
Knowledge as Code: The Memory File Just Got a Spec
Google's Open Knowledge Format: a one-page spec for the LLM wiki. Markdown, one required field, git. Why knowledge as code is your agent loop's missing layer.

Google's Open Knowledge Format: a one-page spec for the LLM wiki. Markdown, one required field, git. Why knowledge as code is your agent loop's missing layer.

The unit of work moved from the prompt to the loop. The five pieces of loop engineering, the memory that makes it compound, and what it won't do for you.

In a large codebase, the model is the smaller variable. The harness around it does the work: CLAUDE.md, hooks, skills, LSP, MCP, subagents.

A year ago, building an AI agent meant frameworks, RAG, and glue code. The Claude Agent SDK, Codex SDK, and skills replaced most of that middle layer.

Developers are shipping AI agents to production. Your Pulumi platform already supplies the seven things those agents need to be governed.

Three frameworks for AI coding agents compared: Superpowers enforces TDD, GSD prevents context rot, and GSTACK adds role-based governance.

We benchmarked Terraform HCL and Pulumi TypeScript across two LLMs. HCL uses fewer tokens, but Pulumi's total pipeline cost is 41% lower.
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