AI & Coding
AI coding, coding agents, models, skills, and intelligent developer workflows
Technical Blog
Practical notes on automation, deployment, and developer workflows
Right now the site is grounded in three solid tracks: Docker and server deployment, Git workflow habits, and Markdown-driven publishing pipelines. AI automation content will expand on top of that, so the homepage now pushes topic hubs and flagship posts first instead of acting like a plain feed.
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Claude Code and Codex API Access: 3 Routes Compared on Cost and Setup
For indie developers and small teams: self-hosted CLIProxyAPI vs OpenRouter relay vs official APIs — real cost structures, setup friction, and data paths, matched to your usage.
Diffle's Text Anchors: Where Do Review Comments Go After a Coding Agent Rewrites the Code?
An analysis of Diffle 0.2.4 comment relocation, four independent Node.js synthetic cases, duplicate-text ambiguity and GitHub Pending Review boundaries.
Can Coding Agents Save Tokens by Remembering Past Edits? Inside Singularity's Cue Matching
An inspection of Singularity's pinned workflow-memory code and five synthetic Node.js cases, including false recalls, stale paths and the limits of reported token savings.
Claude Code Logs Too Long? Testing Context Diet's Error Limits
A source audit and synthetic Node.js tests of Context Diet v0.3.0: why bounded digests omit errors, how to recover raw logs, and what dry/capture actually change.
How Do You Choose a Coding Agent Model? I Compared SelfBench Across 9 Real Repositories
Public coding-agent leaderboards may not represent your codebase. I analyzed nine SelfBench repositories to compare ranking shifts, cost, small-sample uncertainty, and hidden-test quality.
Are AI-Generated Tests Reliable? Using Mutation Testing to Check Coding Agent Tests
A green test suite and 100% coverage can still miss boundary bugs. I ran a first-party mutation-testing A/B fixture to see what survivors reveal and what the extra gate costs.
What Is AI Agent Orchestration? The Hard Part Is Shared State and Handoffs
Once Codex, Claude Code, and other agents work on the same system, task routing is not enough. This post explains ownership, handoffs, receipts, capability boundaries, and replayable coordination state.
Muse.ai Signup Stuck? How I Completed It with ChatGPT Work
When Muse.ai signup behaved poorly in my local browser, I opened the site in ChatGPT Work's cloud browser, took over at the page, and completed registration there.
When CLAUDE.md Gets Too Big: Rethinking AGENTS.md, Skills, and CI
Starting from a real 760-line CLAUDE.md migration, I re-measured what changed after splitting AGENTS.md, Skills, and CI into clearer ownership layers.
New Codex Model Not Showing? Sync the Official Catalog and Sub2API
When a new Codex model exists upstream but does not appear locally, this workflow checks the official models.json, local catalog, minimal_client_version, Sub2API allowlists, and model passthrough in order.
What the Claude Code Source Leak Teaches About Prompts, Safety Gates, and Memory
This post is less about the leak drama itself and more about what public analyses of Claude Code reveal about prompt architecture, safety boundaries, memory design, and why AI coding tools are now competing on much more than model quality.
What Changed in the New Codex: Why It Feels More Like a Dev Environment
If your mental model of Codex is still the early cloud coding agent, this post explains why the newer Codex feels much closer to a real developer workflow.