Earendil

Pi's new system theme asks your terminal for its colors and builds Pi's theme from them. How it works.

At Earendil, we want to build products that respect the choices of the people using them. So when we were refreshing Pi's themes, we wanted a theme that adapts to the terminal it runs in. Most people who spend their day in a terminal have picked their own

Today Earendil and the Pi community shipped Pi 1.0 . This reflects our belief that after countless hours of hardening, maintenance, and active development, Pi is now a solid foundation on which to build. Pi also continues to evolve. Together with Pi 1.0,

If you went to pi.dev in the past, you found a proud declaration that Pi does not support MCP . If you listen to podcasts where we talked about Pi, you will have found more than one dismissive statement about MCP from us. Including a post by Mario about i

LLMs have become almost perfect at generating code, but that isn't the end of the story. Just because the code is formally correct doesn't mean that it is not introducing unnecessary abstractions, creating duplicates, or just making bad decisions overall.

Notes from a non-engineer I'm not an engineer. At a company building agent harness software for programmers typing into black terminal windows, that used to feel like something I should whisper. Everyone around me was shipping code. I was writing docs, pl

Harness - definition by the Cambridge Dictionary Noun. a piece of equipment with straps and belts, used to control or hold in place a person, animal, or object Verb. to control something, usually in order to use its power - When I think of a harness, I th

If you have ever had a long coding session in a coding agent like Pi , Claude Code, or Codex, you will have triggered a compaction. In this post we explain how compaction works and when Pi needs to compact. An LLM conversation Large language models (LLMs)

Sanofi and Earendil Labs

Pi's Minimalism Is Its Advantage AI has made code cheap, and as a result many companies are building bigger tools in pursuit of better performance. Larger prompts, more orchestration, more layers, more complexity. This also makes these tools intrinsically