Every two weeks, we dive into the vast ocean of product content online, both free and paid. We sift through it all to bring you the crème de la crème. Our round-up includes carefully curated links and concise excerpts from top content.

This week’s highlights feature:

• Top 3 Long-Form Articles/Podcasts

• Top 3 Tweets

• Top 3 LinkedIn Posts or Short Videos

Our expert product team has selected these resources to help you save thousands of dollars on unnecessary subscriptions, avoid wasting time reading instead of taking action, and save years following the wrong advice. Our mission is to introduce you to brilliant product thinkers, whether they’re renowned experts or emerging voices.

Top Long-Form Content

1. A Spy's Guide to Running AI

   1. What we liked: A genuinely original lens on AI governance that has immediate implications for product teams building with AI. The spy tradecraft framing cuts through the hype better than any "responsible AI" think piece we've seen this year.

   2. Choice quote: “The most dangerous source isn't someone who lies to you. It's someone who tells you what you want to hear — and does it convincingly."

2. AI Will Fail

   1. What we liked: Just a fun list of famous people saying infamously incorrect things that is a warm reminder that we don’t all have to have it all figured out to be great.

   2. Choice quote: "The people who said it would fail were running the thing it was about to replace."

3. How to Use AI to Become a Genius

   1. What we liked: Skim, don’t read, and ignore the marketing-first content in favor of the main take aways around what differentiates human-first creation in an AI-saturated world.

   2. Choice quote: "The most human company wins."

Top Tweets

1. The 5-Minute AI Exercise I'd Run With Every Team

   1. What we liked: "What is one AI correction you made more than once this week?" is a great mental model. The answers reveal where institutional judgment can be turned into reusable skills, highlighting the difference between prompts that generate outputs and skills that preserve ways of working.

   2. Choice quote: "Those repeated corrections look tactical from the outside. Inside the company, they carry judgment."

2. AI Work Needs a Pull Request

   1. What we liked: Love the idea of treating review of AI work like an engineering pull request. Skim only.

   2. Choice quote: "A pull request turns a proposed change into something visible. Claims need a work surface."

3. Everyone Is Building a Second Brain. The People Winning Are Building a Second Self.

   1. What we liked: Immediately buildable blueprint for moving beyond a "second brain" to a "second self." The combination of a CLAUDE.md identity layer, an Obsidian vault organized around reactions instead of captures, and automated daily synthesis offers a practical architecture for turning AI into a true reasoning partner rather than just a retrieval tool.

   2. Choice quote: "A second brain makes you feel organised. A second self makes you feel like you are working with someone who knows how your mind works."

Top LinkedIn Posts & Short Videos

1. The Rise of the Centaur Creator: Why AI Is Replacing the Maker, but Empowering the Director

   1. What we liked: The Centaur framing is memorable and useful. It reframes a familiar human-vs-AI debate into a more productive question: are you training yourself to be a better director, or are you hoping your making skills will survive?

   2. Choice quote: “AI handles the execution. You handle the taste.”

2. The Infinite Permutation Problem: AI, Creativity, and the Crisis of Human Originality

   1. What we liked: This one will unsettle people who read it carefully, which is exactly what a good piece should do. It’s the most philosophically serious article in the batch.

   2. Choice quote: “Humanity may soon discover that originality was always more recombinational than civilisation previously wanted to admit.

3. The Synthetic Mirror: Why Our Fear of AI Is a Mirror of Our Own Fragility

   1. What we liked: A sharper diagnosis of AI resistance than most pieces in this space, which tend to either dismiss skeptics or validate them. The framing around the "comfort of the rate of change" as organizational stagnation is practically useful.

   2. Choice quote: "We aren't afraid of the code. We are afraid that the world is moving faster than our current definitions of success can keep up with."

This article is brought to you by Productboard

Trusted by the world’s best product teams, Productboard turns customer needs into high-impact strategy in one end-to-end platform. With Productboard Spark, you can go from raw idea to polished product brief in seconds using AI that already understands your business.

See how Productboard Spark can help your product teams ship faster →

In case you missed them — Adam’s recent LinkedIn Content

1. A common question I hear from local governments is, "Should we be training our own LLM?"

2. I've built tech for Fortune 500s, federal agencies, and local city halls. The pitch is identical. The outcome isn't.

3. America has some very unusual cities. Have you heard of California Forever?
   
   
   
   
   

Every two weeks, we dive into the vast ocean of product content online, both free and paid. We sift through it all to bring you the crème de la crème. Our round-up includes carefully curated links and concise excerpts from top content.

This week’s highlights feature:

• Top 3 Long-Form Articles/Podcasts

• Top 3 Tweets

• Top 3 LinkedIn Posts or Short Videos

Our expert product team has selected these resources to help you save thousands of dollars on unnecessary subscriptions, avoid wasting time reading instead of taking action, and save years following the wrong advice. Our mission is to introduce you to brilliant product thinkers, whether they’re renowned experts or emerging voices.

Top Long-Form Content

1. How to Reimagine Your Work in the Age of AI

   1. What we liked: The clearest articulation we’ve seen of where value migrates once producing outputs stops being a constraint — from artifact production to “idea architecture.” Concrete, grounded in his own workflow, and genuinely useful for anyone who ships deliverables.

   2. Choice quote: “Adobe’s move is a distribution story. Figma’s move is an architecture story.”

2. Is AI Going to Destroy Our Lives or Not?

   1. What we liked: Does the synthesis work most readers won’t — pulls labor data, firm behavior, and wealth concentration into one coherent picture, then arms you with a usable rule of thumb for assessing any role. The metaphors land.

   2. Choice quote: “AI is sort of like freeze-dried camp food. It does a good enough job, is filling enough, but it isn’t something you want to eat everyday.”

3. The Hidden Cost of Letting AI Think for You

   1. What we liked: Tight, concrete, and aimed squarely at knowledge workers and builders. The technical-debt analogy makes an abstract worry immediately legible, and the closing prompt — am I using AI to think better, or to avoid thinking? — is the kind of thing a team can actually act on.

   2. Choice quote: “Cognitive debt is what happens when we outsource thinking too early.”

Top Tweets

1. How to Stop Babysitting Your AI Agents

   1. What we liked: The most operationally useful piece in the batch, grounded in real deployments rather than demos, with a “Definition of Done” you can paste into a workflow today and a sharp reframe of what “completion” actually means.

   2. Choice quote: “Receipts beat confidence every time.”

2. Every Company’s First AI Strategy Should Be a Skill Library

   1. What we liked: A genuinely strategic lens for leaders and founders, not another tooling tutorial, with a clean throughline (skills make judgment reusable) and a practical starting move: map the repeated work where experienced people quietly outperform.

   2. Choice quote: “A company’s AI advantage will come from the work it teaches the model to do well, rather than from the model it chooses.”

3. The Reason Why 99% of AI Workflows Die (And the 9 Golden Rules That Keep Them Alive)

   1. What we liked: Reads like hard-won production experience rather than influencer theater, and the rules are specific enough to act on, with a healthy bias toward boring reliability over impressive demos.

   2. Choice quote: “A workflow that works 95% of the time beats a ‘genius system’ that works 40%.”

Top LinkedIn Posts & Short Videos

1. Artificial Intelligence versus Actual Intelligence: Why Human Intelligence Still Matters in the Age of AI

   1. What we liked: The “AI raises the floor, not the ceiling” reading of the Stanford numbers is a genuinely useful insight for anyone shipping AI features: novices gained 34%, experts close to nothing. Directly applicable to how you think about who your AI product actually helps.

   2. Choice quote: “Artificial Intelligence may supply the horsepower. Actual Intelligence still holds the wheel.”

2. Why Empathy May Become the Most Valuable Technology in Artificial Intelligence

   1. What we liked: A clear, founder-facing thesis from one of the more prominent voices in the venture/AI space, with concrete grounding in healthcare and education (the same medical fact delivered coldly vs. empathetically is a different product). The closing prompt — evaluate whether the AI you build strengthens well-being — is an actual design heuristic, not a platitude.

   2. Choice quote: “Trust is built emotionally before logically.”

3. Artificial Intelligence Is About to Decide Who Customers Trust

   1. What we liked: Recasts the challenge of getting your product noticed in terms of what foundational models will find when people look for “best X for Y.” Runs hot on self-promotion toward the end, but the first 2/3 is worth it.

   2. Choice quote: “Google mostly helped people research, while Artificial Intelligence is starting to help people decide.”

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This article is brought to you by Productboard

Trusted by the world’s best product teams, Productboard turns customer needs into high-impact strategy in one end-to-end platform. With Productboard Spark, you can go from raw idea to polished product brief in seconds using AI that already understands your business.

See how Productboard Spark can help your product teams ship faster →

In case you missed them — Adam’s recent LinkedIn Content

1. For product evals, an LLM-as-judge is powerful.

2. In 1891, William Wrigley Jr. was selling soap in Chicago and throwing in free baking powder as a bonus to attract customers.

