Centralized rules for Coding Agents like Claude Code, Github Copilot & Cursor. Your AI coding agent automatically picks the right rules per task. Ship enterprise-ready code at 10x speed.
Hey makers & creators, Pete here, Founder of @findable. and one of the early testers and supporters of Straion.
I’ve been working closely with @lukas_holzer and the team, as I keep seeing the problem of AI coding agents going off the rails.
Doesn't matter if you us Claude Code, Cursor, or Copilot. Yes, they make you faster, but especially in bigger orgs they often create problems.
So instead of just building, you often end up supervising. Correcting. Re-explaining context. Pulling the AI back onto the right path.
That's where Straion is helping engineering teams to stick to the organisations rules.
What impressed me early on is the simplicity of the core idea: give engineering teams a structured way to define “how we build software here,” and make sure AI coding agents actually follow those rules automatically.
Please let us know here in the comments what problems you are facing with AI coding, and how we can help,
@peterbuch Big fan of simple ideas that solve messy problems. This feels like one of those. How long does it usually take a team to get properly set up?
Supervising AI instead of coding defeats the purpose. If Straion solves that, it’s a big win for engineering orgs 🚀
For large teams of thousands of devs, especially in polyrepo / microfrontends like where I work at the moment, this tooling is exactly what we need to scale best practices while enforcing security compliance.
This solves a need that came up in discussion just this week for me. Very interested to follow your progress!
Congrats on the launch, Team Straion!, Managing AI agent rules is becoming a massive bottleneck.
One quick observation: Your copy is very technical. While devs get it, the decision makers (CTOs) are often worried about Technical Debt and Reliability. If you shift your narrative from “Managing Rules” to “Scale your AI dev team without the chaos”, you turn a technical tool into a strategic insurance policy.
At franvimktg, I help technical SaaS tools speak the language of growth
I have a couple of ideas on how to frame this for Engineering Managers to boost your trial sign ups. Cheers!
Hey, this looks amazing! Really useful concept, especially with regard to giving focussed context to an agent and for centralising rules across repos. I'd love to know how the tool selects the right rules to use and if there's any way to see which rules have been selected for a prompt?
the more access a tool gets on you computer the more important it is to give it rules and constraints. i think it solves a real problem.
As a founder of a security consultancy, watching how quickly the AI and agentic movement has taken off has been incredible, but also has introduced new and interesting challenges in keeping the company safe!
I am super excited to see what Straion can do in keeping engineering teams moving quickly while keeping the codebase clean and company policies met!
Seems Straion could handle the challenge of hallucination.... but just curious - would agents themselves handle making rules in future? lol
Seems Straion could handle the challenge of hallucination.... but just curious - would agents themselves handle making rules in future? lol
Love meeting builders here — I’m opening up 15-min intro demo calls for anyone curious about Straion 👋
If you want a quick walkthrough (how we handle dynamic rule/context selection for AI coding agents), grab a slot here: https://cal.com/lukas-holzer/quick-chat
Crongrats on the lunch. Totally see the need as i am often afraid that my coding Assistant is steadily drifitng away from our coding guidlines.
Am i also be able to setup different coding rules depending on the techstack of my project and teams? Web, python,... ?
We built Straion because AI-generated code is everywhere — but in reality, it rarely fits how companies actually build software.
The problem isn’t generating code anymore. It’s alignment. Every company has its own standards for security, privacy, architecture, design systems, and frameworks. Yet AI tools don’t automatically understand those rules. The result? Manual fixes, long review cycles, and wasted time.
We built Straion to change that.
Straion automatically extracts company-specific requirements from sources like wikis, contribution guidelines, and best practices — and translates them into instructions AI agents can actually follow. That way, generated code fits the organization from the start.
This means:
Less manual correction
Fewer review loops
Better security and compliance alignment
Faster, more cost-efficient delivery
Before building, we conducted 100+ interviews with software teams to truly understand their pain points. The result is a product that doesn’t just work technically — it solves a real, expensive problem.
Ultimately, we built Straion so developers can focus on what really matters again: building great software instead of fixing AI output.
Hi, looks awesome @lukas_holzer! is there any limitation in terms of team size, or can it be used with a e.g. 2person team and a 30 person team with the same results?
Hey Pete, that line about ending up supervising instead of building is so accurate. Was there a specific moment where an AI agent completely ignored how your team does things and you had to undo or re-explain everything?
This hits close to home. Coding agents are only as good as the context you give them, and right now that context lives in random markdown files scattered across repos. Having one source of truth that works across Cursor, Copilot, and Claude Code just makes sense.
Hey makers & creators,
Pete here, Founder of @findable. and one of the early testers and supporters of Straion.
I’ve been working closely with @lukas_holzer and the team, as I keep seeing the problem of AI coding agents going off the rails.
Doesn't matter if you us Claude Code, Cursor, or Copilot. Yes, they make you faster, but especially in bigger orgs they often create problems.
So instead of just building, you often end up supervising. Correcting. Re-explaining context. Pulling the AI back onto the right path.
That's where Straion is helping engineering teams to stick to the organisations rules.
What impressed me early on is the simplicity of the core idea: give engineering teams a structured way to define “how we build software here,” and make sure AI coding agents actually follow those rules automatically.
Please let us know here in the comments what problems you are facing with AI coding, and how we can help,
Happy Sunday, Pete