NanoAgent gives developers an AI teammate that can work inside a real repository while keeping the human in control. Ask it to understand a codebase, plan a change, edit files, run validation, review a diff, or automate a pull request review from the same toolchain you already use. It is built for practical engineering work: local projects, real shells, version-controlled memory, reviewable changes, and explicit approval for sensitive actions.

Lightfield — AI-native CRM that builds itself and does work for you

AI-native CRM that builds itself and does work for you

AI coding agents are becoming very powerful, but many of them feel too closed, too provider-locked, or too hidden in how they work. I wanted an agent that could work inside a real repository, but still let the developer stay in control. For me, the important questions were: Can I choose my own model or provider? Can I see what the agent is doing before it edits files or runs commands? Can memory live inside the repo instead of hidden somewhere? Can the same agent work from terminal, desktop, editor, and CI? Can teams review and customize the workflow instead of trusting a black box? That is what pushed me to build NanoAgent. The goal is not to say existing tools are bad. Claude Code, Codex, Cursor, and OpenCode are all impressive. NanoAgent is my attempt to build an open, controllable coding-agent workflow for developers who want AI help without giving up visibility, provider choice, and engineering control.

Lightfield — AI-native CRM that builds itself and does work for you

AI-native CRM that builds itself and does work for you

NanoAgent

AI Coding Agent with Absolute Control

AI Coding Agent with Absolute Control