I am pretty happy with gas city: https://github.com/gastownhall/gascity

I'm not a software engineer and it's enabled me to build a startup with $4k mrr in the last few months solo.

I know a few entrepreneurs and they all independently started building these kind of factories around the same time, so this is definitely not a straw-man.

I'd say give it another couple of months and you won't be able to move for announcements about this kind of thing.

The "sales pitch" is that factories are to agents what agents were to models; Personally I'm not convinced we need an extra automation layer, with all the downsides that come with even more disconnection from the product being built, but some people are starting to swear by them.

I guess it depends on what people define it as. But I've seen many devs build custom harnesses of sorts, and spend lots of time on that to wire it all together, to then really not achieve much with them. Examples being tools or stuff that got superseded once mcps became a thing. Or spend hours making gigantic folder of skills that specified loads of stuff that the next generation model just could infer. Or build a gigantic parallel agent suite when the bottleneck wasn't the agents in the first place.

I have my own dark factory for a small company I work in several projects. The factory is: agent orchestration and swd. Basically I refine the work to do, create a bunch of tickets on day 1 and the factory deliver the work during the rest of the week.

An example https://www.youtube.com/watch?v=lx0Eaane4Ng

> "software factories"

framework

So first off, talking about "LLMs" is kinda a yellow flag that you might be a bit behind the times, here: in ~April of this year[1], "agentic engineering" became truly tractable for serious work. We've all been playing with LLMs for coding and research since ~2023 of course, but they were mostly limited to the chatbot paradigm; even after years of Claude Code "harnesses", most engineers were still not trusting them to perform significant tasks on their own due to inevitable quality issues.

Now, that has changed. This isn't just better models, it's a qualitative improvement in capabilities, a step-change, an inflection point; what the MLrs like to call emergent capabilities, in a loose sense.

To pick just one very tangible example close to my heart: This is why the three.js subreddit[2] has exploded in popularity, showcasing demos by non-engineers that blow any three.js app I saw pre-singularity out of the water, which took hundreds of hours of specialized engineering to make (ask me how I know...). The community is reacting[3] much like the mathematicians, understandably.

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Ok now to answer your actual question (sorry -- that was the intention, originally!) as concisely as I can. "Software factories" are any system you setup to help you build software in deeply agentic ways. All the major harnesses and "ADEs" like Zed could arguably fit here already, but there's a massive ecosystem of other takes, as this article implies. I don't want to give them too much credit for just snagging the name, but the "Factory" startup does embody the idea pretty well: https://docs.factory.com/

They often (though not necessarily, IMHO) include some services that spawn their own agents after deterministic checks ("latent services", in my lingo) and services that use DL models more subtly to empower otherwise-symbolic services ("semilatent services").

In my biased experience, they often focus on a few central usecases, solving the problems that individual devs run into when trying to run multiple harnesses on multiple projects without friction, longterm decoherence, token wastage, or bottlenecks:

1. Code review. This is the big one and far trickier than it seems (trust me!), so often tried then abandoned. There's a huge startup just for this: https://www.coderabbit.ai

2. Cross-harness syncing of settings, hooks, and/or various flavours of very important markdown -- AGENTS.md files, skills, and subagents personas being the big ones.

3. Cross-agent, harness-agnostic coordination and communication. This just recently reached both the main harnesses, but it seems internal for now; a `BULLETIN.md` helps me a TON.

4. More generally, cross-agent coordination when it comes to worktrees, resource sharing (e.g. OCR queues on my 4090, for me), persisting agent-facing content (e.g. reports, trackers, scratch files, .jsonl blobs) in a convenient place that doesn't clog up the repo, and other technical details that might otherwise have to be figured out again and again by each agent.

5. Enforcing standards, either through hooks (blockers, nudges, or revertable fixes) or the aforementioned services. Think commit messages, prose simplicity, doc conventions, etc., though the sky's the limit, here. Like an intuitively-intelligent, more complexly triggered, agent-only precommit setup, in a way.

6. Finally, there's a whole ecosystem of tooling for agents, which I like to call "ACIs"/"Agent-Computer Interfaces". The sky is both the ground and the limit, here; it's really whatever the dev finds their agents to be oddly inefficient about, or just straight up bad at. I personally some to make edits "self-healing", normalize post-OCR cleaning, and capture quick screenshots w/ optional aesthetic critique[4], if that gives you a sense.

TL;DR: Fun stuff to make that speeds you up because it's tailormade to how you work! I made a bunch because I've been ""self-employed"" and thus had the time to explore myself[5], tho I understand why a more realistic after-work paradigm would make this kind of work wasteful.

On that note, back to writing cover letters -- apologies if the long message bothers anyone. I really should start a blog or get a hobby or something, huh

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[1]: i.e. Mythos and GPT-6, though obviously access rolled out slower to orgs/people without the special access programs, and even slower to people who prefer open models, where GLM-5.3[-Flash] was the first real contender[9]. For internal agent usage see this graph https://epoch.ai/data-insights/openai-coding-agent-spending and/or this writeup from June https://www.anthropic.com/research/claude-code-expertise

[2]: https://www.reddit.com/r/threejs/top/?t=month

[3]: https://www.linkedin.com/posts/danielgreenheck_i-think-its-t...

[4]: https://gitlab.com/doering-ai/libs/tact , https://gitlab.com/doering-ai/libs/mend , https://gitlab.com/doering-ai/apps/piq

[5]: Most of it is still private, but I made a subset public at https://gitlab.com/doering-ai/libs/fleet , and my code review & hooks are at https://gitlab.com/doering-ai/apps/gate

[9] https://www.anthropic.com/research/glm-5-3-and-the-spread-of...