Chatto is Robots

← Back I’ve recently open-sourced Chatto, my self-hostable team and group chat app that I’ve been working on for the past 9 months or so. I think it’s really good! Everyone who’s tried it seems to agree! (Which I appreciate so much! The positive reaction to Chatto has been humbling.)<br>But here’s the kicker: my workflows in building and maintaining Chatto are pretty much 100% agentic ; I have, in fact, not written a single line of code since February this year. Yet, I have never felt as involved in a codebase as here. Agentic engineering has allowed me to spend a much larger portion of my time reasoning about the code instead of typing it out. The result is what I feel is the best application I have ever built.<br>In this blog post, I want to give you a good overview of my workflow. If you fundamentally hate the very idea of software being built with the help of AI, I’ll humbly ask you to make the effort to keep reading; your notion of what it means to work with coding agents may be incomplete, and maybe this post will help paint a more nuanced picture.<br>(Oh, and by the way: yes, I wrote the entire post myself. Having AI write blog posts is stupid! Don’t do it!)<br>Let’s dive in. The three pillars of my workflow are tools , agent guidance , and code reviews . I’m going to go through each of these one by one.<br>Tools<br>Models and Agents<br>I’ve had a €200/month subscription with one of the leading frontier labs since around December last year. Up until two months ago, this was Anthropic’s Claude Code; I have since fallen out of love with them and switched to OpenAI and Codex. Claude has become a weirdly unreliable mess, and Anthropic generally has some outright unpleasant views on what their users are allowed to do with their subscription and not. OpenAI’s models are fantastic, get to the point faster, and are way less obnoxiously chatty than Anthropic’s; the codex CLI is a significantly better computer citizen than claude; and to top it all off, OpenAI are being very generous with the many rate limit resets they’re handing out.<br>I don’t love paying €200 a month to a US-based frontier lab. It’s a lot of money — I keep referring to it as “half a PS5 every month”, even though this is no longer accurate — and being this dependent on a vendor, and one in the US to boot, is not great. But I see these as temporary caveats, and ultimately, the value this subscription provides is immeasurably higher. It allows me to move extremely fast by basically stripping most of the tedium from building complex applications. Some form of Chatto would exist without it, but it probably wouldn’t be as good.<br>It really is the easiest €200/month I’ve ever spent.<br>But like many others, I, too, am looking forward to local models eventually taking over “the bottom 80%” of this work. I’m super excited about the things happening in this space, and I’m convinced that 5 years from now, we will look back at 2026 and laugh at ourselves for shelling out all this money just to have a supercomputer write some Go for us. (Unless that supercomputer kills us first, an event that I reckon by now has a 50% chance of happening. Bring it, robots!)<br>Multi-Agent Orchestrators<br>Coding agents sometimes take their sweet time. If you’re just running a single session, you’ll end up with plenty of downtime.<br>The answer to this is parallelization; just run a bunch of agents working on different tasks in parallel. You can’t feasibly do that in the same directory, so you use git worktrees in order to give each agent its own little space to work in. Within each worktree, you’ll want to run your project’s setup task, and a copy of your coding agent. All this adds up, and you don’t want to spend half your workday manually managing git worktrees and running scripts, so instead, you’ll use an agent orchestration tool that does these things for you.<br>And there are so many of these out there. The one I’ve been using for the past half a year or so is Conductor, one of the few closed-source options. I don’t love that aspect of it, but other than that it’s generally fine. It’s also had some pretty terrible performance issues in the past; the main reason why I’m still using it is that I’ve grown accustomed to it, and switching to another tool introduces friction that I’m not eager to deal with.<br>But when I do eventually switch away from it, my new tool of choice will likely be Paseo. It follows the same UI paradigm as Conductor — they all do — but it’s open source and has a much saner architecture, with a server process running the actual agents and the UI only being a client that connects to it. It’s how I would have imagined such a tool to work if I had built my own, and I appreciate that.<br>In Conductor, starting work on a new task is one Cmd-N away; I enter the task, Conductor sets up the worktree, initializes the project, and gets going. When the agent is done, I get a notification; I can then review the code it has written, or click on a “Run” button to start a local copy...