OPERATING NOTES
Practical thinking for founders, operators, and product teams turning strategy into shipped systems.
Operating Notes
Agent skills are not valuable because markdown is easy to edit. They matter when macro-evals turn repeated agent failures into operating memory.
Operating Notes
AI is changing the economics of software company-building. The model layer may become utility, while workflow infrastructure lets serious teams build multiple vertical bets from one operating layer.
Operating Notes
Tobi Lütke’s River argument shows why public AI agent work matters for product teams: visible reasoning, shared memory, faster judgement, and fewer private execution bubbles.
Operating Notes
Agentic AI creates leverage only when companies redesign context, workflows, permissions, evals, governance and team structures. Headcount-first AI transformation makes broken operating models more fragile.
Operating Notes
AI is stripping product management down to its real value: turning customer signal into coherent systems before fast execution becomes a feature factory.
Operating Notes
Why applied AI systems need ownership, evaluation, human review, and quality bars before automation creates durable operational leverage.
Operating Notes
Lessons from hands-on mobile app building across React Native, Expo, onboarding, tracking, paywalls, release cycles, and early growth loops.
Operating Notes
How event design, CRM logic, dashboards, funnel visibility, and acquisition feedback loops improve product and growth decisions before scale compounds the wrong behaviour.
Operating Notes
A practical argument for treating internal tooling as serious product work, especially when workflow design, automation, QA, and decision quality affect commercial output.
Operating Notes
A practical view of technical product management in AI-heavy teams: workflow design, evaluation, implementation trade-offs, instrumentation, and delivery quality.