3. AI can process a permit, but it shouldn’t decide the future of a city…
   
   
   
   
   
   
   

Every two weeks, we dive into the vast ocean of product content online, both free and paid. We sift through it all to bring you the crème de la crème. Our round-up includes carefully curated links and concise excerpts from top content.

This week’s highlights feature:

• Top 3 Long-Form Articles/Podcasts

• Top 3 Tweets

• Top 3 LinkedIn Posts or Short Videos

Our expert product team has selected these resources to help you save thousands of dollars on unnecessary subscriptions, avoid wasting time reading instead of taking action, and save years following the wrong advice. Our mission is to introduce you to brilliant product thinkers, whether they’re renowned experts or emerging voices.

Top Long-Form Content

1. The PM of the Future Is More Hedge Fund Manager Than Builder

   1. What we liked: The hedge-fund manager analogy reframes the job in a way that’s actually motivating rather than threatening, and the piece comes loaded with usable frames — “flare wide, focus hard, ship less,” the 85-90% agent reliability problem, the Vitamix blender test for shipping with AI, and a back-and-forth PRD workflow that beats one-shot prompting. The owner-versus-worker mentality closer is the kind of line PMs will quote in Slack.

   2. Choice quote: “If you’re a worker, every new AI model release is a threat. It’s getting closer to you, doing more of what you do, and that’s terrifying. If you’re an owner, every new release is a capability upgrade.”

2. The Tool Selection Problem: Why AI Agents Call The Wrong Tool And How To Fix It

   1. What we liked: Four named failure modes (ambiguous overlap, missing negative constraints, misleading parameter names, indiscriminate calling) each paired with a specific description-level fix, grounded in a reproducible minimal-agent experiment. PMs and founders shipping agents should make this required reading for the team this week.

   2. Choice quote: “Wrong tool calls are a description problem, not a reasoning problem. The model is following the signals you gave it, and those signals are ambiguous.”

3. Welcome to the Age of Artificial Stupidity

   1. What we liked: It’s worth reading an occasional pessimistic view of AI.

   2. Choice quote: “We had better be quite sure that the purpose put into the machine is the purpose which we really desire and not merely a colorful imitation of it.”

Top Tweets

1. Don’t Outsource the Learning.

   1. What we liked: A serious look at what happens to engineering teams when AI handles the closing-of-tasks but nobody asks whether anyone is getting sharper in the process. The piece pulls together converging research — a 2026 Anthropic randomized trial where AI users scored 50% on comprehension vs. 67% for the manual group.

   2. Choice quote: “I’d rather ship 80% of what I could have and learn 100% of what I needed to, than the reverse. Over years, those two strategies produce very different engineers.”

2. The Last Three Things AI Can’t Copy.

   1. What we liked: A thoughtful, well-written piece on what’s actually scarce in an AI-native world. Less prescriptive than the others, but the framing helps PMs and founders think about where they should be spending their attention.

   2. Choice quote: “AI doesn’t change that mechanism. AI changes the volume. The choosing muscle that used to be a small part of the job is becoming most of the job.”

3. The First Step in Building My AI Native Team: Shared Brain First, Boundaries Second.

   1. What we liked: Easily the best framework-plus-implementation piece of the batch. The “boundaries matter more than connections” point is something most teams learn the hard way after their shared brain turns into a trash bin.

   2. Choice quote: “Lose a capability, the team gets dumber. Lose oxygen, the team stops breathing. I don’t want the memory system to be the single point of death for the whole team.”

Top LinkedIn Posts & Short Videos

1. More (Artificial) Intelligence Does Not Mean More Understanding.

   1. What we liked: “Cognitive debt” is a genuinely new lens — and one that maps cleanly onto how PMs should think about AI-assisted product decisions. Most “AI risk” posts cover the same five technical failure modes; this one names a different failure that’s already happening inside teams shipping AI tools.

   2. Choice quote: “An organization flooded with generated insights may actually become less strategically aware if nobody meaningfully interrogates the assumptions underlying the outputs.”

2. Physical AI: When Artificial Intelligence Meets the Real World.

   1. What we liked: A clean explain on the Physical AI frontier—robotics, autonomics systems, factory floors. The brain/body framing is the cleanest articulation we’ve seen of why the two stacks are converging.

   2. Choice quote: “The workflows and knowledge bases being built today may soon be the intelligence layer powering physical systems tomorrow.”

3. Is Artificial General Intelligence Really Five Years Away or Is That Just the Hype Talking?

   1. What we liked: Useful counterweight for founders fielding investor questions about AGI timelines, or PMs being asked to plan against them. The “deadline without a roadmap is not a forecast — it’s a story with good marketing” line is the kind of thing worth keeping in your back pocket.

   2. Choice quote: “The leaders who win will be the ones building clearly with what AI can actually do today, not waiting on a countdown that most researchers do not believe.”

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This article is brought to you by Productboard

Trusted by the world’s best product teams, Productboard turns customer needs into high-impact strategy in one end-to-end platform. With Productboard Spark, you can go from raw idea to polished product brief in seconds using AI that already understands your business.

See how Productboard Spark can help your product teams ship faster →

In case you missed them — Adam’s recent LinkedIn Content

1. Everyone across the public and private sector is suddenly becoming very interested in two pieces of contract language because of AI.

2. On long Australian highways, road authorities install trivia signs in fatigue zones.

3. 43% of government employees are now using AI at least a few times a year (source: Gallup).

4. The bad version of an AI product strategy conversation goes like this.

5. Most PMs using AI for customer research are doing the wrong things faster.

6. We were in a meeting recently, going back and forth on a question that had been sitting with the team for a while.
   
   
   
   
   
   
   

Every two weeks, we dive into the vast ocean of product content online, both free and paid. We sift through it all to bring you the crème de la crème. Our round-up includes carefully curated links and concise excerpts from top content.

This week’s highlights feature:

• Top 3 Long-Form Articles/Podcasts

• Top 3 Tweets

• Top 3 LinkedIn Posts or Short Videos

Our expert product team has selected these resources to help you save thousands of dollars on unnecessary subscriptions, avoid wasting time reading instead of taking action, and save years following the wrong advice. Our mission is to introduce you to brilliant product thinkers, whether they’re renowned experts or emerging voices.

In case you missed them, here are the recent posts from Emergent:

1. Slack has one search. Notion has two. Here’s why.

Top Long-Form Content

1. After “AI-First” Comes “AI-Only”

   1. What we liked: A genuinely contrarian frame from someone with the operational receipts to back it up (98% of code AI-written, team shrinking while revenue triples). The “horseless carriage” critique of the word “AI” itself — and the pivot to “alien intelligence” — gives PMs and founders a sharper lens for redesigning workflows from scratch rather than retrofitting AI into human-shaped seats.

   2. Choice quote: “’AI-first’ identifies a human-shaped vacancy and asks if a model can fill it… ‘AI-only’ asks why the chair exists at all.”

2. Product Thinking Isn’t Learned. It’s Developed.

   1. What we liked: Simple and to the point. See title.

   2. Choice quote: “You don’t need to become an engineer… You just need to ship small things, fast, and pay close attention to what happens. The tools have removed the building barrier. What remains is the willingness to put your bet in front of reality and let reality teach you.”

3. AI Won’t Make Your Company More Productive

   1. What we liked: A highly skeptical but worthy read about why the enterprise isn’t reaping the AI rewards to the extent it expects.

   2. Choice quote: “When an engineer saves 90 minutes using Claude, those 90 minutes don’t turn into 90 more minutes of shipped code. They evaporate. Into Slack. Into a longer lunch. Into “thinking time.” Into one more meeting that didn’t need to exist.”

Top Tweets

1. Most PMs are still using Claude like ChatGPT.

   1. What we liked: A concrete, file-by-file framework for moving past prompt-pasting into AI-native PM operations. The five-file starter kit is exactly the kind of thing a PM can implement Monday morning, and the diagnosis of why generic Claude outputs fool people (”generic strategy with confident formatting”) will land with anyone who’s been quietly disappointed by their own results.

   2. Choice quote: “The output is not bad because Claude is dumb. The output is bad because the PM gave it a pretend version of the job.”

2. Every team shipping an AI agent lives with the same anxiety: what happens when it does something the user didn’t ask for.

   1. What we liked: A war story for how to potentially deal with agent “rogueness.”

   2. Choice quote: “Nine out of ten problems, people were trying to fix through prompting. We’ve kind of switched modes into more architectural agent changes.”

3. Performance is intelligence times context.

   1. What we liked: A clean formula (Performance = Intelligence × Context) that reframes the enterprise AI moat conversation. The SAT-score analogy is a sharp way to puncture the assumption that benchmark wins translate to deployed value, and it gives PMs and founders a vocabulary for the work that actually matters.

