The Neuron: AI Explained
This AI Agent Builds Better Code Than Most Developers (Factory AI)
27 Jan 2026
Chapter 1: What are autonomous coding agents and how do they work?
These aren't humans, they're a different type of tool that humans can use. We have customers that have quite literally run sessions that go well under the 80 million tokens. Two or three years ago, the term agents had really negative connotations because the only agents that were really out there were extremely unreliable. No one had seen this sort of fully autonomous interaction form factor yet.
It's a fully self-contained, binary that runs on any operating system on any device in any environment with any interface that you can imagine.
Welcome, humans, to the Neuron Podcast. I'm Corey Knowles, here with our purveyor of words and slinger of cat puns, Grant Harvey. How are you, Grant?
Doing well. Doing well. How are you, Corey?
I'm doing good, man.
Doing good. I'm excited because today we are digging into the rise of autonomous software agents. Factory AI is one of the fastest growing companies in this space, building droids that can take tickets, modify real code bases, and work inside existing dev workflows. But before we get started, Please take a quick moment to like and subscribe so you don't miss out on videos just like this one.
And joining us today is Factory AI co-founder and CTO Eno Reyes to talk about how this works, what breaks, and what it's like to scale a company at this speed even. Eno, welcome to The Neuron. How are you?
Thanks for having me. Excited to be here and excited to chat more about the droids. The droids. The droids. Were you inspired by Star Wars with the name droids? My lawyers say that that is not something that I can comment on. Just kidding. No. Actually, the name's origin comes from the fact that two or three years ago,
The term agent had really negative connotations because the only agents that were really out there were extremely unreliable. They would break at every corner. And when we wanted to sell to enterprises, if they heard the word agent, they would associate it with basically like a research experiment. So we came up with a name that we felt would...
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Chapter 2: What challenges did Factory AI aim to address in software development?
Or has it expanded since then?
Yeah, so the actual Droid itself is actually, you know, So it is totally general. Now, what developers can do, though, is there's tons of customizations that they can introduce. You can introduce skills which give it the ability to basically pull in context and work on any workflow or
bucket of information that you want to pull in, you can do hooks, you can do custom slash commands, all these different customizations that you can bring in sub agents, etc. And so what what people can do is if they want a code review droid, then they might place droid inside of GitHub actions and say to it, you should be code review agent.
If you want a security droid, you can place it in your, you know, whatever system that you use for either pipelines or security review, and it becomes a security review agent. If you want to expand that and make it customized to your organization, you can introduce skills and custom sub agents and all these other things that basically allow it to conform to your organization standards.
I've heard that Droid is kind of almost like an engineering team that runs in the background. You can use it in that way.
How do the agents then understand large, messy, real-world code bases versus, say, another agentic tool and how they- I think that this is one of the most interesting questions because there are several things that go into being able to explore and understand a very large code base, especially for hard problems. I think that the three angles I would say is there's the environment.
That matters a lot. Basically, what information does the droid have access to in order to understand? Two, there's the droid's inherent ability to explore and search. And three is how it handles long-term goal-directed behavior. That third is
arguably the most important piece of research that, you know, as factories and agent research lab, and that's basically the most important piece of research is how do you do long-term goal-directed behavior?
But I think on that first point of like the environment, one thing that I think makes droids really effective in larger code bases, enterprise environments is that it, it's very, it makes it very easy for you to understand is your environment actually agent ready. In other words, it will tell you, you know, is Droid operating in its best environment possible?
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Chapter 3: How has the vision for fully autonomous agents evolved over time?
Maybe you insert a reminder that say, hey, by the way, you should just check up to make sure this work is actually valid. You can seek these out in the background. And whenever you edit a file, provide language server feedback that helps the model understand, oh, I might be missing these things.
So there's tons of things you can do within the harness that make the model more aware without needing to actually waste LLM calls.
then from a behavioral perspective there there's also a lot that goes into enabling the tooling to get easy answers from important questions so like we have uh in our product an api for agent readiness which basically and a dashboard so so there's 150 plus signals that a code base could have uh ranging from it is a linter present to uh You know, are tests available?
Is there documentation across the code base? And this applies to mono repos where it will segment out each project or single code bases.
So when you make it really easy for an agent to seek that information, like one API call to get the answer, you make it easier in general for the system to rely on that information versus if it needs to find that out from scratch every time, you're going to waste your users tokens trying to get the answer.
Yeah, I've lived that, actually. Like, working with an agent, like, in my terminal, I've been constantly reminding it, like, remember, you should check all the scripts to make sure that you, you know, know all the dependencies of everything. Like, I'm doing that. So, like, yeah, use Factory because it'll save you those tokens.
Yeah. Totally. And hooks are also great for that. Like, I think there's a pretty popular one right now called Ralph Wiggums. It which is a odd name. And I always feel silly saying that it's from the seasons. But it's basically a hook that you run at the end when the agent loop stops.
And, and it sends a prompt back to the agent that basically says, you know, here's the step by step plan of what you were supposed to do. did you actually validate and complete the work that you're supposed to do? If not, restart, right? And so it's effectively a while loop in a while loop.
I honestly think that the existence of plugins like that means the agents harnesses aren't taking advantage of what they could be, but regardless, people find this out and then they build and they customize.
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