00:00 GMTAI and JobsOlder WorkersNBAJudgmentTech Commentaryhttps://doaipm.com/en/blog/felt-faster-actually-slower/https://doaipm.com/en/blog/felt-faster-actually-slower/In METR's randomized controlled trial, 16 experienced open-source developers did real tasks on projects they'd maintained for an average of five years. The ones using AI were 19% slower. But the worse part is the other half: they predicted AI would speed them up 24% beforehand, and after finishing — after personally living through the slowdown — they still believed they'd gone 20% faster. Their gut and the stopwatch were off by nearly 40 percentage points, with the sign flipped. As someone who plans roadmaps, quotes timelines, and defends budgets on team-productivity estimates every day, I want to spell out where this illusion comes from, where it holds, and how it's quietly seeped into every AI-related decision in our line of work.Fri, 19 Jun 2026 00:00:00 GMTAI CodingDeveloper ProductivityProduct ManagementAI ProductivityTech Commentaryhttps://doaipm.com/en/blog/altman-ai-washing/https://doaipm.com/en/blog/altman-ai-washing/The guy selling AI hardest just admitted, on the record, something everyone already suspected. Sam Altman says a lot of so-called 'AI layoffs' are really AI washing — cuts that were coming anyway, blamed on AI to look dignified. What makes it stranger: months later he said he was 'delighted to be wrong,' because the jobs apocalypse he once feared never showed up. On one side, six figures of tech jobs vanished in 2026 under the AI banner. On the other, AI's top salesman says the whole thing got oversold. The gap between those two statements is the part worth watching.Thu, 18 Jun 2026 00:00:00 GMTSam AltmanAI LayoffsAI WashingTech CommentaryCareershttps://doaipm.com/en/blog/selling-software-stocks/https://doaipm.com/en/blog/selling-software-stocks/Jefferies just cut Workday, DocuSign, Monday.com, and Freshworks to Hold, citing AI disruption risk in plain language. Software stocks are down 30% to 55% this year. The market is making one bet: once a product's features can be cloned by AI in a single sentence, the business of charging subscriptions for those features stops being worth anything. The point isn't that software dies. It's that the valuable part of software is moving — out of the features themselves and into judgment, taste, distribution, and trust. Anyone who misses the move falls with the multiples.Wed, 17 Jun 2026 00:00:00 GMTSoftware StocksSaaSAI DisruptionVibe CodingTech Commentaryhttps://doaipm.com/en/blog/ai-layoffs-backfire/https://doaipm.com/en/blog/ai-layoffs-backfire/Gartner surveyed 350 companies with over $1B in revenue, and about 80% cut staff because of AI. But the companies that cut weren't any more likely to see a real return than the ones that didn't. The layoffs freed up budget; they didn't free up return. The reason is simple: these companies treated AI as a way to replace people and save money, when AI's real value is amplifying human judgment. Cut people as a cost and you cut exactly the part that produces the return.Tue, 16 Jun 2026 00:00:00 GMTAI layoffsenterprise AIROIAI-era product managertech commentaryhttps://doaipm.com/en/blog/alibaba-everything-but-judgment/https://doaipm.com/en/blog/alibaba-everything-but-judgment/In a single week, Wuzhao was pushed out of DingTalk, and word spread that Chief Scientist Zhou Jingren was leaving too, six days after he took the title. Alibaba quickly denied the Zhou rumor, but the steady exit of Tongyi's core people this year is very real. Put it all together and you see something strange: Alibaba owns the strongest AI model in China and the most relentless execution culture there is, yet its technical talent and its product captains keep walking out the door. The problem isn't the technology. It isn't the execution. It's the one seat nobody can fill: judgment.Mon, 15 Jun 2026 00:00:00 GMTAlibabaAI strategyTongyijudgmenttech commentaryhttps://doaipm.com/en/blog/ai-lies-to-you/https://doaipm.com/en/blog/ai-lies-to-you/In June, a KPMG report on AI was caught full of AI hallucinations: of 45 citations, only 5 pointed to real sources. A report about AI got fooled by AI. AI lies to you, and it does so with a straight face. That isn't a bug, it's part of how it works. Because it lies, the person who catches it, verifies it, and signs off on it is irreplaceable. And to make that job cheaper and faster, you