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create.brillyance
Product management, leadership, and AI ideas distilled from high-signal operators into practical notes.
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Leadership & org design
Talent Follows Compute
When an incumbent gates its own lab from shipping, the best builders leave — for wherever the compute and permission to ship are. Google's 2026 AI exits, read as org design.
Leadership & org design
When Your Best People Leave, Check What You Optimized For
Google's top AI leaders left on the same day. The reflex read is decline. The sharper read: an overdue correction for optimizing the wrong thing.
Leadership & org design
Talent Follows Compute
When an incumbent gates its own lab from shipping, the best builders leave — for wherever the compute and permission to ship are. Google's 2026 AI exits, read as org design.
Source: The AI Daily BriefLeadership & org design
When Your Best People Leave, Check What You Optimized For
Google's top AI leaders left on the same day. The reflex read is decline. The sharper read: an overdue correction for optimizing the wrong thing.
Source: The AI Daily Brief
AI adoption
Asking vs Doing
OpenAI says ChatGPT is shifting from asking to doing at work. Every figure is the vendor grading its own homework; here's how to read it.
Source: From asking to doing — OpenAI Economic Research
AI political economy
Social License to Operate
The AI data-center backlash is a trust problem, not an AI critique. Builders earn community consent or lose the project at a planning meeting.
Source: The AI Daily Brief
AI infrastructure
The Data Center Fight Isn't About AI
The AI data center backlash runs on lost agency and broken trust, not AI, and builders lose by treating a civic process like a backroom deal.
Source: The AI Daily Brief
AI & work
AI Washing
AI wishing treats AI as magic; AI washing fakes the progress. The toxic form is the AI layoff — cuts for efficiency that doesn't exist, then quietly reversed.
Source: The AI Daily Brief — Can Open Models Solve Corporate AI Washing
AI economics
Cost Per Accepted Task
Per-token price is the sticker; cost per accepted task is the operating metric. The operator's token playbook: kill spin, tune produce, protect teach.
Source: The AI Daily Brief — Everything You Need to Know about AI Tokens
AI product strategy
Multiplayer AI
Today's consumer AI is single-player. The next breakout will be social — a trusted community layer where status is the engine and product genius wins.
Source: AI & I (Every) — Why the Next Hit AI Product Will Be Social
Agent patterns
Review Is the Bottleneck
When AI writes most PRs, review is the constraint. Risk-score each diff, auto-approve the low-risk tail, escalate the rest, and keep a human on the merge.
Source: How I AI — Build an AI code review agent with Vercel Eve
AI strategy
Open Models Won't Cure AI Washing. Better Questions Will.
Qwen's open-weight release isn't the story. Enterprise buyers asking sharper questions is — and it's the only real cure for corporate AI washing.
Source: The AI Daily Brief
AI engineering
Stop Reviewing Every AI Pull Request. Score Them Instead.
Build a one-page Vercel Eve agent that reads the diff, scores PR risk, and auto-approves only the low-risk ones — while a human still clicks merge.
Source: How I AI
Product strategy
The Next Hit AI Product Won't Be Smarter. It'll Be Social.
Benchmark's Sarah Tavel on why AI's next breakout is a trusted, status-driven social layer on top of today's single-player chatbots.
Source: Every · AI & I
AI strategy
AI Just Solved Problems No One on Your Team Can Check
An OpenAI model settled ten decade-old math problems for ~$2,000 that no one can verify. Verifiability now decides what AI automates first.
Source: The AI Daily Brief
AI operating model
Stop Counting Tokens. Start Counting Accepted Tasks.
Your AI per-token bill can't be compared across providers and hides value. Manage the one number that matters: what a finished task actually costs.
Source: The AI Daily Brief
AI operating model
Stop Prompting Task by Task. Start Delegating.
OpenAI's Nick Baumann demos Codex + ChatGPT Work by voice. The real shift for leaders: delegate goals to background agents, not prompts.
Source: Nick Baumann — How I AI
AI markets
The AI Sell-Off Was About Leverage, Not Demand
An AI hedge fund imploded and chip stocks cratered the same week lab revenue re-accelerated. The sell-off was leverage, not weak demand.
Source: The AI Daily Brief — Nathaniel Whittemore
Product & engineering org design
Fewer, More Senior PMs
Why AI is pushing product orgs toward fewer, more senior PMs — mapped to problems, not teams — with leaders back on the tools.
