Practical thinking on AI context governance, multi-agent coordination, organisational learning, and the infrastructure shift happening right now.
AI agents have no persistent memory between sessions. Your organisation's hard-won knowledge never accumulates. This isn't a product limitation — it's a structural problem that requires infrastructure to fix.
Most enterprise AI is built for execution. Agent deliberation — where agents reason together and reach grounded conclusions — is the natural next stage and requires shared context to work.
The team that owns developer experience is the same team that should own the AI context layer. Publish once — every agent in the org works from the same ground truth.
Teams govern models, outputs, cost — but almost none govern the context layer that shapes all three. Here's the framework and why it matters now.
When outsourced developers use AI tools with access to your codebase, proprietary context leaks in ways most security frameworks haven't modelled.
MCP has become the most important enterprise AI infrastructure standard of 2025 — opportunity and governance risk, explained.
Engineering teams spend months refining system prompts. Most have no mechanism to protect them when shared with vendors.
Zero-trust for AI context — governing what gets injected into your AI tools — is a new and largely unaddressed security discipline.
New articles on governance, security, and AI infrastructure every two weeks. No noise.
No spam. Unsubscribe any time.