Practical AI for Production
Field notes on agent security, workflow automation, and what it takes to deploy AI systems that hold up under real business pressure.
Nobody Funded Them. Nobody Knew Their Names. They Still Won.
40 open-source projects broke out in 2025 and 2026 with no funding and no famous founders. The strongest pattern: they cut scope down to one action before anything else. Includes a downloadable audit.
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Fortnite as a Training Ground: What General Intuition's $2.3B Bet Means for Your AI Agents
General Intuition raised $2.3B to train AI agents on video game data. What the underlying logic means for every business deploying automation today.
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AI Doesn't Need More Policy. It Needs a Human Layer.
Most companies think AI governance means policies and docs. The real gap is operational — who reviews, who sets thresholds, who can stop the system.
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The Asimov Problem: When Your Team Stopped Auditing the AI Without Noticing
Most production AI deployments cannot answer four basic audit questions. On the audit gap — and why teams notice only after something goes wrong.
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What Agent-Level Audit Trails Actually Look Like in Production
Most AI agents can tell you what they did. Very few can tell you why, under whose authority, and with what data. A practical breakdown of production-grade decision tracing.
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