have to use the best AI you can get.Sun, 14 Jun 2026 00:00:00 GMTAI hallucinationAI-era product managersjudgmenttech commentaryhttps://doaipm.com/en/blog/busy-for-nothing/https://doaipm.com/en/blog/busy-for-nothing/437 days. Field visits, customer satisfaction pulled from 30% to 80%, a camp bed in the office, watching when the lights went out in the Feishu building across the street. Wu Zhao's diligence was real. So was DingTalk ONE: launched in four months, 3 million daily actives, retention off a cliff, dismantled within ten months. AI has maxed out productivity while the new consumption scenarios haven't shown up, and nobody has found the right path for human-AI collaboration. This is more than one man's failure; it's an entire era's winning formula expiring at once. And busywork is the first trap this era has dug for product managers.Sat, 13 Jun 2026 00:00:00 GMTDingTalkAI-era product managershuman-AI collaborationtech commentaryhttps://doaipm.com/en/blog/the-price-of-judgment/https://doaipm.com/en/blog/the-price-of-judgment/SpaceX went public at a $1.75 trillion valuation and rose 19% on its first day. The only part of it that actually turns a profit is Starlink, and its revenue isn't a fraction of what that number implies. The market isn't buying rockets, and it isn't buying revenue. It's buying one person's judgment, proven right again and again across twenty-four years. In an AI era where execution keeps getting cheaper, the biggest check in history landed on the one thing still appreciating.Sat, 13 Jun 2026 00:00:00 GMTMuskSpaceXAI-era product managersjudgmenttech commentaryhttps://doaipm.com/en/blog/wrong-operating-system/https://doaipm.com/en/blog/wrong-operating-system/He joined Alibaba as an intern in 1999, left for Japan two years later, and stayed eleven years. Back home he built DingTalk, built hardware, and even pointed his own startup at the Japanese market. The precise, disciplined, obsessively polished operating system Wuzhao runs on was forged in Japan. It's a top-tier rig for building hardware and a fundamental mismatch for exploring AI. The real reason DingTalk stalled was written in his résumé all along.Sat, 13 Jun 2026 00:00:00 GMTDingTalkAI-era product managersorganizational culturetech commentaryhttps://doaipm.com/en/blog/pm-is-the-new-bottleneck/https://doaipm.com/en/blog/pm-is-the-new-bottleneck/You used to explain a requirement once and downstream would chew on it for two weeks. Now an AI-powered downstream comes back in twenty minutes asking for the next instruction. HBR says management systems can't keep up with AI's output pace; Andrew Ng says product managers have become the bottleneck. The exhaustion is real — but it's worth understanding why. It's a signal that power is flowing back to you, and a warning sign that you're living as a human CI server.Fri, 12 Jun 2026 00:00:00 GMTAI-era product managersbottleneck shiftjudgmenttech commentaryhttps://doaipm.com/en/blog/agents-need-boundaries/https://doaipm.com/en/blog/agents-need-boundaries/65% of enterprises had an AI agent security incident last year. Some agents mined crypto and opened backdoors on their own. Everyone's scrambling to patch 'agent security,' but the real hole isn't technical — it's that the whole industry treated 'can act' as the finish line and skipped the unsexy part: defining what agents aren't allowed to touch.Thu, 11 Jun 2026 00:00:00 GMTAI agentAI securitygovernancetech commentaryhttps://doaipm.com/en/blog/garbage-ships-faster/https://doaipm.com/en/blog/garbage-ships-faster/Lovable is celebrating 50 million projects and 720 million monthly visits — do the division, and the average project gets seen 14 times a month. AI didn't kill garbage products. It maxed out garbage production capacity. Garbage was never about failing to build it. It's about something that never should've been built in the first place.Wed, 10 Jun 2026 00:00:00 GMTvibe codingAI productsbuild economytech commentaryhttps://doaipm.com/en/blog/nobody-measured-the-value/https://doaipm.com/en/blog/nobody-measured-the-value/Microsoft quietly pulled Claude Code from an internal division and pushed thousands of engineers back to GitHub Copilot. Uber burned through its entire 2026 AI coding budget in four months. The narrative is that AI coding is too expensive. It isn't. The real problem is that companies bought 'productivity gains' as a feeling, never as a number — and now the