The Strongest Agent Control Is Reversibility
Approval protects the moment of action. Reversibility protects what happens after. Classify agent work by whether you can undo it, and review earns a real target.
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Articles about governance and its practical role in production agent work.
How to Audit an AI Agent Routing Decision
When an agent takes a shortcut, operators should not have to guess why. A useful receipt explains the decision in plain language.
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Build a Governed LangChain Agent with Punk
A production agent needs more than a useful answer. It needs explicit execution boundaries, approval before consequential work, and evidence that survives the run.
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How Punk Brings Governed AI Agents Into Buzz Communities
A message can request agent work without being allowed to invent the user, channel, permissions, or actions behind that work.
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How Punk Governs the OpenAI Responses API for Coding Agents
Coding agents need more than text streaming. They need a runtime that preserves typed tools, reasoning summaries, terminal states, and evidence end to end.
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How to Run Claude Code Through Punk as a Governed AI Gateway
Claude stays the developer interface while Punk adds a governed model path and optional runtime tools underneath it.
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How to Run Codex Through Punk Without Replacing the Codex Harness
Keep the coding experience your engineers know while adding governed model routing, evidence, cost controls, and safer optimization underneath it.
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The Agent Stack Needs Three Contracts
Intelligence is becoming abundant. The scarce infrastructure is the layer that makes perception, authority, and adaptation inspectable.
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What Is Punk Chorus? Governed Multi-Model Reasoning With Receipts
A harder question should not automatically trigger an expensive model panel. Chorus spends selectively, verifies claims, and records why an answer was allowed to leave.
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Your AI Agent Pilot Needs an Evidence Budget
The hidden cost of an agent pilot is not inference. It is the work required to know whether the system deserves more authority.
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How to Give AI Agents Autonomy Without Losing Control
The choice is not full autonomy or manual control. Good operations give agents freedom inside clear, observable, consequence-aware boundaries.
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