eval-driven development
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AI Product Data Security: A Practical Playbook for PMs
A practical playbook for mapping AI data flows, assigning risk, selecting vendors, and embedding security controls without blocking delivery.
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AI Product Validation: From Promising Demo to Proven Value
A practical evidence ladder for validating AI demand, model quality, user value, safety, and unit economics before expanding production exposure.
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The AI PM One-Pager: Radical prototyping requirements for speed, clarity, and truth
A single one-pager can transform how AI product teams move from idea to insight. By prompting tools directly and defining eval-driven criteria up front, I cut…
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Unleashing Inbound Sales with AI: My Playbook for Launching and Scaling Sales Agents Fast
Inbound sales shouldn’t wait in queues, and AI finally gives us a way to act on buyer intent in real time. The Sales Agent Blueprint is…
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Build an AI Toolbox That Improves Product Management
A practical operating model for choosing AI tools, grounding them in product evidence, measuring workflow gains, and scaling with clear guardrails.
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How to Build Agentic AI for Product Analytics and Support
A practical model for connecting behavioral data, safe agent actions, and outcome measurement so product support resolves issues without losing control.
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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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AI-Native Startup Execution: A Practical Operating System
A practical operating model for choosing the wedge, focusing the ICP, designing the team, and turning model-quality evidence into customer outcomes.
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From Brain Dump to Done: How Todoist’s Ramble Captures Tasks in Real Time with AI
Ramble turns stream-of-consciousness voice notes into structured tasks in real time by skipping transcription and using a Gemini live audio model. The Doist team pairs instant…
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How to Build a Trusted AI Product Platform That Scales
A practical operating model for building AI platforms that earn trust through governed data, verifiable outputs, controlled actions, and measurable outcomes.
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How We Taught Agentic AI to Speak Product Analytics—and Unlocked Actionable Insights
I describe how we taught agentic AI to understand the nuanced language of product analytics and deliver trustworthy answers grounded in our metric catalog and event…
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Stop Drowning in Tasks: How AI Marketing Agents Restore Focus and Maximize Impact
Marketers don’t have a volume problem—they have a focus problem. AI multiplies effort, but without outcome clarity it only accelerates busywork. I outline a practical playbook:…
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Stop Forcing AI to Prove ROI: A Product Leader’s Playbook to Measure Real Business Value
AI ROI isn’t elusive—it’s mismeasured. I outline a practical playbook that ties leading indicators to revenue, cost, and risk through a clear driver tree and disciplined…
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Never Stop Disrupting: Why the Fin API Platform Signals a New Era for Agentic AI
Disruption favors teams that move from features to agents—and the Fin API platform accelerates that shift. With a customer agent platform resolving over 2M issues weekly…
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Inside Banani: How a Canvas-First AI Designer Elevates UX and Accelerates Product Teams
Banani’s canvas-first AI designer reframes how teams access high-quality UX by generating design—not just code. I break down how the team handles parallel edits, per-screen context…
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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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Product Experimentation for AI Systems: A Practical Playbook
A practical playbook for testing prompts, retrieval, and policy changes with decision-ready metrics, safe rollouts, and reliable instrumentation.
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Apex Arrives: Vertical AI That Beats GPT-5.4 on Customer Service Speed, Accuracy, and Cost
Apex is a new vertical model for Fin that outperforms GPT-5.4 and Opus 4.5 on speed, accuracy, and cost—now powering ~100% of English chat and email…
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How to Scale AI Customer Experience Without Losing Quality
Build an AI CX quality system that combines risk-based monitoring, explicit scorecards, human review, and a closed product improvement loop.
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How to Ship Responsible AI Products in Regulated Healthcare
A practical delivery model that turns healthcare AI data boundaries, evaluation, staged rollout, and production monitoring into release decisions.
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Browse topics
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