   2. Choice quote: “We’ve rebuilt our junkyard engine into a racecar turbine but the car is still stuck in the driveway.”

Top LinkedIn Posts & Short Videos

1. The New Constraint: Why AI Made Product Management Harder, Not Easier

   1. What we liked: Cites Andrew Ng’s PM-to-engineer ratio shift (from 1:6 toward 1:0.5) and introduces the “blast radius of bad strategy” concept — when building is cheap, wrong-direction mistakes compound exponentially.

   2. Choice quote: “AI didn’t replace the product manager, it removed our excuses. We can no longer blame slow engineering cycles for a lack of product-market fit.”

2. I Am AI — Aged Intelligence

   1. What we liked: PM-relevant lesson: judgment under ambiguity is what AI exposes, not what it replaces.

   2. Choice quote: “AI gave me the average of the category. Experience brought the point of view.”

3. Navigating AI in Product Management: Why You Aren’t Becoming Outdated

   1. What we liked: If you’re feeling overwhelmed by the rapid rise of AI and worrying about your skills becoming obsolete, you are not alone — but the fundamentals of product management have not changed.

   2. Choice quote: “While the ‘why’ and ‘what’ of Product Management remain exactly the same, the ‘how’ is rapidly evolving.”

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This article is brought to you by Productboard

Trusted by the world’s best product teams, Productboard turns customer needs into high-impact strategy in one end-to-end platform. With Productboard Spark, you can go from raw idea to polished product brief in seconds using AI that already understands your business.

See how Productboard Spark can help your product teams ship faster →

In case you missed them — Adam’s recent LinkedIn Content

1. What a wrong answer looks like in most markets: a slightly irrelevant search result or a less exciting movie recommendation.

2. I’ve had a lot of conversations with crypto people, and most of them lose me within two minutes.

3. “Selling to early adopters is like proposing marriage, and you wouldn't propose marriage with a slide deck”.

4. 42% of startups fail because there’s no market need for their product.
   
   

Every two weeks, we dive into the vast ocean of product content online, both free and paid. We sift through it all to bring you the crème de la crème. Our round-up includes carefully curated links and concise excerpts from top content.

This week’s highlights feature:

• Top 3 Long-Form Articles/Podcasts

• Top 3 Tweets

• Top 3 LinkedIn Posts or Short Videos

Our expert product team has selected these resources to help you save thousands of dollars on unnecessary subscriptions, avoid wasting time reading instead of taking action, and save years following the wrong advice. Our mission is to introduce you to brilliant product thinkers, whether they’re renowned experts or emerging voices.

In case you missed them, here are the recent posts from Emergent:

1. AI Made Coding Faster. So Why Is Everything Breaking? (Video)

Top Long-Form Content

1. Will AI Create More Product Managers?

   1. What we liked: A genuinely contrarian economic argument with a usable three-tier taxonomy. Rather than the usual “AI changes everything” handwaving, it names which specific PM functions cheapen, which don’t, and what that means for where the value pools.

   2. Choice quote: “Two of three PM functions got dramatically cheaper. One stayed the same.”

2. Where Your AI Time Actually Goes

   1. What we liked: A clean diagnostic for the “I used AI all day and made nothing” feeling, with an allocation target you can measure yourself against. Reframes tool-switching and endless prompt tuning as modern forms of work avoidance.

   2. Choice quote: “The fourth rewrite of your instruction file, undertaken because the third one didn’t feel quite right, is almost always avoidance. Ship something, and let the output tell you what needs fixing.”

3. The Best AI Users in Any Company Aren’t the Engineers. They’re the Product Managers. Here’s Why!

   1. What we liked: A sharp, contrarian reframe that turns the “PMs are at risk from AI” narrative on its head. The “if you work with 6 to 10 engineers, you already manage 6 to 10 context windows” line makes an abstract argument concrete enough to act on tomorrow.

   2. Choice quote: “Start treating your AI conversations the way you treat your engineering partnerships. Write a brief before you prompt. Review the output like you’d review a PR. Give specific feedback, not vague reactions. Run multiple sessions in parallel on different workstreams.”

Top Tweets

1. Shipping Faster Is Making Your Product Worse

   1. What we liked: A genuinely counterintuitive framing for AI-era PMs — that more features, faster, is quietly killing adoption — from one of the most recognized voices in product. The “speed compounds in one direction, understanding compounds in another” line is the kind of reframe that changes how a roadmap conversation goes. Bonus points for the “don’t call it AI” tactical insight.

   2. Choice quote: “A lot of SaaS products are about to struggle because they were built on an assumption that is breaking: Users won’t keep coming to your UI to ask questions. They expect answers to come to them.”

2. AI made you efficient but are you compounding

   1. What we liked: A blunt reframe of what “AI-pilled” should even mean, aimed directly at founders. The efficiency-vs-compounding distinction gives PMs and founders a sharper standard for judging whether their AI investments are actually working. Coming from a prominent early-stage investor, it doubles as a signal of what the best AI-native companies are actually doing.

   2. Choice quote: “This is why the best AI-native teams don’t just feel faster. They’re not operating on a tighter loop. They’re operating on a different curve. They are compounding.”

3. Put the bot where the work happens

   1. What we liked: The calculator-mode-vs-team-member-mode framing is the kind of distinction that’s obvious once you see it but reframes how teams should actually deploy AI. For PMs and founders thinking about org-wide AI rollout, this is a clean argument for why the deployment surface matters more than model selection — with a concrete example of the “what did we decide on pricing again?” moment most teams lose hours to every week.

   2. Choice quote: “Execution breaks less often than coordination. People ship good work in parallel, then discover they were building different versions of the future.”

Top LinkedIn Posts & Short Videos

1. AI and the Death of Critical Thinking

   1. What we liked: Names a failure mode most PMs are blind to — your team getting faster while getting worse at the thing that matters. The frameworks are genuinely new and directly portable to how we evaluate AI-assisted work.

   2. Choice quote: “The most dangerous worker in the AI age is not the unskilled one; it is the smoothly misled one.”

2. Product Management in the AI era is no longer about prioritization.

   1. What we liked: Dense and PM-native. The “90% correct fails in Fintech, wins in Creative Writing” line alone is worth the read. Every PM can slot their current product into those three axes tomorrow morning.

   2. Choice quote: “Tech is now the commodity. Product judgment is the moat.”

3. We Call It Artificial Intelligence. We Should Call It Alien Intelligence. Here Is Why.

   1. What we liked: The rare philosophical piece grounded in actual deployment context (Data Fabric, Collections, Finance, HR platforms). The “alien intelligence” reframe is useful shorthand for why foundation models behave in ways our traditional product intuition misses.

   2. Choice quote: “The ‘designer’ of human emotion is not a mind. It is a process. A very slow, very powerful, very blind optimisation process running on biological hardware.”

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This article is brought to you by Productboard

Trusted by the world’s best product teams, Productboard turns customer needs into high-impact strategy in one end-to-end platform. With Productboard Spark, you can go from raw idea to polished product brief in seconds using AI that already understands your business.

See how Productboard Spark can help your product teams ship faster →

In case you missed them — Adam’s recent LinkedIn Content

1. I traveled to a Palantir alumni meetup in the middle of our busiest onboarding month so far.

2. Before 9/11, the Twin Towers were proof that the US government could build something the entire world looked up at.

3. We just rewrote about 70% of an AI course we launched 10 months ago.

4. Japan is in the top 5 for most earthquakes of any country on earth, but its death toll per earthquake is among the lowest in the world.

5. Singapore pays its entry-level ministers $1.1M/year. The US pays its Fed Chair, the person steering a $30 trillion economy, less than a mid-level PM at Google.

6. Every six months, I cancel all of our customer meetings for a week to make room for the one thing most teams never give themselves enough time to do: be creative.

7. In 2025, Zuckerberg told Joe Rogan, "all junior and mid-level developer jobs will be gone by the end of the year."

8. Two years ago, a design mock that looked rough would kill a deal.

9. Sweden built a road system in 1997 based on a premise most countries still reject: humans will always make mistakes behind the wheel.
   

Every two weeks, we dive into the vast ocean of product content online, both free and paid. We sift through it all to bring you the crème de la crème. Our round-up includes carefully curated links and concise excerpts from top content.

This week’s highlights feature:

• Top 4 Long-Form Articles/Podcasts

• Top 3 Tweets

• Top 3 LinkedIn Posts or Short Videos

Our expert product team has selected these resources to help you save thousands of dollars on unnecessary subscriptions, avoid wasting time reading instead of taking action, and save years following the wrong advice. Our mission is to introduce you to brilliant product thinkers, whether they’re renowned experts or emerging voices.

In case you missed them, here are the recent posts from Emergent:

1. (Video) Your AI Eval is Overcomplicated

2. Building Revolutionary Technology for Seniors

Top Long-Form Content

1. Avoiding The Eye of Sauron

   1. What we liked: A sharp, original framework for assessing startup risk in the age of foundation models. The “workflow vs. chassis” distinction and the counterintuitive insight that “boring” enterprise customers with low technical capability are now the most attractive ICP is the kind of contrarian thinking founders and PMs need right now.

