CATEGORY
AI / Agent
2026-10 6 posts
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How Managed Agents Takes an Agent Apart: Brain, Hands, and Session
The design reasoning behind Anthropic splitting an agent into a session, a harness, and a sandbox, and what happens when you run all four parts of the official workshop repository: custom tools, multi-agent, memory, and file output
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Model Providers Are Taking Over the Agent Runtime: Managed Agents and the OpenAI Agents API
What Anthropic Managed Agents and the OpenAI Agents API add to each provider's lineup, how the two runtime APIs converged on the same abstractions, a run of the same task on both, and a comparison with local harnesses and cloud coding products
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In the Agent Era, the Scope a Specialist Software Supplier Can Choose
Part 4 of 4: lock agent features in one dedicated agent, or expose them as tools and work assets any worker can use? It shapes what a supplier can sell.
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Seeds and Germination: Software That Evolves in the Field
Part 3 of 4: fitting a product to each customer site with people and agents, building runtime adaptation into it, and feeding field experience back.
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Every Organization Needs an Agent Runtime
Part 2 of 4: why even air-gapped organizations will run a general-purpose agent runtime on work PCs, and how to connect it to internal models and tools.
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Separating the Worker from the Tool
Part 1 of 4: work spans products, so general-purpose agents become workers and products their tools. What to expose, and where software keeps its value.
2026-09 2 posts
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Can tgrep, CodeGraph, Mantic, or ripwire Replace ripgrep?
tgrep, CodeGraph, Mantic, and ripwire vs ripgrep on eight repos. Each hinges on a different variable: query, language coverage, file names, or phrasing.
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ego-browser and Aside Fail Differently
Same missions, two browser agents: ego-browser isolates its tabs and returned success on missed clicks; Aside works in your real tabs and threw errors.
2026-07 1 post
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Wiring codex to a Local Qwen — ollama, vLLM, and the developer role
Point codex CLI at a local model on ollama or vLLM. ollama needs one config.toml; vLLM rejects the developer role, fixed by a template patch or a proxy.
2026-05 9 posts
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Requirements as Latent State
A requirement is a latent state and the user's sentence a noisy observation. What follows for EARS, spec-driven development, harnesses, and when to ask.
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Skill and Harness
A skill compresses how to behave; a harness organizes how to tell if that behavior nears the goal. Why the two still contain each other in practice.
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Harness as Environment
A vector DB full of experience does not make an agent adapt. That takes a harness: what may change, how success is judged, how far a failure rolls back.
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Memory as Adaptation
Long-running agents need more than a RAG store: why memory split into working, episodic, semantic, and procedural layers that ground policy adaptation.
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Weights, Prompts, Codes as Parameters
If agent problems are POMDPs, weights, prompts, and code are parameters at three layers of one policy space. Why the layers opened in that order.
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Sharing Claude Code Sessions via Symlinked .jsonl
Resume the same Claude Code session across accounts by pointing every projects directory at one shared physical path
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Codex App Server Python SDK — JSON-RPC v2 over stdio
A Python SDK over the codex app-server stdio interface — install, first call, thread model, main methods
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Running Multiple Claude Code Accounts on One Machine
Run isolated Claude Code accounts on the same Mac with one env var and a small zsh function
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Claude Code Settings Sync and Troubleshooting
Sync matrix, migration steps, common failures, and diagnostic commands for running multiple Claude Code accounts on one machine
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