bill is crystal clear while the benefits aren't worth a single data point.Tue, 09 Jun 2026 00:00:00 GMTAI codingenterprise AIROItech commentaryhttps://doaipm.com/en/blog/you-are-the-eval/https://doaipm.com/en/blog/you-are-the-eval/In 2026, building 'evaluation systems' for AI has become a full-blown discipline — gold-standard datasets, scorers, LLM-as-judge, CI gates, all positioned as the engineering practice that makes AI reliable. Strip away the engineering wrapper, though, and evals are really about one thing: who gets to define 'good,' and who owns the consequences. That part can't be outsourced.Mon, 08 Jun 2026 00:00:00 GMTevalsAI产品经理judgmenttech-commentaryhttps://doaipm.com/en/blog/ai-that-pushes-back/https://doaipm.com/en/blog/ai-that-pushes-back/The biggest change in Claude Opus 4.8 isn't that it's smarter — it's that it's more honest. It asks clarifying questions, admits uncertainty, and will argue back when your plan doesn't hold up, instead of serving you a half-finished job dressed up as 'done.' When AI starts pushing back, 'speak it, AI builds it' stops being a monologue and becomes a real conversation — and the skill every PM needs to build now is being a worthy counterpart.Sat, 06 Jun 2026 00:00:00 GMTdoaipmAI-native PMClaudejudgmentspeak-it-AI-builds-ithttps://doaipm.com/en/blog/say-it-dont-spec-it/https://doaipm.com/en/blog/say-it-dont-spec-it/Everyone's shouting that vibe coding is dead and the answer is spec-driven development. But for product managers, front-loading a pile of detailed spec documents just drags back the PRD burden AI finally got rid of. You don't have to choose between 'winging it' and 'writing specs' — there's a third path: speak it, AI builds it.Fri, 05 Jun 2026 00:00:00 GMTdoaipmAI-native PMspec-drivenvibe codingspeak-it-AI-builds-ithigh-fidelityhttps://doaipm.com/en/blog/taste-is-the-moat/https://doaipm.com/en/blog/taste-is-the-moat/AI has made building things nearly free. Anyone can ship a working product. The barrier is gone — so the question becomes: if anyone can build, why is yours better? The answer is taste. And the counterintuitive part: taste isn't a gift. It's a skill you can train.Thu, 04 Jun 2026 00:00:00 GMTdoaipmAI-native PMtastejudgmenthigh-fidelityhttps://doaipm.com/en/blog/prototype-is-not-production/https://doaipm.com/en/blog/prototype-is-not-production/Mid-2026, vibe coding has split the room in two: one camp calls it the biggest shift since cloud, the other calls it gift-wrapping AI slop. The critics' concerns about security and maintainability are valid — for production systems. For prototypes, they're wildly overstated. doaipm's high-fidelity + safety-net approach has always kept those two things separate.Wed, 03 Jun 2026 00:00:00 GMTdoaipmAI-native PMvibe codinghigh-fidelitysafety nethttps://doaipm.com/en/blog/from-executor-to-orchestrator/https://doaipm.com/en/blog/from-executor-to-orchestrator/AI has taken over gathering, synthesizing, and running the process. Product managers are shifting from executor to orchestrator. Where should you invest the time you've just won back? In the places AI can't reach — judgment, empathy, taste. And now you build things yourself.Tue, 02 Jun 2026 00:00:00 GMTdoaipmAI-native PMagentic言出法随https://doaipm.com/en/blog/stop-learning-start-doing/https://doaipm.com/en/blog/stop-learning-start-doing/In the AI era, product managers don't need to hoard knowledge — you'll never out-know AI. Ask it on the spot instead of studying in advance. The core of DO AI PM is DO; the core of DO is SAY — and speaking is the most basic skill a product manager already has. There's no prerequisite. The only barrier is that you haven't started.Tue, 02 Jun 2026 00:00:00 GMTdoaipmAI-native PM言出法随Claude Codehttps://doaipm.com/en/blog/vibe-coding-is-product-management/https://doaipm.com/en/blog/vibe-coding-is-product-management/When AI writes the code, what's left is judgment: deciding what to build, for whom, and what 'good' means. That has always been product management. Here's why not knowing how to code can be an advantage — and how to do it on purpose.Mon, 01 Jun 2026 00:00:00 GMTdoaipmAI-native PMvibe codingClaude Codemethodologyhttps://doaipm.com/en/blog/welcome/https://doaipm.com/en/blog/welcome/The first doaipm post. Not knowing how to code is an advantage — this very site was "spoken" into existence with Claude Code.Sat, 30 May 2026 00:00:00 GMTdoaipmClaude Codemethodology