How Pi's minimal harness improves coding-agent cost and performance, with examples from Databricks and Shopify's pi-autoresearch extension.
Pi: The Minimal Agent Within OpenClaw
A gentle introduction to the Pi coding agent and why I think it’s a glimpse into the future of software.
Scaling long-running autonomous coding · Cursor
We've been experimenting with running coding agents autonomously for weeks at a time.
can1357/oh-my-pi
⌥ AI Coding agent for the terminal — hash-anchored edits, optimized tool harness, LSP, Python, browser, subagents, and more
Building pi in a World of Slop — Mario Zechner
fx - Tiny, open, native coding agent
Tiny, open, native coding agent. A minimal CLI written in Zig, optimized for research and embeddability as part of larger systems.
Background Coding Agents: Predictable Results Through Strong Feedback Loops (Part 3) | Spotify Engineering
This is part 3 in our series about Spotify's journey with background coding agents and the future of large-scale software maintenance. See also and .
nicobailon/pi-model-switch
Pi coding agent extension that gives the agent the ability to switch models on its own
I Hated Every Coding Agent, So I Built My Own — Mario Zechner (Pi)
Agent Skills
AI coding agents take the shortest path to done, which usually means skipping the specs, tests, and reviews that make software reliable at scale. Agent Skill...
More pull requests, not less work - Sensemaker
Linear's telemetry shows coding agents multiplying output while planning and coordination do not shrink.
Towards self-driving codebases · Cursor
We're making a part of our multi-agent research harness available to try today in preview.
nicobailon/pi-interactive-shell
Pi coding agent extension that allows Pi to autonomously control interactive CLIs in an observable overlay. Full PTY emulation, no tmux, token efficient. User can take over anytime.
Prime Agent: A self-improving RLM agent
Prime Agent is our open-source, self-improving coding harness built around two abstractions: the Recursive Language Model (RLM) and the Continual Harness. With Opus 5, it achieves 95.5% on ARC-AGI-3, surpassing the reported human expert baseline.
Prompt Caching In Agents | EARENDIL
How prompt caching shapes the cost, latency, tools, and architecture of coding agents, and what Pi does to keep cache behavior visible.
xai-org/grok-build
SpaceXAI's coding agent harness and TUI. Fullscreen, mouse interactive, extensible.
