philipplgh

1/ I built @kombuse_labs — an open-source desktop app for managing AI coding agents with a local issue tracker. Runs on SQLite, integrates with Claude Code and Codex and makes everything available via MCP for the tools and IDEs you already use. No cloud setup. Here's what it does and why:

11/ Give it a try Local-first. Private by default. MIT licensed. github.com/KombuseLabs/ko… kombuse.dev

10/ Transparency NO MAGIC Sessions are inspectable — full system prompts, invocation traces, which agent called what, which permissions were granted. Layered levels of details: tickets = why: high level management of tasks sessions = how: available to inspect and analyze one by one or batched Productive and mostly autopilot, but never a black box, a loop running for hours, or nested sub agent calls invisible to user.

1/ I built @kombuse_labs — an open-source desktop app for managing AI coding agents with a local issue tracker. Runs on SQLite, integrates with Claude Code and Codex and makes everything available via MCP for the tools and IDEs you already use. No cloud setup. Here's what it does and why:

Been working on this and just open sourced it— Kombuse is a local-first app for managing AI coding agents with a private issue tracker. It integrates Claude Code and Codex and come with a full development pipeline that was used to develop the app itself ✌️

@heymilady 2026 AI wrapper. 1973 tools.

@philipplgh wait bash and grep are still cooking? some habits never die huh

1/ How to optimize your codebase for agents Most repos are optimized for the user's mental model, for file browsers with deeply nested hierarchies or the IDE. Few optimize for search. In 2026, that’s a mistake. If you’re using AI coding agents, you are not optimizing for yourself or even the agent but for code discovery via: - (rip)grep - glob - path heuristics - symbol frequency Ask Claude or Codex: “How can my codebase be optimized for grep and glob?”

@BrunoFOMO just out here fighting to reduce my $ spent on tokens

9/ Meta prompting Let claude and codex do your job. Ask them "how can I make things easier for you?". They’ll surface structural inefficiencies you don’t see — from finding KPIs to excessive search cycles to unnecessary token spend. Often the bottleneck isn’t reasoning. It’s exploration. Every codebase has different optimization headroom. Code navigation is one problem. Look at the details of what they are doing from time to time. Check the "Thinking" sections and try to understand where they struggle. Enable agents to help themselves. Build self-healing feedback loops.

8/ Advanced optimizations II React Query Registry: Instead of inline string segments create a registry of stable key identifiers. This gives you - deterministic search - safer cache invalidations - stronger typing and enforced structure - refactor safety