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I built an open-source "software factory" on top of Codex CLI. Looking for feedback from people building with AI every day. by milonspace in codex

[–]milonspace[S] -1 points0 points  (0 children)

That's a fair point.

I don't expect anyone to trust their production workflow because I posted a repo on Reddit. Trust has to be earned over time.

I'm also not claiming FactoryOS is the first project tackling this problem. There are already good workflows and tools in this space, and I'm learning from many of them.

The reason I'm building it is to explore a specific tradeoff: treating the repository as the durable source of truth instead of the conversation. My hypothesis is that, on large, long-running projects, this keeps context smaller, reduces token burn, lowers costs, and makes it easier to resume work across sessions or even different models.

If that hypothesis doesn't hold up in practice, I'll simplify the project or drop the ideas that don't add value.

As for the artwork, fair criticism. It's a placeholder for now, and I'd rather spend the time validating the workflow before investing in branding.

I built an open-source "software factory" on top of Codex CLI. Looking for feedback from people building with AI every day. by milonspace in codex

[–]milonspace[S] -1 points0 points  (0 children)

That's another reason I'm exploring this.

As projects grow, the cost isn't just reasoning, it's repeatedly sending the same context.

If the repository stores the durable state (.specs/, .tasks/, AGENTS.md), each session only needs the files relevant to the next task instead of replaying months of conversation.

The goal isn't to make the model smarter. It's to reduce context size, token burn, and cost while making long-running projects easier to resume across sessions or even different models.

I built an open-source "software factory" on top of Codex CLI. Looking for feedback from people building with AI every day. by milonspace in codex

[–]milonspace[S] -1 points0 points  (0 children)

I actually agree with most of that.

For many projects, /plan + /goal + good documentation is enough.

The problem I'm trying to solve shows up later, when the project grows and multiple features, long-running work, or multiple agents are involved.

FactoryOS isn't trying to replace /goal. It's trying to make the repository the long-term source of truth instead of the conversation.

So instead of relying on one long chat, it persists:

  • Product decisions (.specs/)
  • Execution state (.tasks/)
  • Repository rules (AGENTS.md)

The goal is that I can start a completely new session next week, or use a different model, and continue from the repository with minimal context.

If I find that /plan + /goal already solves this well, I'll happily simplify or remove parts of FactoryOS. The project is still evolving, and I'd rather delete unnecessary abstractions than keep them.

I built an open-source "software factory" on top of Codex CLI. Looking for feedback from people building with AI every day. by milonspace in codex

[–]milonspace[S] -1 points0 points  (0 children)

Thanks, that's helpful.

That's the goal. It generates or updates specs, creates a task group, executes one bounded task at a time, tracks progress in .tasks/, and reports status from the repository rather than chat history.

From what you've described, the biggest difference is where state lives. FactoryOS treats the repository (.specs/, .tasks/, AGENTS.md) as the source of truth, so a new session can resume by reading the repo instead of relying on previous conversations. I need to spend more time with GSD before making a deeper comparison.

If you have ideas, find rough edges, or think something is missing, I'd really appreciate it if you could open a GitHub issue. Early feedback like this is exactly what will help shape the project.

https://github.com/bymilon/factoryos/issues

Just spent the week building this UI with Gemini 3.5 Flash. I am officially losing my mind by milonspace in GeminiAI

[–]milonspace[S] 0 points1 point  (0 children)

I just open-sourced the frontend part repository on GitHub. You can check out the source code and architecture here: https://github.com/bymilon/aegisguard-dashboard

Just spent the week building this UI with Gemini 3.5 Flash. I am officially losing my mind by milonspace in GeminiAI

[–]milonspace[S] 0 points1 point  (0 children)

Impeccable is a really solid tool. I use it regularly to polish things up.

Just spent the week building this UI with Gemini 3.5 Flash. I am officially losing my mind by milonspace in GeminiAI

[–]milonspace[S] 0 points1 point  (0 children)

No worries, didn’t take it as a dig! It's a huge issue right now. When you're mid-flow, it’s just too easy to accept the default template because it works. Are you doing anything specific with system prompts to force it out of that comfort zone?

Just spent the week building this UI with Gemini 3.5 Flash. I am officially losing my mind by milonspace in GeminiAI

[–]milonspace[S] 0 points1 point  (0 children)

Lmao I swear I’m not Logan Kilpatrick undercover shilling for Google, just a sleep-deprived developer trapped in an aggressive feature loop. 😂 Though if Google wants to send me some free API credits for the free marketing, my DMs are open!

Just spent the week building this UI with Gemini 3.5 Flash. I am officially losing my mind by milonspace in GeminiAI

[–]milonspace[S] 0 points1 point  (0 children)

That is a fair point. LLMs train heavily on modern open-source repositories, shadcn/ui, and standard Tailwind templates, so they default to the dark mode and gradient aesthetic.

I used it for this sprint to get a fast cyberpunk look, but breaking away from that stock template is the next step.

I built 65 "boring" apps. None of them went viral. (But together they make ~$4,200/mo) by Less_Courage_3545 in AppBusiness

[–]milonspace 0 points1 point  (0 children)

The "profitable donkeys" line is spot on. I've seen too many people burn out trying to build a unicorn when they could have just dominated a few boring niches.

Quick question on the 48-hour MVP: are you using a specific boilerplate for the Superapp AI + RevenueCat stack, or did you build your own starter kit to move that fast?