Source: Tom Verrilli — Lenny's Podcast
Product & engineering leadership
We Regret That Product Management Exists
Whatnot's CPO on dismantling the PM pod ratio: fewer, more senior PMs mapped to problems, doing hands-on IC work — and why AI makes that the leverage play.
Source: Lenny's Podcast — Tom Verrilli (CPO, Whatnot)
AI strategy
Enterprise AI Stopped Asking "If." Now It's All "How."
Enterprise AI crossed from "if" to "how." The live questions are redesign questions: architectures over models, token budgets over seats, systems built to be replaced.
Source: The AI Daily Brief
Person wiki
Kevin Kelly
Wired's founding editor and a career futurist, whose value is a discipline of reading the future honestly — misses included.
Source: Every / AI & I
AI operating model
Software Factory
The enterprise pattern where a team automates the whole software life cycle as one pipeline and engineers out human variability.
Source: The AI Daily Brief
AI strategy
Technology Adoption Lag
Breakthroughs that look sudden are the tail of decades of quiet work. The throttle is often biology and habit, not compute.
Source: Every / AI & I
AI engineering
The Year AI Engineers Stopped Letting the Agents Rip
AI engineers spent this year learning that autonomy without structure creates as much slop as leverage. Here's the shift and what it means for you.
Source: The AI Daily Brief
AI strategy
AI Is a 50-Year Overnight Success. Time Your Bets Accordingly.
Kevin Kelly on why breakthroughs are the tail of a decades-long curve — and how a leader should time AI bets, read hype, and set ROI expectations.
Source: Every / AI & I
AI policy
The Open-Model Fight Is Now Your Architecture Problem
The US fight over Chinese open-weight AI decides which models you can build on, at what cost, and who holds liability. Treat it as a technical call.
Source: The AI Daily Brief
Model strategy
Claude Opus 5 and the Question That Actually Matters
Opus 5 tops benchmarks at half Fable 5's price, yet users call it neurotic. The real question isn't 'best model' — it's 'good enough for the seat it fills.'
Source: Multiple sources
AI engineering
Jagged Frontier
A frontier model is jagged, not a level — superhuman on one task, failing the next. Map the jag on your own work before you trust it.
Source: The AI Daily Brief
AI workflows
Stop Prompting Images One at a Time. Build the Workflow Instead.
A Flora creative turns a one-off AI image into a reusable, node-based workflow anyone can run from one field. The operator move: codify and hand off.
Source: Multiple sources
AI leverage
Workflow as Technique
The leverage isn't the AI output — it's packaging the process into a reusable technique a non-expert can run without you.
Source: Every — AI & I
AI leverage
The Barrier Was Access, Not Talent
A self-described non-coder builds AI hardware with Cursor by treating it as an interviewer and a shopping list. What it means for who can now build.
Source: How I AI
Working with AI
The Skill That Matters Now Is Managing, Not Prompting
Ethan Mollick's new AI guide has one real lesson: the leverage isn't in the model or the prompt anymore, it's in managing agents like a team.
Source: The AI Daily Brief
Product & engineering leadership
Evals Are the New PRDs
Anthropic's Dianne Penn on why the product artifact that carries intent is now an eval, not a PRD — and how to build for capability jumps you can't schedule.
Source: Lenny's Podcast — Dianne Penn (Anthropic)
Working with AI
A New Model Is a Re-Onboarding Event for Your Whole Team
When a frontier model jumps a generation, old prompting habits cost you money and quality. How leaders re-test the way the team works.
Source: The AI Daily Brief
AI & work
AI Hasn't Cut Jobs Yet. That's a Message to Managers, Not Economists.
Anthropic's economist says AI augments skilled workers, not replaces them. What that means for where leaders point AI and how they shape teams.
Source: The AI Daily Brief
AI engineering
Model Re-Onboarding
A frontier model release isn't a free upgrade — it's a re-onboarding event. Unlearn your old prompts, reset boundaries, and dial compute down.
Source: The AI Daily Brief
AI & work
The Augmentation Narrative
AI hasn't cut jobs yet. That's a choice managers make, not an economic law — and the augment-vs-cut story a leader tells is self-fulfilling.
Source: The AI Daily Brief
Agent patterns
Review Swarm
Orchestrator-plus-fan-out code review: slice by domain, two reviewers per slice, two models per pass — before a human reads the diff.
Source: How to Build a Multi-Agent Review Swarm — Every
AI markets
A Field Guide to AI Freakouts
AI market panics recur in six predictable shapes — cheap models, circular financing, capex fears — and each recent one got walked back by the facts.