   2. Choice quote: “The labs aren’t just building better models. They’re arming your customers.”

2. They Tried to Kill Product Managers. Now Everyone Needs to Be One.

   1. What we liked: A punchy, well-structured argument that flips the “PM is dead” narrative on its head with real examples from the author’s own AI building spree. The framework diagram showing where AI compresses the value chain (build) vs. where it doesn’t (discovery, GTM) is worth saving.

   2. Choice quote: “AI isn’t killing the need for product management. It’s making product management a skill everyone needs.”

3. AI Is Helping PMs Do the Wrong Things Faster

   1. What we liked: A sharp, experience-backed takedown of how most teams are misusing AI for discovery, with a clear “downstream vs. upstream” framework and concrete alternative prompts you can use today. The 10% moves vs. 10x moves distinction is one every PM should internalize.

   2. Choice quote: “It feels productive. But it’s automating confirmation bias at scale.”

4. Should PMs Care About AI Agents Going Rogue?

   1. What we liked: A thoughtful review of the story of an agent going rogue and writing a hit piece against a human, and what it teaches us about building in the AI-era.

   2. Choice quote: “The same root cause every time: agents with too much autonomy, too few guardrails, and no product-level decision about where the boundaries should be.”

Top Tweets

1. From Hierarchy to Intelligence

   1. What we liked: This is the most ambitious and original post in the batch — a genuine first-principles rethinking of how companies should be organized in the age of AI, from a founder actively implementing it at scale. The historical grounding gives the argument real intellectual weight, and the concrete four-layer architecture (capabilities → world model → intelligence layer → interfaces) is a framework product leaders can steal tomorrow. This is the kind of piece that redefines a conversation.

   2. Choice quote: “When the intelligence layer tries to compose a solution and can’t because the capability doesn’t exist, that failure signal is the future roadmap.”

2. Commoditizing AI Inference with Instruments

   1. What we liked: A genuinely contrarian and well-reasoned take that most product leaders haven’t internalized yet. The commodity market analogy is sharp and the framework is immediately useful for any PM or engineering leader making inference procurement decisions. The observation that every “handle” people use to pick models (parameter count, reasoning vs. non-reasoning) describes how inference is made, not what it delivers, is a powerful reframe.

   2. Choice quote: “Can you define what ‘good enough’ looks like, and let the market figure out who fills it cheapest?”

3. Stop AI Rework: 4 Operating Rules That Keep Speed and Accuracy

   1. What we liked: Short, sharp, and immediately actionable. Every rule maps to a specific failure mode that anyone working with AI in production will recognize. The reframe of “iteration” as “preventable churn” is a useful diagnostic for teams. The advice to ask Claude to build a skill whenever you finish a repeatable job is the kind of simple behavioral change that compounds.

   2. Choice quote: “AI leverage is not just better prompting. It’s better control of the seams: understanding → generation → review → action.”

Top LinkedIn Posts & Short Videos

1. In a World of Agents, the Product Role Splits in Two

   1. What we liked: A provocative and specific vision from a top-tier thinker on what PM rituals look like when agents do the execution. The “instead of standups / instead of OKRs / instead of PRDs” structure makes it immediately applicable to anyone rethinking their team’s operating model.

   2. Choice quote: “The daily ritual becomes reviewing deltas, scanning failures, and deciding which ones matter. Less reporting, more triage.”

2. Product Improv: Is Your Product Team Drifting to Failure?

   1. What we liked: A contrarian take that cuts against the “just add AI tools” narrative. The core argument — that AI without PM training creates strategic drift at higher velocity — is one of the most important warnings in the current landscape.

   2. Choice quote: “You’re not just making mediocre decisions faster — you’re scaling them.”

3. Claude Code Isn’t Just a Coding Assistant — It’s 512,000 Lines of Infrastructure

   1. What we liked: A masterclass in what “building around the model” actually looks like at production scale. Any PM building AI products should study this post — the LLM is one piece, the system around it is the product.

   2. Choice quote: “The model generates the output. The system makes sure nothing breaks on the way there.”

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In case you missed them — Adam’s recent LinkedIn Content

1. 2007: The head of design at Apple, Jony Ive, helped put a computer in your pocket and train a generation to check a glowing rectangle 96 times a day.

2. Yesterday, I was scrolling through Google’s Gemini page when I had to stop and screen record what I was seeing.

3. Everyone’s talking about how great OpenClaw is.

4. Most AI gadgets we’ve seen so far have failed in the real world.

5. I was asked recently what product would solve a problem that I feel the most, but hasn’t been made yet.

6. Your first few onboarding sessions are very delicate.

Every two weeks, we dive into the vast ocean of product content online, both free and paid. We sift through it all to bring you the crème de la crème. Our round-up includes carefully curated links and concise excerpts from top content.

This week’s highlights feature:

• Top 3 Long-Form Articles/Podcasts

• Top 3 Tweets

• Top 2 LinkedIn Posts or Short Videos

Our expert product team has selected these resources to help you save thousands of dollars on unnecessary subscriptions, avoid wasting time reading instead of taking action, and save years following the wrong advice. Our mission is to introduce you to brilliant product thinkers, whether they’re renowned experts or emerging voices.

In case you missed them, here are the recent posts from Emergent:

1. Building Revolutionary Technology for Seniors (podcast)

Top Long-Form Content

1. Why Product Sense Is the Only Product Skill That Will Matter in the AI Age

   1. What we liked: One of the most respected product sense thinkers uses a multi-turn dialogue with Claude, to try to disprove the title and yet still proves it true.

   2. Choice quote: “The only real long-term career moat for product people is how you can improve on the already-brilliant, already-comprehensive inputs and outputs that AI will provide for you.”

2. Claude Code for Product Managers

   1. What we liked: This doesn’t just describe what’s possible — it walks through the actual skill architecture, context strategy taxonomy (local files, CLI tools, MCPs, APIs, browser agent), and output-shaping techniques that make the difference between useful automation and expensive slop. The honest section on limitations earns the piece real credibility.

   2. Choice quote: “Taking the output, deciding if it’s good enough, and iterating on the workflow until it meets your quality bar — that’s the essential skill of the AI-powered product manager that still can’t be replaced by AI.”

3. AI Is Helping PMs Do the Wrong Things Faster

   1. What we liked: This piece names something most teams are quietly doing and calling discovery. The case study — where asking about goals instead of features uncovered an entirely unserved segment and drove 10x usage growth in year one — makes the argument concrete. The 10% vs. 10x move distinction is a clean, memorable frame for where senior PM attention should actually go.

   2. Choice quote: “When every company has access to the same AI-generated market data, the same AI-summarized support tickets, the same AI-clustered usage patterns, the competitive advantage shifts to whoever has proprietary insight that AI can’t generate.”

Top Tweets

1. Junior PM: Our DAU is terrible. Users log in once a month.

   1. What we liked: A rare post that names the most common PM failure pattern directly: building for the user you wish you had instead of the user you actually have. The dialogue format makes dense strategic thinking remarkably accessible. The GitHub example lands hard — daily usage is earned through indispensability, not manufactured through streaks and push notifications.

   2. Choice quote: “Every failing product needs those [notifications, streaks, points]. Make them unnecessary first.”

2. I fired 24 people in 24 hours.

   1. What we liked: Founders and PMs building zero-to-one products in AI will feel this one. The anti-”scale fast” thesis is contrarian in a VC-dominated discourse, and the personal price tag makes it credible rather than theoretical. Relevant for any PM thinking about growth strategy or organizational health under pressure.

   2. Choice quote: “Scaling fast is overrated. Slow, sustainable, cash-flow growth buys peace.”

3. The Cost of Overthinking: Why Smart People Get Stuck

   1. What we liked: Moderately relevant for PMs prone to over-planning roadmaps or deferring decisions waiting for perfect information. The replies surfaced a useful framing: “analyze → decide → execute → adjust.” However, this post leans more motivational than analytically rigorous, and the content is largely platform-agnostic rather than PM- or AI-specific. Ranked last among the five for that reason.

   2. Choice quote: “Overthinking isn’t the problem. Doing nothing while you overthink is.”

Top LinkedIn Posts & Short Videos

1. Many companies are so addicted to revenue they’re growing themselves broke.

   1. What we liked: Cuts to a real structural dysfunction holding most companies back from genuine AI-era competitiveness. The framing of “revenue addiction” as an organizational pathology rather than a strategy problem is novel and resonant for product leaders trying to justify foundational AI investments.

   2. Choice quote: “The real edge was never ‘hitting this quarter’s number.’ It’s always been building the capability that makes next quarter’s number inevitable.”

2. Most product teams have one launch checklist. They use it for everything. And that’s why customers tune out.

   1. What we liked: A practical framework any PM or PMM team can implement immediately. The point about re-launches is genuinely underrated — most teams treat launch as a one-time event and leave significant adoption on the table.

   2. Choice quote: “When every release is ‘game-changing,’ your audience learns to ignore all of them. Save the big words for when they earn it.”

