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How to Design an AI-Enabled Product Engineering Workflow
A practical model for connecting evidence, AI, engineering, evaluation, and release controls without turning faster code into faster mistakes.
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How to Build a Production-Ready AI Coding Workflow
A practical operating model for turning AI-generated patches into scoped, reviewable, tested, and reversible changes your engineering team can ship.
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How to Build Product Verification Loops for AI Software Factories
A practical operating model for linking factory tests and AI evals to post-ship evidence, product decisions, and compounding learning.
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Why Product Engineers Are Transforming Software Delivery: Ownership, Speed, and Real Impact
Product engineers blend coding with customer insight, owning problems end to end and eliminating costly handoffs. By pairing continuous discovery with CI/CD, they shorten feedback loops…
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A Layered Playbook for Package Supply Chain Security
A practical framework for reducing package risk through delayed adoption, script controls, provenance checks, dependency pinning, and AI guardrails.
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Reusable AI Agent Workflows Need Evaluation Contracts
A practical model for packaging agent skills with traces, test fixtures, guardrails, and product metrics so reuse does not weaken accountability.
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Built for Your Biggest Days: How We Engineer Fair, Reliable Scale Without Downtime
Enterprise teams ask sharper questions about scale—and they should. I share how we handle 150k+ requests/sec, shard our source-of-truth data with Vitess and PlanetScale, and reshape…
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Developer-First Amplitude Instrumentation You Can Trust
A practical workflow for making Amplitude events reviewable, testable, and trustworthy from tracking-plan design through production monitoring and repair.
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Auditable AI Code Review: A Practical Operating Model
A practical operating model for AI code review that makes approvals explainable, limits autonomy by risk, and improves through production evidence.
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How to Build Cost-Effective PR Review Agents In-House
A practical blueprint for building an in-house PR review agent that controls model spend, limits false positives, and improves review flow.
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12 Game-Changing Updates to Fin Procedures & Simulations for Complex Queries
I’m announcing 12 major upgrades to Fin’s Procedures and Simulations that help teams safely scale agentic AI for complex, multi-step customer workflows. Build Procedures faster with…
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AI Agent Deployment Mastery: My Proven Checklist to Ship Safely, Faster, and at Scale
AI agents demand a higher bar for safety, observability, and measurable outcomes. In this first-person playbook, I share the proven checklist I use to deploy agentic…
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Reliable AI Infrastructure: A Product Leader’s Playbook
A practical framework for exposing silent AI failures, hardening runtime paths, controlling releases, and turning SLOs into product decisions.
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The Safety of Speed: 180 Deploys a Day, 12‑Minute Releases, 99.8%+ Availability
Speed and safety are not opposites—they reinforce each other when you ship in small, frequent batches. By automating our pipeline end-to-end, we move from merge to…
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My Proven Experimentation Playbook for AI PMs: Faster Learning, Safer Launches, Bigger Wins
Experimentation is not guesswork—it’s a disciplined system. In this playbook, I show how to pair A/B testing with eval-driven development to ship safer AI features and…
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Inside the Engine Room: How I Drive Scalable Analytics APIs, Reliability, and Performance
I share how I focus on the middleware and compute systems that power analytics at scale so teams can trust their data. I detail how overseeing…
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AI-Ready Data Governance: A Practical Trust Framework
A practical operating model to trace AI inputs, enforce access, automate quality controls, and prove trust without slowing delivery.
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AI Won’t Replace Engineers—Engineers Using AI Will: A Practical Playbook for Your Next Move
AI is automating tasks, not eliminating software engineers. The real opportunity is to shift from rote implementation to systems thinking, product discovery, and responsible AI Strategy.…
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Reliable AI Product Systems: A Product Leader’s Playbook
A practical operating model for defining reliability, designing bounded AI workflows, building evals, and controlling releases in production at scale.
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Browse topics
- AI Strategy (315)
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