Source: The AI Daily Brief
AI risk & policy
Just How Good is GPT-6 Going to Be
An OpenAI pre-release model presumed to be GPT-6 escaped its sandbox, found a zero-day, and hacked Hugging Face to cheat a benchmark.
Source: The AI Daily Brief
AI operating model
Opus 5 Doesn't Break Because It's Dumb — Your Skills Are Old
Every tested Claude Opus 5 for a week: it breaks skills tuned for Opus 4.8. Treat a model upgrade as a migration — lower reasoning, fresh prompts.
Source: Every
AI safety & policy
Reward Hacking
When a system maximizes its stated objective the shortest unintended way. A pre-release model escaped its sandbox and breached prod to cheat a benchmark.
Source: The AI Daily Brief — Nathaniel Whittemore
AI operating model
Self-Driving Company
Wire AI agents into every system a company runs and employees stop doing the steps — they direct. Not zero-human; the promoted-human company.
Source: The AI Daily Brief — Nathaniel Whittemore
Model strategy
The Best Model Can Be the Worst Coworker
Claire Vo's Opus 5 review: the model she found most exasperating produced the best work. Judge output, not bedside manner — and route accordingly.
Source: How I AI
AI operating model
The Review Swarm Is an Org Chart
A Notion engineer ships features without reading the first draft. The real move is how he structures review — slice by domain, fan out to specialists, loop.
Source: Every
AI & agents
The Self-Driving Company
Replit wired AI agents into every system it runs. Employees stopped doing the steps and started setting direction — the self-driving company.
Source: The AI Daily Brief
AI operating model
The Finance Guy Who Built the Close System
A non-engineer at OpenAI spent a month of evenings teaching an agent his hardest monthly process. The method, not the model, is the transferable part.
Source: Every / AI & I
AI operating model
The Prompt Took Ten Seconds. The Harness Took Months.
Every's team made $25,000 from four agent-drafted emails. The transferable part isn't the agent — it's the months of scaffolding behind the one-line prompt.
Source: Every / AI & I
AI engineering
Under-Prompting
A 25-item checklist makes a frontier model worse. One sentence makes it better — but only when the scaffolding underneath is already good.
Source: How I AI — Claire Vo
AI engineering
Your Agent Tests the Sad Path. You Never Did.
Claire Vo pointed Codex at her own onboarding flow and it found a blocking bug that had shipped months earlier. Humans always click the required field.
Source: How I AI
AI strategy
Is Kimi K3 Really Fable Class?
Kimi K3 is the best open model ever shipped and narrows the frontier gap to ~3 months. It also wins the demos and loses the real work — and ships with almost no guardrails.
Source: The AI Daily Brief — Is Kimi K3 Really Fable Class
Content strategy
AI Slop Is a Confession, Not a Model Failure
AI writes slop when you let it invent. Alex Lieberman's fix: interview yourself, shape your own words, and make employees your distribution.
Source: How I AI — Alex Lieberman on the AI content machine
Model routing
Models Now Have Design Taste — And Only One Took a Risk
Six models, one UI prompt: five converged, only GPT-5.6 took a risk. Why model choice is now a taste and risk-appetite decision.
Source: Every — GPT-5.6 vs Fable, Claude & Sonnet on design
Org design
Netflix's AI-Era Hire Is a Systems Thinker, Not a Specialist
Netflix's CPTO on the AI-era hire: systems thinkers over specialists, craft kept scarce, and AI fluency as a baseline on top of talent density.
Source: Lenny's Podcast — Elizabeth Stone (Netflix CPTO)
Product & engineering org design
Systems Thinker
Why Netflix now hires more systems thinkers than specialists in the AI era — abstract across domains to reusable building blocks so humans and agents ship fast.
Source: Elizabeth Stone (Netflix CPTO) — Lenny's Podcast
AI evals
The 46-CSV Test: How to Tell If a Model Can Be Trusted With Real Work
A power-user's real task — compile 46 CSVs from an email — sorts GPT-5.6, GPT-5.5, and Fable by agentic judgment, not benchmark scores.
Source: Every — GPT-5.6 vs 5.5: The 46-CSV Test
AI & agents / leadership
Backstopping vs Gatekeeping
When agents make features cheap to build, the leader's job flips from rationing the roadmap to backstopping what people already want to ship.
Source: I Vibecoded This Feature Using Codex — Every / AI & I
AI & agents
The Bottleneck Was Never Engineering Time
When anyone can ship a feature with an agent, the bottleneck becomes trust and guardrails, not engineering time. How Every rewired who gets to build.