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Trusted by the world’s best product teams, Productboard turns customer needs into high-impact strategy in one end-to-end platform. With Productboard Spark, you can go from raw idea to polished product brief in seconds using AI that already understands your business.

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In case you missed them — Adam’s recent LinkedIn Content

1. Hot product take: There is no single “right” way to build.

2. Volvo invented the 3-point seatbelt in 1959.

3. We had our first PR crisis recently, ironically because of someone else’s AI.

4. “Projects that used to require big teams can now be accomplished by a single very talented person.”

5. The Director of US civilian cyber defense is facing heat for pasting sensitive documents into public ChatGPT.

6. NEW EPISODE 🎙: How Chapter Is Building the Trust Layer for Seniors

7. 2,000 years ago, the Romans built gravity-fed aqueducts to move water tens of miles across mountains and valleys into their cities.

8. 1 in 2 people on the planet have used the products built by Meta.

9. Most residents today still prefer to call city hall rather than visit the city website.

10. Hong Kong has been flushing its toilets with seawater since the late 1950s.

Every two weeks, we dive into the vast ocean of product content online, both free and paid. We sift through it all to bring you the crème de la crème. Our round-up includes carefully curated links and concise excerpts from top content.

This week’s highlights feature:

• Top 3 Long-Form Articles/Podcasts

• Top 3 Tweets

• Top 3 LinkedIn Posts or Short Videos

Our expert product team has selected these resources to help you save thousands of dollars on unnecessary subscriptions, avoid wasting time reading instead of taking action, and save years following the wrong advice. Our mission is to introduce you to brilliant product thinkers, whether they’re renowned experts or emerging voices.

In case you missed them, here are the recent posts from Emergent:

1. What Jony Ive and OpenAI Are Really Building

Top Long-Form Content

1. A framework for filtering AI noise

   1. What we liked: A brutally practical antidote to AI FOMO. Diego lays out a clear 2-path framework for deciding when to integrate AI into your roadmap vs. when to ignore it—backed by real examples of failed pilots and “vibe-based QA.” Required reading for PMs being pressured to ship GenAI features without guardrails.

   2. Choice quote: “95% of GenAI pilots deliver zero P&L impact.”

2. Founders, your software company is not going to IPO

   1. What we liked: A cold splash of water for late-stage founders. Instead of chasing the IPO fantasy, this forces product leaders to design for durability, efficiency, and alternative outcomes. It challenges growth-at-all-costs thinking at exactly the right moment.

   2. Choice quote: “853 US companies are valued at $1B+. According to SVB, fewer than 5% meet the revenue + efficiency bar required to go public.”

3. Will vibe coding end like the maker movement?

   1. What we liked: A thoughtful critique of vibe coding as performance vs. durable value creation. The “no scenius phase” insight explains why so many AI prototypes feel manic but shallow. Strong perspective on where value will actually accrue in the stack.

   2. Choice quote: “Vibe coding skipped that phase entirely.”

Top Tweets

1. Cursor’s $7,225 invoice broke the internet. So I mapped pricing across 50 AI startups to figure out what’s actually working.

   1. What we liked: This takes what could’ve been surface-level outrage bait and turns it into operating insight. Instead of debating whether one invoice was “crazy,” it zooms out and analyzes patterns across 50 AI startups. The result isn’t opinion — it’s taxonomy. Six pricing models. Clear tradeoffs. A decision tree founders can actually use. It reframes pricing from vibes to design.

   2. Choice quote: “Six models emerged, four case studies, and one decision tree for picking yours.”

2. Things I wish someone told me before I almost gave up on OpenClaw

   1. What we liked: This reads like someone who bled for the knowledge. It dismantles the “just let it run overnight” fantasy and replaces it with structure: model tiering, explicit skills folders, cron isolation, verification loops. The meta-lesson is bigger than OpenClaw — agents don’t get smarter with freedom, they get better with constraints. It’s a manual for becoming an orchestrator, not just a user.

   2. Choice quote: “The agents that actually work? They’re not smarter. They’re more constrained.”

3. Most PMs write documentation backwards.

   1. What we liked: A clean mental model for product work maturity. The 1-pager → 3-pager → 5-pager progression forces validation before overinvestment. It normalizes killing ideas early and writing specs only for work that survives scrutiny. The sharpest line reframes documentation entirely: it shouldn’t scale with your anxiety — it should scale with your confidence.

   2. Choice quote: “Documentation should match your confidence level, not your anxiety level.”

Top LinkedIn Posts & Short Videos

1. The old stuff still works

   1. What we liked: A provocative take on the disutility in too much vibe coding.

   2. Choice quote: “Turns out all the engineering discipline I picked up over 20 years didn’t become obsolete, it got more important.”

2. “How much money will this feature make?”

   1. What we liked: Sharp reframing of a question every PM hears. It separates what a team can directly influence from what it merely contributes to.

   2. Choice quote: “We need to separate what our solutions can influence directly from what they only contribute to.”

3. When it comes to Strategy, what separates the Company, Product, and Feature levels?

   1. What we liked: The Russian matryoshka analogy lands because it exposes the failure mode: feature thinking masquerading as strategy. Company sets context. Product defines how to win. Features should reinforce — not rewrite — that choice. Clean mental model. Hard to argue with.

   2. Choice quote: “Features should prove the strategy, not define it.”

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This article is brought to you by Productboard

Trusted by the world’s best product teams, Productboard turns customer needs into high-impact strategy in one end-to-end platform. With Productboard Spark, you can go from raw idea to polished product brief in seconds using AI that already understands your business.

See how Productboard Spark can help your product teams ship faster →

In case you missed them — Adam’s recent LinkedIn Content

1. The ‘AI boom’ looks big until you put it next to past economic shifts.

2. I’ve watched city after city approve the same failed playbook: a chatbot here, a pilot there, a “proof of concept” that proves nothing except the vendor got paid and the “AI” box gets checked.

3. Japan’s 60-year-old bullet train, the Shinkansen line, refunded hundreds of passengers for a 35-second delay.

4. Olympic airtime for all of my favourite sports combined: 11 minutes.

5. We’ve been scared of the wrong thing when it comes to AI.

6. 9 in 10 managers regularly spend time on admin tasks. On average, those tasks consume 2 full days every week.

7. I’ve worked with hundreds of startup CEOs, and I can safely say that there is one trait that is remarkably common among the failure cases – the CEO does not have self awareness of their weaknesses.

Every two weeks, we dive into the vast ocean of product content online, both free and paid. We sift through it all to bring you the crème de la crème. Our round-up includes carefully curated links and concise excerpts from top content.

This week’s highlights feature:

• Top 3 Long-Form Articles/Podcasts

• Top 3 Tweets

• Top 4 LinkedIn Posts or Short Videos

Our expert product team has selected these resources to help you save thousands of dollars on unnecessary subscriptions, avoid wasting time reading instead of taking action, and save years following the wrong advice. Our mission is to introduce you to brilliant product thinkers, whether they’re renowned experts or emerging voices.

In case you missed them, here are the recent posts from Emergent:

1. AI Isn’t Replacing Junior Devs - It’s Exposing Their True Value

Top Long-Form Content

1. Every Maker Is Now a Manager (of AI)

   1. What we liked: A deeply researched, contrarian take from someone actively building in this space. Instead of the typical “AI makes you more productive!” narrative, this names the psychological toll that most practitioners feel but can’t articulate — and proposes a design-level fix.

   2. Choice quote: “We spend our attention evaluating results instead of supervising the process. As we would with a capable colleague!”

2. Digital Twins for Product Feedback

   1. What we liked: This is the kind of specific, replicable PM workflow that readers can implement Monday morning. The honest limitations section (you need a year of built-up context, human judgment is non-negotiable, the twin will sometimes be wrong) adds credibility. A pure signal piece for working PMs.

   2. Choice quote: “I used to approach documents hoping they’d survive first contact. Now I send them knowing they already have.”

3. A Personal OS in Claude Code

   1. What we liked: The most immediately copy-paste-able article of the week. Where most “personal OS” content stays at the concept level, this one gives you the folder structure, the CLAUDE.md file, the workflow specs, and the example commands. The templates vs. workflows distinction alone is worth the read.

   2. Choice quote: “Less files = less LLM decision-making about what to prioritize. Claude can pick up what it needs from one consolidated doc.”

Top Tweets

1. Software development is undergoing a renaissance in front of our eyes.

   1. What we liked: This is the post of the week. A co-founder of OpenAI sharing the actual internal memo for how they’re restructuring their own teams around coding agents. The specificity is remarkable — skills directories, AGENTS.md files, “say no to slop” as a code quality principle. Every product leader should read this as a preview of what their own org will need to do in the next 6 months.

   2. Choice quote: “For any technical task, the tool of first resort for humans is interacting with an agent rather than using an editor or terminal.”

