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Giving everyone a LLM no more replaces engineers, than giving everyone a saw replaces carpenters.
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The AI-native developer is not the engineer who ships the most. It is the engineer whose system still tells the truth about itself after the model has been working on it for six months.
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The danger is not that agents are wrong. The danger is that they are right often enough, that we stop verifying their gaps.
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Compared to code a specification is a higher level of ambiguity, not a higher level of abstraction.
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We stop participating meaningful in the progress of a subject when we stop being able to think fluently about it.
Agent’s Playbook:
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Specs constrain intent.
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Plans constrain approach.
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Tasks constrain sequencing.
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Tests, schemas, linter constrain behavior.
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Harnesses constrain execution.
My Tools:
- bkmr: Knowledge Management for Humans and Agents.
- twagent: Define your agents configuration canonically in TOML. Compile agent-specific artifacts for Claude Code, Copilot CLI, IntelliJ, and pi. No duplication. Handles instructions, skills, subagents and MCP configurations.
- twmux: Race-condition-safe tmux wrapper giving LLM agents reliable shell I/O, a consistent JSON contract, and socket isolation.
- twsrt: Translates one canonical set of security rules into agent-specific permission configs for Claude Code, Copilot CLI, and others — single source of truth, no drift.
- mmdlint: Mermaid linter, ideal for agent usage in sandbox where mmdc does not work.
- pi-extensions: Adds sandboxing, access control, and vim editing to the pi coding agent.