Tooling

48 posts
Nobody learned a city from a map

Nobody learned a city from a map

The fastest way to learn agentic development is to stop studying it: move in, extract repeatable patterns into skills, and reflect to compound.

Hosting shared document services - WOPI

Hosting shared document services - WOPI

Ever wanted to build your own Google Docs-style document service? This post introduces WOPI, the open protocol that lets web applications embed Office document editing directly in the browser, while keeping your app in control of storage and permissions.

From opt in to default

From opt in to default

Developers don't skip standards because they're careless, they skip them because there are fifteen things to remember and the code was the hard part. The real question isn't which tasks your LLM handles well. It's what's still slipping through ungated.

Three Claudes walk into a codebase

Three Claudes walk into a codebase

The machines aren't replacing developers, they're promoting them. You're no longer just writing code; you're managing agents, reviewing output, and setting standards. Three Claudes walk into a codebase, and suddenly you're a manager.

Running multiple Claude accounts without logging out

Running multiple Claude accounts without logging out

Managing multiple Claude Code accounts across machines gets messy fast. Jean-Claude keeps the useful parts in sync, separates account-specific config, and makes switching between personal, team, and client setups far less painful.

Technical debt lost its excuse

Technical debt lost its excuse

Technical debt used to justify meetings, trade-offs, and dedicated sprints. AI has changed that. Cleanup is now fast, cheap, and continuous. Teams that stop debating and start fixing unlock faster delivery and better outcomes.

Conductor: running multiple AI coding agents in parallel

Conductor: running multiple AI coding agents in parallel

Conductor by Melty Labs makes parallel agent workflows practical by running multiple agents with separate tasks simultaneously. The trade-offs are real but manageable, and this is where development is heading.

I'm using my engineering colleagues as my personal agents

I'm using my engineering colleagues as my personal agents

A couple of months ago, I was copy-pasting prompts into ChatGPT. Now I'm shipping features, running tests, managing branches, and keeping documentation alive, with a team of agents doing the heavy lifting. All by myself.

Stop obsessing over the perfect prompt

Stop obsessing over the perfect prompt

LLMs are built for conversation, not incantations. The value isn't in your opening message, it's in the back-and-forth: clarifying, correcting, refining. Iteration is cheap. The conversation is the work.

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