2. The combination is rare because most orgs actively select against it.

   1. What we liked: A contrarian, honest take on why the “high agency” mantra falls flat in practice. The insight that PMs who survive 10+ years optimize for just enough agreeability to stay employed is uncomfortable and true. Directly relevant to AI-first PMs who need to push orgs toward uncomfortable transformations.

   2. Choice quote: “Real high agency means burning political capital regularly. You need enough wins to replenish faster than you spend.”

3. 9 prioritization lessons I learned the hard way.

   1. What we liked: The “ignorance tax” framing is memorable and immediately applicable. The contrarian point that you won’t need frameworks if your strategy is focused enough challenges the PM community’s obsession with scoring models.

   2. Choice quote: “Most of the time you won’t need any frameworks if you have an adequately focused strategy.”

Top LinkedIn Posts & Short Videos

1. “Have you ever noticed that AI gets worse the longer you talk to it?”

   1. What we liked: Takes a phenomenon every PM has experienced but few can explain and turns it into a systematic playbook. The parallels drawn to human cognition (recency bias, working memory, overload) make the concept immediately intuitive. 365+ reactions and 42 comments show massive resonance. Highly practical for any PM using AI tools daily.

   2. Choice quote: “Long conversations dilute attention, not because the model is ‘forgetting,’ but because it’s deciding what matters now.”

2. AI coding tools are turning PMs into “builders” for the wrong features.

   1. What we liked: A timely contrarian take that challenges the vibe-coding hype. The core insight — that engineering scarcity used to force better thinking, and AI abundance has removed that constraint — is sharp and important. The three pre-build questions are immediately applicable.

   2. Choice quote: “AI doesn’t fix unclear thinking. It just executes it faster.”

3. Everyone’s building AI agents. Very few understand what’s actually under the hood.

   1. What we liked: A solid architectural mental model for PMs who need to understand agent infrastructure without getting lost in engineering details. The body-as-metaphor framework (brain, hands, nervous system) makes the stack intuitive and memorable. Useful for any PM scoping or evaluating AI agent products.

   2. Choice quote: “A model without tools is just a chatbot.”

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In case you missed them — Adam’s recent LinkedIn Content

1. In 2024, I joined South Park Commons, founded by Ruchi Sanghvi and Aditya Agarwal, to spend time figuring out what was actually worth building.

2. Nearly 80% of organizations say they’re using AI, yet only ~1% have it fully embedded across teams.

3. A Florida commuter wired a signal jammer into his car to block mobile phone use on his daily drive to increase his safety from distracted drivers. Instead of praise, he was hit with a $48,000 fine.

4. India built a public payments system that now accounts for roughly 49% of all real-time payment transactions in the world.

5. People keep framing the AI race like a sprint.

6. Steel from WW2 pulled from old shipwrecks is used to build some of the most precise scientific instruments on Earth.

Every two weeks, we dive into the vast ocean of product content online, both free and paid. We sift through it all to bring you the crème de la crème. Our round-up includes carefully curated links and concise excerpts from top content.

This week’s highlights feature:

• Top 3 Long-Form Articles/Podcasts

• Top 3 Tweets

• Top 4 LinkedIn Posts or Short Videos

Our expert product team has selected these resources to help you save thousands of dollars on unnecessary subscriptions, avoid wasting time reading instead of taking action, and save years following the wrong advice. Our mission is to introduce you to brilliant product thinkers, whether they’re renowned experts or emerging voices.

In case you missed them, here are the recent posts from Emergent:

1. English Is the Silent Default in AI Models (Video)

Top Long-Form Content

1. Management as AI Superpower

   1. What we liked: Reframes “management” from a soft skill to the core competency of the AI era. The “Equation of Agentic Work” framework for deciding when to delegate to AI is immediately actionable for PMs and builders alike.

   2. Choice quote: “The skills that are so often dismissed as ‘soft’ turned out to be the hard ones.”

2. How to Write a Good Spec for AI Agents

   1. What we liked: Solves the real pain point every PM and developer faces: how to communicate intent to AI without overwhelming it. The “six core areas” checklist and three-tier boundary framework (Always/Ask first/Never) are immediately deployable.

   2. Choice quote: “The key is to write smart specs: documents that guide the agent clearly, stay within practical context sizes, and evolve with the project.”

3. The 80% Problem in Agentic Coding

   1. What we liked: A brutally honest examination of the emerging “comprehension debt” crisis as developers ship code they don’t fully understand. Critical for product and startup leaders to be aware of.

   2. Choice quote: “If your ability to ‘read’ doesn’t scale at the same rate as the agent’s ability to ‘output,’ you aren’t engineering anymore. You’re rubber stamping.”

Top Tweets

1. The most underrated line in @karpathy’s post...

   1. What we liked: Captures an important nuance most miss—the difference between making something work quickly versus building something scalable and monetizable. Highly relevant for PMs navigating the build-vs-buy decision in the AI era.

   2. Choice quote: “There’s vibe coding (make it work now) and there’s vibe engineering (build the right thing in a way you can scale and monetize).”

2. Most product strategy is optimistic guessing wearing a suit.

   1. What we liked: Offers a practical mental model that flips conventional strategy thinking on its head. The framework—current state, projected mess, ideal future, then ideal current state—is immediately actionable.

   2. Choice quote: “If you can’t articulate the failure path, you don’t understand your position. You’re hoping.”

3. Every PM who wants to survive the AI era should watch this video

   1. What we liked: Dense with actionable wisdom from someone who built core products at Google, Facebook, Square, and DoorDash. The insight that PMs should define outcomes as customer state changes rather than features shipped is a mindset shift worth internalizing.

   2. Choice quote: “Your value is editorial capability—looking at 100 features and identifying the 2 things that will actually drive customer outcomes.”

Top LinkedIn Posts & Short Videos

1. Hot take: AI isn’t going to replace Product Managers. It’s going to expose who was never a PM to begin with.

   1. What we liked: A bold, contrarian take with a concrete two-stack framework that distinguishes between enduring PM skills and emerging AI competencies. The specific technical skills listed in Stack 2 provide a practical learning roadmap for PMs wanting to stay relevant.

   2. Choice quote: “It’s replacing artifact PMs - the ones whose entire job is ‘formatting’ thinking, not doing thinking THEMSELVES.”

2. Stop asking AI to do your job. Ask it to make you better at it.

   1. What we liked: An actionable framework that flips conventional AI usage on its head. The specific prompt examples are immediately usable, and the insight that AI should stress-test thinking rather than bypass it is genuinely novel.

   2. Choice quote: “If you use AI to bypass the thinking process, you’re automating away your own value. But if you use AI to stress-test your thinking, you become 10x more effective.”

3. Most people want AI to sound like them. But no one does this first (and it takes 47 mins).

   1. What we liked: A deeply practical system for solving the generic AI output problem. The emphasis on documenting rejections rather than just preferences is a clever insight, and the portability across AI tools makes this a foundational productivity technique.

   2. Choice quote: “80% of your file should be what you’d never say.”

4. Everyone tells you what you should do. Yet, no one knows your context.

   1. What we liked: A refreshing counter to the framework-obsessed PM culture. The practical action items are immediately executable, and the honest self-reflection about blaming company rigidity resonates with many PMs.

   2. Choice quote: “Product folks like playing a game, finding excuse not to do the job. I played that for too long, blamed the company rigidness. Once I stopped playing that stupid game, growth became natural.”

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In case you missed them — Adam’s recent LinkedIn Content

1. Wikipedia hasn’t had a real competitor in 30 years.

2. Tesla’s trillion-dollar 2025 shareholder-approved pay package matters for one simple reason: it only rewards results that materially change the landscape of the American economy.

3. 10 shocking facts everyone should know about our government today:

4. I finally found a great use case for OpenAI’s Operator agent in my personal life.

5. Around 30% of US job openings have disappeared since ChatGPT launched in 2022.

6. Your parking ticket was issued by AI, and now your parking laws might be written by it, too.

Every two weeks, we dive into the vast ocean of product content online, both free and paid. We sift through it all to bring you the crème de la crème. Our round-up includes carefully curated links and concise excerpts from top content.

This week’s highlights feature:

• Top 3 Long-Form Articles/Podcasts

• Top 3 Tweets

• Top 3 LinkedIn Posts or Short Videos

Our expert product team has selected these resources to help you save thousands of dollars on unnecessary subscriptions, avoid wasting time reading instead of taking action, and save years following the wrong advice. Our mission is to introduce you to brilliant product thinkers, whether they’re renowned experts or emerging voices.

Top Long-Form Content

1. AI evals are changing the PM craft

   1. What we liked: Tackles the most critical evolution in AI-first PM craft with concrete frameworks for integrating evals throughout product development, from customer research to PRD writing to testing, complete with real examples from Amplitude, Harvey, and AirOps.

   2. Choice quote: “Instead of measuring ‘# users who completed the 5-step email creation flow,’ PMs need to ask, ‘Did the email meet our quality bar? How many edits were needed before the user sent the email we drafted?’”

