Read the Why-Line Before You Trust the Org Policy
An Organization policy line on /status can explain a miss. It does not prove the fleet policy loaded. Read claude doctor, name the proxy owner, then resume coding.
Shinjae Kang
ReadAi-Agents
11 posts
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Shinjae Kang
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I Do Not Let a Coding Agent Pick Its Own Model
The agent that writes the diff does not choose the model for that pull request. A named human pins the model before the session starts. Auto is a vendor default, not an owner.
Shinjae Kang
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Your Coding Agent Needs a Map, Not a Bigger Context Window — Part 2
A bigger context window still lets a coding agent search the whole tree. Put the map file on the ticket as an allow-list, fail out-of-map paths, and name who updates the list.
Shinjae Kang
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Parallel AI Agents on a Shared Checkout — The Lease Contract You Need
Running multiple coding agents on one Git working tree without a lease contract is a merge race, not parallelism. Here's the isolation and ownership pattern that prevents silent corruption.
Shinjae Kang
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The Schema Change an AI Coding Agent Cannot Safely Guess
A generated migration that runs locally is not a production contract. Before an AI coding agent rewrites columns, require expand steps, dual-read boundaries, backfill evidence, worker compatibility, and an explicit rollback decision.
Shinjae Kang
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AI Agent Frameworks in 2026 — What the Comparison Charts Don't Tell You
A production evaluation guide for LangGraph, AutoGen, CrewAI, and LangChain: define state, proof, rollback, and maintenance exit criteria before an agent framework reaches a real SaaS workflow.
Shinjae Kang
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Grok 4.5 Is a Coding-Agent Moment Only If It Survives the Harness
Grok 4.5 is now available on the xAI API with pricing and reasoning controls that make developers pay attention. The real adoption test is whether it survives your local coding-agent harness.
Shinjae Kang
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Wrangler Now Treats AI-Agent Static Deploys Differently: Verify the Target, Not Just Success
Wrangler 4.108.0 added a quiet branch for agent-driven static Pages deploys. The operational lesson is simple: an AI deployment is not complete until the target platform, URL, resource ownership, and rollback path are verified.
Shinjae Kang
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A Repeatable Review Harness for AI-Generated Code After the First Merge Gate
The first merge gate catches obvious AI coding mistakes. A repeatable review harness catches the slower failures: drift, missing rollback paths, weak tests, and agent changes that look fine until production maintenance begins.
Shinjae Kang
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The Agent Edit Contract I Use Before a Coding Agent Touches a Repo
A practical contract for giving coding agents repository context, edit boundaries, verification steps, and rollback paths before they touch code.
Shinjae Kang
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Long-Running AI Agents — From Demos to Production
A long-running coding agent can stay green after it changes directory. Production still needs a sandbox that survives /cd, a budget that counts nested work, and a human who owns both.
Shinjae Kang
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