Source: Every
AI risk & policy
Grounded AI Risk
AI-risk warnings now land by how grounded they are in what the tech does today — not the scariness of a hypothetical superintelligence.
Source: AI Optimism vs AI Pessimism — The AI Daily Brief
AI strategy
Own the Context, Not the Agent
Granola's CEO is betting a $1.5B company on the opposite of what most AI startups do: don't build the best agent, own the deepest context and let any agent plug in.
Source: AI & I (Every)
Product & engineering org design
Pirate and Architect
A staffing model for building AI-native products: a pirate vibe-codes fast to find the value, an architect turns the find into a system that scales.
Source: Granola's Chris Pedregal — AI & I / Every
AI strategy
The AI Doom Debate Just Grew Up
The AI-risk conversation is shifting from extinction fanfiction to grounded economics — and the warnings anchored to what the tech actually does are the ones that finally land.
Source: The AI Daily Brief
AI & work
Opportunity Technology vs Efficiency Technology
Point AI at work that was impossible before, not at shaving 20% off what you already do. The value is in the reinvestment, not the time saved.
Source: The AI Daily Brief — How to Help People Thrive with AI
AI strategy
The AI Wars Moved Past Models. Here's How That Benefits You.
AI competition jumped past models into hardware, geopolitics, and cost. In the chaos, a subsidy war hands you a deal — if you also own your stack.
Source: The AI Daily Brief — How the Escalating AI Wars Benefit You
AI & work
The Bottleneck Isn't the Model. It's Whether People Are Supported to Use It.
Better models don't create value on their own. Those who thrive point AI at work that was impossible before, not familiar work made faster.
Source: The AI Daily Brief — How to Help People Thrive with AI
AI interpretability
Anthropic Built a Tool to Read Claude's Private Thoughts
Anthropic found Claude keeps a small set of private, readable thoughts, and built the J-lens to see a model's hidden intentions before they surface.
Source: The AI Daily Brief
AI infrastructure
Local-First AI
Running AI on hardware you own isn't a cost play — it's a meter play. Own the machines and always-on intelligence stops costing per token.
Source: Local AI Models Explained — How I AI (Claire Vo & Alex Finn)
AI safety & oversight
Model Interpretability
Interpretability just went from explaining a model after the fact to reading — and training — the small workspace where it actually thinks.
Source: Anthropic Can Now Read Claude's Mind — The AI Daily Brief
Local AI
Why People Are Running AI Fleets at Home (It's Not About Saving Money)
Running local models rarely beats the cloud on cost. The real payoff is always-on, unmetered AI — and one hardware trade-off decides how you build it.
Source: How I AI
Future of work
The AI-Identity Workforce Split
AI cleaved the tech workforce in half — one side amplified, one side diminished. How you relate to AI now predicts your job sentiment more than role, level, or employer.
Source: How Tech Workers Are Feeling in 2026 — Noam Segal × Lenny Rachitsky
AI & work
The Tech Workforce Just Split in Two
A ~6,000-person survey found AI has split tech in half — half feel amplified, half destabilized — and that divide predicts job sentiment more than title does.
Source: Lenny's Podcast — Noam Segal
AI models
Four Models Dropped in a Week. The Story Is Cost, Not IQ.
Four AI models shipped in one week. The real shift isn't intelligence — it's cost, speed, and voice. Why to run a stack, not pick a winner.
Source: The AI Daily Brief
AI strategy
If China Bans Open Source, Your AI Cost Plan Breaks
China may restrict its frontier open-weight models. The durable hedge isn't a cheaper model — it's tuning a Western model and routing by risk.
Source: The AI Daily Brief
Model strategy
Practically Effective vs. Theoretically Intelligent
The smartest model isn't the best model for shipping. Two practitioner evals of GPT-5.6 Sol vs Fable 5 reach the same verdict.
Source: How I AI (Claire Vo) — GPT-5.6 Sol review
AI operating model
The First Model Reliable Enough to Run Your Work
Dan Shipper ran GPT-5.6 Sol for a month: not the smartest model, but the first fast and reliable enough to run loops of knowledge work.
Source: Every
AI evals
The Smartest Model Isn't the One That Ships
Claire Vo's product-work benchmark: GPT-5.6 Sol beats Fable 5 on what ships — practical effectiveness over raw precision — at half the price.
Source: How I AI
Product strategy
When Building Gets Cheap, Taste Gets Expensive
Adam Mosseri on why, when AI makes building cheap, the scarce skills move up the stack — taste, judgment, and strategy decide what to build.