2. Claude Code and What Comes Next

   1. What we liked: An analytical approach to unpack why this moment in AI tools represents a genuine capability leap. The hands-on experiment (Claude working independently for 74 minutes to build a functional startup) makes the abstract concrete.

   2. Choice quote: “I’ve never felt this much behind as a programmer. The profession is being dramatically refactored as the bits contributed by the programmer are increasingly sparse and between.”

3. Data Is Your Only Moat

   1. A strategic 2x2 framework analyzing AI applications by adoption difficulty and problem complexity. Explains why coding agents improved so fast (easy adoption → data flywheel), and predicts the “hard-hard” quadrant will see the next wave of winners.

   2. What we liked: Finally, someone articulates why different AI categories are succeeding at different rates. The insight that enterprise integration difficulty creates its own moat is counterintuitive but compelling for founders and PMs positioning their products.

   3. Choice quote: “Easy to adopt also means easy to displace. Hard to adopt products have their own data moat: Once you’re embedded in an enterprise, you learn about how that company works in a way that makes your product incredibly hard to replace.”

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4. 10 Ideas for 2026

   1. What we liked: Shreyas cuts through the noise with pithy observations that lodge in your brain. The piece on being “perpetual pawns of problems that shouldn’t have arisen” is a perfect diagnosis of chronic organizational fire-fighting.

   2. Choice quote: “The reason you are saying we don’t have time to think right now and we must do something right away is that you said the same thing last time and before that and the time before that, and so we are now perpetual pawns of problems that shouldn’t have arisen in the first place.”

Top Tweets

1. I just saved hours per week with ONE hour and ONE button press inside Claude.

   1. What we liked: A highly actionable tutorial from one of AI’s most prominent voices that shows exactly how to leverage Claude’s underutilized Skills feature for productivity gains. This is the kind of practical workflow optimization AI-first PMs should be implementing immediately.

   2. Choice quote: “Now, for the rest of eternity, I just have to type into a conversation ‘write me a newsletter subject line’ it will apply all of my rules and preferences and style and structure and output them in the exact way and order that I want.”

2. We built Openwork!

   1. What we liked: A practical, open-source tool announcement that addresses real cost concerns with Claude Cowork while demonstrating concrete automation workflows. The ability to chain local and cloud actions is particularly valuable for PMs managing complex project portfolios.

   2. Choice quote: “In the demo we use it to scan through my laptop and find all my unfinished projects and put them in a notion database with completion status.”

3. I know exactly what would fix our product org.

   1. What we liked: Cuts through typical PM platitudes to address the structural dysfunction most PMs face daily. The tactical advice to document rework patterns and reframe pitches around cost rather than process is immediately applicable. The honest acknowledgment that some systems simply can’t be fixed without executive intervention will resonate with frustrated PMs.

   2. Choice quote: “Problems move people. Solutions don’t. Your manager doesn’t care about product operating models. They care about the $2M you’re burning on coordination overhead.”

Top LinkedIn Posts & Short Videos

1. The real reason you get pushback on Discovery is because you communicate it as a phase and “Plan this for Q1.”

   1. What we liked: Reframes Discovery from ceremony to continuous uncertainty reduction, making it more palatable to stakeholders and more effective for teams. The practical Freemium launch example demonstrates how to identify and test critical assumptions without ritual.

   2. Choice quote: “Discovery isn’t about running a prescribed set of activities—interviews, prototypes, opportunity solution trees—because you’re supposed to. It’s about identifying your riskiest assumptions and testing them as cheaply as possible before you commit engineering capacity and organizational credibility.”

2. Do you know how to correctly set user personas for your product?

   1. What we liked: Uses a memorable, humorous example to drive home a critical point about behavior-based segmentation. Clarifies the distinction between demographics (useful for product building) and personas (representing usage patterns).

   2. Choice quote: “User personas are about identifying patterns of behavior, not about any specific user, fictional or otherwise.”

3. GTM ≠ product launches.

   1. What we liked: Challenges the common conflation of GTM and launches with a memorable analogy and actionable framework. The visual comparison chart makes the distinction immediately usable for product teams and founders.

   2. Choice quote: “A launch can’t fix a weak GTM strategy... A launch is an accelerant. It amplifies whatever you give it. If your product is an absolute ball of crap, that’s what the launch will amplify.”

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In case you missed them — Adam’s recent LinkedIn Content

1. Every city leader I meet wants faster service delivery with AI. And increasingly, the teams running those services want to deliver it.

2. City and county leaders: stop hiring incumbents who treat your contract like a guaranteed paycheck.

3. A city once invited us in for an in-person working session.

4. I just finished one of the most talked-about books in government right now, “Breakneck: China’s Quest to Engineer the Future,” and it made me rethink something we see every day inside cities.

Every two weeks, we dive into the vast ocean of product content online, both free and paid. We sift through it all to bring you the crème de la crème. Our round-up includes carefully curated links and concise excerpts from top content.

This week’s highlights feature:

• Top 3 Long-Form Articles/Podcasts

• Top 3 Tweets

• Top 3 LinkedIn Posts or Short Videos

Our expert product team has selected these resources to help you save thousands of dollars on unnecessary subscriptions, avoid wasting time reading instead of taking action, and save years following the wrong advice. Our mission is to introduce you to brilliant product thinkers, whether they’re renowned experts or emerging voices.

Top Long-Form Content

1. Beyond “AI Product Managers” - How Proper PMs Can Start Thinking About AI Product Strategy

   1. What we liked: A refreshingly contrarian take that challenges the “AI Product Manager” title craze with a simple, actionable framework for deciding which AI initiatives actually deserve investment versus which are just checkbox exercises for boards.

   2. Choice quote: “If everyone’s super for wrapping an LLM into their product, then no one is.”

2. 13 Product-building Lessons from Palantir

   1. What we liked: Real war stories from the trenches with specific examples of what went wrong and why, from building calculator widgets that users rejected to managing custom deployments that nearly sank into technical debt - lessons you can’t get from frameworks.

   2. Choice quote: “Secondhand understanding is almost always incomplete. When engineers only read tickets or summaries, they miss the context that shapes a user’s real-world decisions.”

Read more

Every two weeks, we dive into the vast ocean of product content online, both free and paid. We sift through it all to bring you the crème de la crème. Our round-up includes carefully curated links and concise excerpts from top content.

This week’s highlights feature:

• Top 3 Long-Form Articles/Podcasts

• Top 4 Tweets

• Top 3 LinkedIn Posts or Short Videos

Our expert product team has selected these resources to help you save thousands of dollars on unnecessary subscriptions, avoid wasting time reading instead of taking action, and save years following the wrong advice. Our mission is to introduce you to brilliant product thinkers, whether they’re renowned experts or emerging voices.

Top Long-Form Content

1. The 3 Forces Killing AI Startups (And How the 10% Survive)

   1. What we liked: A contrarian take on AI startup economics showing how successful AI companies can access 80-133x larger TAMs by targeting HR budgets ($96k-$160k/year per agent) versus traditional SaaS IT budgets ($1.2k/year per seat).

   2. Choice quote: “You’re not competing with other AI tools. You’re competing with hiring decisions.”

2. Why AI Cannot Simulate Your Customers’ Behaviour

   1. What we liked: A reality check for product managers showing why talking to real customers remains irreplaceable, with a clear 4-step framework for validating actual customer needs versus AI-generated hypotheses.

   2. Choice quote: “Founders would literally rather boil the ocean than talk to customers.”

Read more

Every two weeks, we dive into the vast ocean of product content online, both free and paid. We sift through it all to bring you the crème de la crème. Our round-up includes carefully curated links and concise excerpts from top content.

This week’s highlights feature:

• Top 3 Long-Form Articles/Podcasts

• Top 4 Tweets

• Top 3 LinkedIn Posts or Short Videos

Our expert product team has selected these resources to help you save thousands of dollars on unnecessary subscriptions, avoid wasting time reading instead of taking action, and save years following the wrong advice. Our mission is to introduce you to brilliant product thinkers, whether they’re renowned experts or emerging voices.

Top Long-Form Content

1. The AI Application Spending Report

   1. What we liked: This data-driven report reveals which AI tools are gaining real traction among startups, showing that horizontal applications (60%) are dominating vertical ones (40%), and that creative tools and “vibe coding” have become truly cross-functional capabilities.

   2. Choice quote: “AI is changing what skills people have, what tasks people do, and what teams look like... not only is AI augmenting employees in specific roles, it’s turning specific roles into broadly deployed skills across a company (everyone can be a creative now!).”

2. The Emerging AI-Native GTM Playbook: 6 Patterns from companies racing to $100M

   1. What we liked: Identifies six counterintuitive patterns that separate explosive AI-native growth from incremental progress, backed by real data from companies reaching $100M ARR with remarkably lean teams.

   2. Choice quote: “The playbook for building billion-dollar AI companies looks radically different from the SaaS era. While traditional enterprise software companies spent years building sales teams and marketing engines, a new generation of AI-native startups is reaching massive scale with lean teams, minimal funding, and unconventional strategies.”

