The full-stack PM: frameworks for product strategy and leadership

Executive overview

Most product managers think too narrowly — about features, their users, their backlog. The best PMs own outcomes across the full stack: users, marketing, engineering, leadership, and strategy.

Anuj Rathi, CPO at Jupiter Money and formerly SVP at Swiggy, shares a set of interlocking frameworks for how to build products, run strategy, and lead teams. The thread connecting all of them: explore divergent options, get concrete fast, and think like an influencer at every level.

Full-stack PMs who own outcomes across disciplines consistently outperform specialists who optimise only their own domain.

New users are lazy, vain, and selfish

• Users have already allocated their time — they are not looking for your product
• Lazy: blow their mind immediately or lose them
• Vain: they have existing habits; asking them to change is a big ask
• Selfish: show them what's in it for them before anything else
• Onboarding and copy matter more to product success than core feature work for loyal users
• Connect marketing message through to onboarding — the user's journey starts before they open the app
• Cross-selling fails when PMs don't empathise with users who found value in one thing and stopped there

Working backwards with three PR FAQs

• Amazon's working backwards process forces you to work from a full GTM picture, not just user value
• A press release surfaces disagreements early — on dates, goals, and alliances — before you've committed
• Always write three divergent PR FAQs, not one: forces genuine exploration, lets leadership compare and reject with reasoning
• FAQs can be tailored to the company context (e.g. compliance checks at a fintech, multi-sided impact at a marketplace)
• Always recommend one option — but present two alternatives so stakeholders can see what was considered and why it was rejected
• Once aligned, apply disagree-and-commit: no revisiting

Show, don't tell

• Rather than personas, use persons: a named individual with a specific situation, emotional state, and trigger for opening your app
• Walk through every pixel and line of copy in service of that exact person
• Build the full emotional journey, including waiting states, delays, and failure modes
• At the product leader level, create a full strategy-on-a-page: acquisition, activation, cross-pollination levers, membership — in three alternatives

The 4BB framework for product strategy

• Brilliant Basics: the foundation — tech health, platform investment, things the company is built on
• Bread and Butter: regular product backlog — bug fixes, improvements, experiments within existing lines
• Big Bets: cross-team initiatives requiring PR FAQ sign-off and collective commitment
• Breaking Bad: company redefinition — pivots, new categories, changing what the business is
• The allocation across these four is a product strategy conversation between head of product and CEO, not a PM prioritisation call
• Making trade-offs explicit (e.g. fewer bugs vs. a shot at changing the game) gives PMs clarity and alignment

PM skills and leadership diagnostics

• Three skills that define who should be in product: raw smarts (problem identification and solving), drive/grit (hardest to coach), and influence (non-negotiable)
• Being excited about getting better at influence matters more than already being good at it
• Three reasons things don't happen as a leader: can't do (capability), won't do (motivation/alignment), not set up to do (your org design problem)
• ~70–80% of execution failures are setup failures — not people failures
• Org design determines product architecture (Conway's Law runs both ways)

Building in three-sided marketplaces

• OKRs break in multi-sided marketplaces: levers on one side are not independent from the others
• Big Bets work better than OKRs in marketplaces — they force a complete story across all sides
• Stability across all sides is the prerequisite before deciding which side to optimise for
• Derive your focus from company vision (Amazon: customer-centric; Alibaba: seller-centric)
• A/B experiments produce misleading results in marketplaces due to network effects between variants

Contrarian opinions on product craft

• Speed vs. excellence: if forced to choose, choose excellence — most experiments that fail could have been killed as thought experiments
• Most product ideas don't need to be tested; smart people thinking harder would reject them before building
• Think more and ship better; speed is the default pressure but rarely the right call