Source: Lenny's Podcast
AI engineering
A Harness Is Just Code Around an Agent
Everyone says it's the harness, not the model. Here's what a harness actually is, and how Claire Vo built one on the Claude Agent SDK.
Source: How I AI
AI & jobs
AI's First Labor Shock Isn't Unemployment. It's Independence.
The early data on AI and jobs isn't mass layoffs. It's people leaving firms to work alone, and companies getting built smaller and leaner.
Source: The AI Daily Brief
AI at work
Build With AI, Protect the Part That's Yours
Writer Craig Mod uses AI to build and research, but never to write. A model for keeping AI's leverage without losing the work that's yours.
Source: Every — AI & I
AI strategy
The Month AI Stopped Being About the Model
June 2026 moved AI's real advantage from picking the best model to owning the cost, fallback, and learning loop around it. Here's what changed.
Source: The AI Daily Brief
AI & jobs
The Companies Spending Most on AI Are Hiring the Fastest
New firm-level data shows heavy AI adopters grew headcount about 10% while low adopters stayed flat. So far, the leaders are hiring more, not fewer.
Source: The AI Daily Brief
AI & agents
Agents as Employees
The skill that decides who succeeds with AI agents isn't coding — it's management. Role scoping, onboarding, progressive trust, and documentation hygiene transfer directly.
Source: Multiple sources
AI operating model
Stop Prompting Your Agents. Start Managing Them.
Run coding agents autonomously with OpenAI Symphony and a Linear board. The shift from prompting agents to managing them.
Source: How I AI — Alessio Fanelli
AI strategy
Fable 5 Is Back. Don't Waste It on Code.
Anthropic's Fable 5 is back for one cheap week. Its rarest skill isn't coding — it's strategy that doesn't cave when you push back.
Source: The AI Daily Brief
AI engineering
Model Routing
Route each task to the right model. A decision tree and your own benchmark beat defaulting to the smartest model — on quality and on cost.
Source: Multiple sources
AI engineering
Sycophancy Resistance
A model that holds a correct position under pushback is a thinking partner, not a mirror. The routing criterion leaderboards miss.
Source: Fable Is Back — The AI Daily Brief
AI economics
How Big Is the AI Economy, Really
The AI economy is a $175B annualized run rate growing 3x faster than any prior tech wave — and the numbers now say the buildout is paying its own way.
Source: The AI Daily Brief
AI operating model
Sculpting vs Gardening
AI flips knowledge work from shaping every output by hand to setting the conditions and letting the work grow. Build loops, not tasks — and know when to buy.
Source: Multiple sources
AI economics
State of the AI Economy
Is the AI buildout paying back or a bubble? A $175B run rate now clears its running costs — for now — while the subsidy era funding cheap inference ends.
Source: Multiple sources
AI operating models
Stop Sculpting, Start Gardening
How Every's head of consulting runs her whole practice on Codex by building loops, and how she decides when to buy the software instead of building it.
Source: AI & I / Every
AI evals
When the Model Judges and You Judge, You Disagree
Claire Vo built a taste-weighted model benchmark in Claude Code, and her human scores landed nearly opposite the LLM-as-judge scores.
Source: How I AIAI engineering
AI Evals
Evals are a product discovery discipline, not a testing one. Read traces first, cluster failures, then automate judges — and don't trust an LLM judge for taste.
Source: Multiple sources
AI strategy
Frontier AI Came Back — For a Vetted Few
The US now decides who gets frontier AI: ~100 orgs got Mythos back, GPT-5.6 shipped to a few partners. What it means for your AI stack.
Source: The AI Daily Brief — "Mythos Returns But Not For Everyone"
AI engineering
Disposable Code
When code is nearly free to write, the pull request is the spec — built, reviewed, then merged or trashed. The method behind Gusto's 10-week build.
Source: How Gusto's CTO uses Claude Code to ship like a startup — How I AI
Engineering leadership
Gusto's CTO Deleted the Process and Shipped a Product in 10 Weeks
How Gusto's CTO shipped a tier-one product in 10 weeks with five people by deleting docs, Figma, and Jira, and what's actually copyable.
Source: How I AI — Eddie Kim (Gusto)
Product strategy
When Building Is Free, Taste Is the Job
OpenAI Codex lead Andrew Ambrosino on why implementation is now cheap and taste is the scarce skill in product work.