Read more

Every two weeks, we dive into the vast ocean of product content online, both free and paid. We sift through it all to bring you the crème de la crème. Our round-up includes carefully curated links and concise excerpts from top content.

This week’s highlights feature:

• Top 4 Long-Form Articles/Podcasts

• Top 3 Tweets

• Top 4 LinkedIn Posts or Short Videos

Our expert product team has selected these resources to help you save thousands of dollars on unnecessary subscriptions, avoid wasting time reading instead of taking action, and save years following the wrong advice. Our mission is to introduce you to brilliant product thinkers, whether they’re renowned experts or emerging voices.

Top Long-Form Content

1. The Execution Trap for Product Managers

   a. What we liked: A highly actionable 5-step framework for inspiring teams while orchestrating complex product launches. A bit touchy-feely, but on point.

   b. Choice quote: “When everything looks like a high-priority, dependency-free ‘win,’ teams tune out. Orchestration without inspiration turns into background noise.”

2. 15 Hot Takes That Cut Through the AI Hype

   a. What we liked: The author’s contrarian takes challenge conventional wisdom with brutal honesty—like “AI agents often aren’t the right solution” and his decision tree for when to actually build an AI agent. The practical guidance on building AI-native teams and avoiding “vibe coding” provides immediate value for product leaders.

   b. Choice quote: “The term ‘AI PM’ has become a meaningless branding exercise. Everyone’s an ‘AI PM’ on LinkedIn these days. What matters more is showing proof of work—what did you actually ship with AI recently?”

Read more

Every two weeks, we dive into the vast ocean of product content online, both free and paid. We sift through it all to bring you the crème de la crème. Our round-up includes carefully curated links and concise excerpts from top content.

This week’s highlights feature:

• Top 3 Long-Form Articles/Podcasts

• Top 3 Tweets

• Top 4 LinkedIn Posts or Short Videos

Our expert product team has selected these resources to help you save thousands of dollars on unnecessary subscriptions, avoid wasting time reading instead of taking action, and save years following the wrong advice. Our mission is to introduce you to brilliant product thinkers, whether they’re renowned experts or emerging voices.

Top Long-Form Content

1. The AI Productivity Paradox: High Adoption, Low Transformation

   1. What we liked: Strong framing of the “shadow AI” economy and the need for adaptive systems and process redesign.

   2. Choice quote: “Most organizations aren’t failing because they lack AI tools. They’re failing because AI sits in the shadows, disconnected from workflows, never compounding into real productivity.”

2. 15 AI Distribution Plays That Build Real Moats

   1. What we liked: It gives PMs permission to make distribution requirements first-class PRD elements alongside UX and technical specs.

   2. Choice quote: “In AI, the half-life of differentiation is measured in weeks…This means distribution is not a GTM exercise. It’s a product design principle.”

Read more

Every two weeks, we dive into the vast ocean of product content online, both free and paid. We sift through it all to bring you the crème de la crème. Our round-up includes carefully curated links and concise excerpts from top content.

This week’s highlights feature:

• Top 4 Long-Form Articles/Podcasts

• Top 4 Tweets

• Top 3 LinkedIn Posts or Short Videos

Our expert product team has selected these resources to help you save thousands of dollars on unnecessary subscriptions, avoid wasting time reading instead of taking action, and save years following the wrong advice. Our mission is to introduce you to brilliant product thinkers, whether they’re renowned experts or emerging voices.

In case you missed them, here are the posts from Emergent from the past three weeks:

1. Best Of Product Roundup - August 16, 2025

2. (Video) AI Is Here—So Why Are We Still Hiring Designers and Engineers? (free)

3. (Video) Why the Future of Product Management Is Deeply Technical (free)

Top Long-Form Content

1. OpenAI’s Product Lead Reveals the 4-Part Framework for AI Product Strategy

   1. What we liked: A sharp warning for product leaders that defensibility in AI comes from moats like data, trust, and distribution — not just adding AI features.

   2. Choice quote: “AI itself isn’t the moat. Everyone can access GPT-4o, Claude, Llama, Mistral. The barrier to entry is zero. If your strategy is ‘use OpenAI’s API and wrap a UI around it,’ you don’t have a company, you have an expensive demo that can be cloned overnight.”

2. You think you are AI-first, but you probably aren't

   1. What we liked: This challenges superficial AI adoption and urges product professionals to rethink their systems from the ground up for meaningful transformation.

   2. Choice quote: "You can’t really be ‘AI-first’ or ‘AI-native’ unless you reimagine your business around the architectural properties of AI."

Read more

Every two weeks, we dive into the vast ocean of product content online, both free and paid. We sift through it all to bring you the crème de la crème. Our round-up includes carefully curated links and concise excerpts from top content.

This week’s highlights feature:

• Top 4 Long-Form Articles/Podcasts

• Top 3 Tweets

• Top 3 LinkedIn Posts or Short Videos

Our expert product team has selected these resources to help you save thousands of dollars on unnecessary subscriptions, avoid wasting time reading instead of taking action, and save years following the wrong advice. Our mission is to introduce you to brilliant product thinkers, whether they’re renowned experts or emerging voices.

In case you missed them, here are the posts from Emergent from the past three weeks:

1. (Video) Vibe Coding Influencers are Lying To You (free)

2. (Podcast) The Defense Startup That’s Quietly Disrupting China and Russia (free)

3. (Article) Write perfect prompts with no effort (free+Custom GPT)

4. (Video) The Death of the Middle: Why Average is Over (free)

Top Long-Form Content

1. How to Create an AI Product Strategy

   1. What we liked: A hot take with an easy to follow 7-step framework on product strategy with AI from an OpenAI product leader.

   2. Choice quote: “Your AI product strategy is the DNA of your product. If the DNA is wrong, no amount of growth hacks or funding will save it.”

2. Why Winners Win

   1. What we liked: Emphasizes some of the patterns that will still win in an AI world including examples from Roblox, Anduril, and more.

   2. Choice quote: “Modelbusters usually take one of two forms: companies with a larger-than-anticipated TAM and companies that add product lines that open up even more opportunities for their business.”

Read more

Every two weeks, we dive into the vast ocean of product content online, both free and paid. We sift through it all to bring you the crème de la crème. Our round-up includes carefully curated links and concise excerpts from top content.

This week’s highlights feature:

• Top 3 Long-Form Articles/Podcasts

• Top 3 Tweets

• Top 4 LinkedIn Posts or Short Videos

Our expert product team has selected these resources to help you save thousands of dollars on unnecessary subscriptions, avoid wasting time reading instead of taking action, and save years following the wrong advice. Our mission is to introduce you to brilliant product thinkers, whether they’re renowned experts or emerging voices.

In case you missed them, here are the posts from Emergent from the past three weeks:

1. (Video) The Most Dangerous Productivity Myth (free)

2. (Video) The Non-Technical PM Is Dead (free)

Top Long-Form Content

1. Context Engineering: Bringing Engineering Discipline to Prompts

   1. What we liked: Helps to define this new term “context engineering” and reframes prompt engineering as only the starting point.

   2. Choice quote: “Prompt engineer: Maybe if I phrase it this way, the LLM will do what I want…Context Engineering: What inputs does this system need?”

2. Why most startups are building AI the wrong way

   1. What we liked: Pushes us to acknowledge our pre-generative-AI product thinking baggage and gives us a path to think from AI first principles.

   2. Choice quote: “You no longer need step-by-step flows. You no longer need the user to click through menus and logic trees.”

Read more

Every two weeks, we dive into the vast ocean of product content online, both free and paid. We sift through it all to bring you the crème de la crème. Our round-up includes carefully curated links and concise excerpts from top content.

This week’s highlights feature:

• Top 4 Long-Form Articles/Podcasts

• Top 3 Tweets

• Top 4 LinkedIn Posts or Short Videos

Our expert product team has selected these resources to help you save thousands of dollars on unnecessary subscriptions, avoid wasting time reading instead of taking action, and save years following the wrong advice. Our mission is to introduce you to brilliant product thinkers, whether they’re renowned experts or emerging voices.

In case you missed them, here are the posts from Emergent from the past three weeks:

1. (Video) The Secret to Sales? Shut Up. (free)

2. (Video) Equity Math Every Startup Should Understand (free)

Top Long-Form Content

1. How to build prototypes that actually look like your product (podcast)

   1. What we liked: For anyone experimenting with design prototyping tools, the disconnect between what AI generates and what your engineers see in production can be a major communication problem. Plus, we wrote a similar piece months ago, and this goes far beyond!

   2. Choice quote: “These tools can be used by anyone on the team…there’s no limit on who’s allowed to have ideas.”

2. The rise of the AI-native employee

   1. What we liked: A clear redefinition of modern productivity that reframes AI fluency not as a skill set but as a mindset. We also love that the author wasn’t working in these cultures previously, so the contrast is stark.

   2. Choice quote: “An AI-native employee isn’t someone who ‘uses AI.’ It’s someone who defaults to AI.”

Read more