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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 Product Leaders Should Evaluate Emerging AI Tools
A practical framework for choosing, testing, and governing emerging AI tools without turning promising demos into unmanaged workflow clutter.
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How Snapbar Turned Crisis Into an AI-Native Photo Experience Revolution
Snapbar’s reinvention shows how a mature company can turn crisis into a durable AI product strategy. The company moved from physical photo booths to a WebRTC-based…
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Reliable AI Coding Requires Four Kinds of Control
A practical framework for controlling requirements, context, verification, permissions, and recovery when teams build software with AI agents.
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From AI Builder to Agent Swarm: A Product Delivery Model
A practical model for combining AI Builders, selective agent parallelism, evaluations, and release controls across product discovery and delivery.
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Package Hack Wake-Up Call: My Playbook for Securing Cowork, Coding Agents, and Secrets
A recent wave of malicious package hacks pushed me to level up my security posture without slowing down my AI workflows. In this piece, I break…
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Beyond the Product Builder Hype: How AI, org design, and joy shape PM success
Is the product builder wave a mandate or a useful tool? I unpack how to use coding and AI in product management without causing organizational chaos.…
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Vibe Coding Unleashed: How Parallel Agents Build KPI Driver Trees in Under Two Hours
Parallel agents are transforming how I build analytics artifacts and make product decisions. By running specialized agents in parallel—metrics, data modeling, research synthesis, prototyping, and evaluation—I…
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