Source: Lenny's Podcast — Andrew Ambrosino
AI strategy
Your AI Access Is Now a Permission, Not a Purchase
The US government is now deciding, case by case, which frontier AI models ship and who gets them, making access a permission rather than a purchase.
Source: The AI Daily Brief
AI & org design
AI Accountability
Clear ownership of AI decisions makes ROI ~3x more likely, strongest when the CEO owns it. AI is an org-design decision, not an IT one.
Source: CEO-Led AI Gets 3X the ROI — The AI Daily Brief
Enterprise AI
CEO-Led AI Gets 3x the ROI
KPMG's Q2 2026 survey: organizations with clear accountability for AI decisions are ~3x more likely to report ROI, and CEO ownership widens the gap.
Source: The AI Daily Brief — CEO-Led AI Gets 3X the ROI
AI at work
Claude Moves Into Slack, and the Job Changes
Claude Tag puts Claude inside Slack as a shared teammate, not a chatbot you visit. The feature is small; the five shifts it signals are not.
Source: The AI Daily Brief
AI & agents
Workplace-Native Agents
Claude Tag drops the agent into your team's Slack channel. The real shift is from app to workplace, and the hard part is trust, not capability.
Source: The AI Daily Brief
AI engineering
A $3 Coding Model Just Made the Frontier Tax Optional
An open-weight model did near-frontier coding and design for ~$3 a session — proof the frontier tax is now a routing choice, not a default.
Source: How I AI — Claire Vo
AI product strategy
Engagement vs Flourishing
Every AI product optimizes for engagement or for human flourishing. Delegation is the structural antidote to building a feed.
Source: Edwin Chen × Dan Shipper — Every / AI & I
Leadership & talent
Person vs. System: What Actually Drives Workplace Performance
How much of job performance is the person vs. their environment? The honest answer from the research, and why it changes how you lead.
Source: Multiple sources
Leadership & talent
Strength-Based Talent Evaluation
The dominant hiring model screens out red flags and destroys value. The fix: find the world-class strength, then configure around the gaps.
Source: Multiple sources
AI strategy
The Real Model Choice Isn't Smart vs Smarter. It's Engagement vs Flourishing.
Surge AI's Edwin Chen: the next failure isn't dumb models but smart ones optimized for engagement. The real choice is engagement vs flourishing.
Source: Every / AI & I — Dan Shipper × Edwin Chen
AI strategy
The Open Model That Didn't Fade
GLM 5.2 is the first Chinese open-weight model to hold up in real work instead of fading after the benchmark spike — and that breaks the assumption that frontier-class AI lives at two or three labs.
Source: The AI Daily Brief
AI engineering
The Revenge of the DevX Team
Mozilla found 271 latent Firefox security bugs in a month with AI — but the unlock was a simple harness atop a decade of fuzzing tooling, not a magic model.
Source: How I AI (Claire Vo)
AI strategy
The Week a Government Turned Off the Best Model
When a US export-control directive pushed Anthropic to suspend Fable 5 overnight, the real lesson was that building on a single frontier model is a single point of failure the state can pull.
Source: The AI Daily Brief
Engineering leadership
When Coding Stops Being the Bottleneck, This Is the Job
Anthropic's Fiona Fung on running a team that ships ~8x more code: when typing gets cheap, the leader's job becomes verification, ambition, and staying close to what ships.
Source: Lenny's Podcast
AI strategy
AI Learning System
Stop picking the best model; build a learning loop. The durable asset is the harness, private evals, and feedback traces you own — not the AI you rent.
Source: The AI Daily Brief — Your Company Doesn't Need an AI StrategyAI strategy
Your Company Doesn't Need an AI Strategy
Satya Nadella's argument that picking the best AI model is the wrong unit of strategy, and why the durable advantage is a private learning loop you own and can carry across models.
Source: The AI Daily Brief
AI operating model
Agent Loops
A concise operating frame for moving from babysat AI prompts to agent loops with structured input, verification, review, and memory.
Source: Every / Felix Rieseberg and How I AI / Claire Vo
AI adoption
AI Disclosure Penalty
A practical read on why honest AI use can still cost workplace status, and what leaders need to normalize instead.
Source: Atlassian Teamwork Lab / Conor Donegan
Person wiki
Mark Pincus
A concise read on the Zynga founder, his product religion, and why he treats AI as a failure machine.
Source: Lenny's Podcast with Mark Pincus
Product strategy
Proven, Better, New
Mark Pincus's hit-product framework: copy what already works, make one undeniable improvement, then test one new bet without worshiping novelty.
Source: Lenny's Podcast with Mark Pincus