domain

product

94 cards · 59 operators · 54 tier-A claims · 13 synthesis patterns.

Strongest claims

1. Optimise for absolute count of users reaching each stage, not stage conversion rates Archie Abrams
2. Agents are first-class product users; design for output reliability, not navigation Elena Verna
3. Agents work when treated as a team, not a single super-tool Claire Vo
4. An intake interview guide aligns PM and PMM before any GTM work begins. Ashley Bass
5. When the agent isn't doing what you want, fix the context, not the model Sherwin Wu
6. Build for the model six months out, not the one that ships today Boris Cherny

Adjacent domains

• ai-native · 39 co-occurrences
• leadership · 25 co-occurrences
• pmm · 20 co-occurrences
• gtm · 16 co-occurrences
• growth-demand · 14 co-occurrences
• engineering · 12 co-occurrences
• design-ux · 8 co-occurrences
• growth · 6 co-occurrences

Synthesis patterns in product

• Agents are first-class users, design for output, not navigation
• Agents mapped 1:1 to JTBD with named human checkpoints
• Pricing is a behavioral-architecture problem
• Build for the next model, not the current one
• Diagnose before executing, refuse the playbook ask
• Generalists with taste, shipping end-to-end
• LLM-as-OS, post-training as moat
• Absolute counts + correlated short signals, not stage rates and long loops
• Pricing is the most leveraged and most under-invested function
• Quality and friction-as-feature are growth levers, not constraints
• Research preview, frontier programs, seasons not roadmaps
• Status quo / no-decision is the real competitor
• Subtraction-first operating discipline

94 insights in product

• Optimise for absolute count of users reaching each stage, not stage conversion rates · Archie Abrams
• Agents are first-class product users; design for output reliability, not navigation · Elena Verna
• Agents work when treated as a team, not a single super-tool · Claire Vo
• The number one enemy of innovation is efficiency, AI is collapsing the moats specialization built · Leah Tharin
• Exploring and understanding complex systems · Anirudh Rayaprolu
• An intake interview guide aligns PM and PMM before any GTM work begins. · Ashley Bass
• Appoint one trusted-taste expert as the eval benevolent dictator, committees stall the loop · Hamel Husain
• When the agent isn't doing what you want, fix the context, not the model · Sherwin Wu
• Build for the model six months out, not the one that ships today · Boris Cherny
• Build for the model six months out, the current model will eat your scaffolding · Sherwin Wu
• Build products at the edge of what does not yet work · Cat Wu
• In AI products, capability overhang is the central growth problem · Amole Naik
• Continuous Calibration, Continuous Development (CCCD) is the operating loop for AI products · Aishwarya Naresh Reganti
• Code and media are the only forms of leverage that don't require asking, labour and capital both come gated · Naval Ravikant
• -> Context on pain points and product: what and who are we solving for, and how · Shivangi Sahu
• The block to AI adoption is the start, not the depth, design 30-day ladders, not deep-dive bootcamps · Hilary Gridley
• PMM role at Amilia: end-to-end GTM, deep customer insights, and product collaboration · Cris Thome
• Make design an explicit ship-blocking bottleneck · Evan Spiegel
• The design role's time mix shifted from 60% mocking to 30% mocking, 30% pairing, 20% code · Jenny Wen
• Done-for-you for the strategy, done-with-you and DIY for the rest, never sell time · Alex Hormozi
• Differentiation requires three checks: different, better, and matters viscerally to users · Ayo Omojola
• Test automation that can't adapt to product changes creates a maintenance burden worse than manual testing. · Dileep Krishna
• Customer loyalty in service contexts is driven by effort reduction, not delight, exceeding expectations doesn't build loyalty · Matt Dixon
• Give the model tools and a goal; do not hard-code the workflow · Boris Cherny
• Treat `.claude/` as a deployable artifact with versioning and rollback · Pawel Huryn
• Hire engineers with product taste rather than adding more PMs · Cat Wu
• In PLG, no pricing model can save you if onboarding doesn't reach the Eureka moment quickly · Ramli John
• Evals are systematic data analysis on your LLM application, start with error analysis, not tests · Hamel Husain
• Don't test what won't reach sample size in a month, pre/post is fine · Elena Verna
• Sort the roadmap into four buckets, Brilliant Basics, Bread-and-Butter, Big Bets, Breaking Bad · Anuj Rathi
• Run a Frontier cohort, early-adopter access to bleeding-edge features, in parallel with normal rollout · Aparna Chennapragada
• In an AI-native team, hire generalists with one deep dimension, not specialists · Anton Osika
• Push past expert opinion until you reach the actual law of physics or contract · Ayo Omojola
• People don't want the mathematically optimal strategy, they want one that lets them sleep at night. Reasonable beats rational in practice. · Morgan Housel
• Watch for "illegible energy", ideas the team can't articulate but can't stop talking about · Jenny Wen
• Treat upward influence as a discovery interview, not a sales pitch · Jessica Fain
• Position AI as intelligence put into things that already exist, not as a new thing · Qasar Younis
• Map agents 1:1 to enumerated jobs-to-be-done, not abstractly to "AI-augmented" workflows · Evan Spiegel
• JTBD interviews surface the customer's actual language and the switch trigger · Bob Moesta
• Killing your own initiatives loudly is the highest-trust move with executives · Jessica Fain
• Label every strong opinion with a confidence level so the room knows when to push back · Mihika Kapoor
• Latent demand, what users hack around the product to get, is the next loop · Boris Cherny
• Growth needs both lead bullets and cannonballs, the laziness trap is shipping only lead bullets · Adriel Frederick
• LLM platform is the new OS, agents are the new apps, MCP registries are the new app stores · Mark Petty
• 30–40% of growth experiments with short-term lift show no incremental value at one year · Archie Abrams
• Losses feel about 2× as painful as equivalent gains, switching costs are paid in pain, not dollars · Daniel Kahneman
• By 2028, AI agent "machine customers" will replace 20% of human-readable storefront interactions · Gartner
• Design for the marginal user, the person on the cusp of converting in the worst conditions · Adriel Frederick
• Tool adoption should not be conflated with value delivery. · Mark Kosoglow
• Customer data is not a defensible moat for GTM tech companies. · Mark Kosoglow
• PMM owns both halves of the loop, market to the product, product to the market · Martina Lauchengco
• Pre-PMF, stop theorizing marketplace dynamics, pick the hardest side and nail liquidity · Benjamin Lauzier
• • You'll be misunderstood by the exact people you are fighting for · Ani Filipova
• Most people are still using AI like this: ask → answer → forget · Alok Yadav
• Natural language is the interface; conversation flow is the design surface · Aparna Chennapragada
• Design for the otaku, the obsessive customer who already wants what you make and will tell their hive · Seth Godin
• Pitch a vision as pain → solution → proof, interleaved per beat, not three sequential acts · Mihika Kapoor
• Find the Pattern of Pain, and don't rush past it. Most teams fail by not digging deep enough. · Hiten Shah
• The planning fallacy guarantees every launch timeline is optimistic, the fix is the outside view · Daniel Kahneman
• AI raises the bar for PMs, tactical work is delegatable; judgment, taste, and customer empathy become more valuable · Lenny Rachitsky