Governance
Governance is not a compliance checklist. It is the specification of who is accountable when things go wrong, what controls check quality and risk, and which decisions require human oversight versus algorithmic autonomy. AI programmes collapse when C-suite, finance, and deployment teams measure success differently. Governance clarifies what "done" means and who owns it.
Essays
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The Frontier Is Jagged. Your Workflow Needn't Be.
A harness cannot erase the jagged frontier, but it can ground agents in fresh context, restrict their tools, and give people ownership of the exceptions.
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The Most Dangerous AI Is the One That Does Exactly What We Asked
Decision AI begins where the copilot metaphor breaks: when nobody is left to catch the model pleasing us.
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Done, Keys, and a Second Check
Copying the consumer 'agents want' form factor into the enterprise without ownership of done, keys, escalate or monitor rights, and a second check is not an operating model.
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From 100 Agents to Two Heroes
Broad agent experimentation is a phase. Without owners of big bets, change management, and adoption OKRs, you scale demos.
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Shared State, Not a Civilisation
What the OpenAI-Hugging Face agent incident actually means for enterprises deploying AI agents.
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What Karpathy Didn't Say About Your Enterprise AI Strategy - Part 1: The Diagnostic
Your enterprise AI rollout is probably sequenced wrong. Not because of the models. Because of the operating model.
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Your AI Programme Didn't Fail. Your Governance Did.
A CDO I spoke with recently put it this way: "The technology worked. The business case didn't. We still got cancelled."
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The AI Deal That Almost Closed, Until the CFO Walked In
Enterprise AI isn't failing because the technology doesn't work. It's failing because it was sold to CIOs and judged by CFOs.
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Part 2: The Enterprise Agentic AI Implementation Framework
From PoC to Production in Regulated Industries.
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The Accuracy Paradox: Why Enterprises Demand 100% from AI Agents While Tolerating 95% from Humans
What 1.5 million leaked API keys taught us about the PoC-to-production gap in regulated industries.
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Tools Are Not the Operating Model
Enterprises invest heavily in AI tools but see little transformation. The gap is not technological. It is structural. Without changes to roles, workflows, and decision rights, even the most powerful tools remain peripheral.