03 / AI platforms
AgentOS — AI agents and developers building software together
It turns client requirements into tasks, runs specialised AI agents in parallel and keeps every change under review, tests and human approval.
- 750+pull requests opened by agents
- 1,000+tasks completed
- 10 hto rebuild a project that originally took 127 days
01 / Overview
AgentOS is an autonomous development platform that coordinates software delivery between human developer teams and specialised AI agents — from the client's requirements to a tested release.
02 / The problem
Software teams lose much of their time to repetitive work: turning requirements into tickets, boilerplate code, reviews, tests and status reports. Progress, blockers and technical risks are hard to see, and handing work to AI tools without structure makes quality harder to control.
03 / Our approach
AgentOS analyses client requirements and turns them into technical tasks, splits large projects into stages and small development tasks, and assigns them to AI developer agents. Backend, frontend, QA and other specialised agents work in parallel, while automatic checks, code review, tests and human approval gates keep quality under control.
04 / The result
AgentOS is live, used by five international companies and more than 500 active users. Its agents have opened 750+ pull requests and completed more than 1,000 tasks, and rebuilt in 10 hours a project that had originally taken 127 days to write. Models are configurable — Claude Opus 5.5, OpenAI, Groq, GLM 5.3 or whichever model a client prefers — while pull-request approval and merge rules keep people in control of what ships. Within the ecosystem, AgentOS carries out the software tasks that RootOS plans.
05 / Key features
What it does.
- 01
Requirements to tasks
Analyses client requirements and turns them into technical tasks.
- 02
Planning in stages
Splits large projects into stages and small development tasks.
- 03
Parallel AI agents
Backend, frontend, QA, BI, project manager, software architect and DevOps agents work in parallel, each in its own role.
- 04
Automatic quality checks
Runs automatic checks, code review and tests on every change.
- 05
CI/CD and releases
A dedicated DevOps agent runs CI/CD pipelines, deployments and releases automatically.
- 06
Progress reporting
Reports on progress, blockers, technical risks and results.
06 / Architecture
How it is built.
Human in the loop
Every change goes through pull-request approval and merge rules: agents propose, people approve what ships.
Works where developers work
Fully integrated with GitHub, GitLab, Forgejo and Jira — agents open pull requests and update tickets in the tools the team already uses.
The ecosystem's developer workforce
AgentOS executes the software tasks that come out of MeetOS decisions and RootOS priorities.
07 / Technology
Tech stack.
- Agents
- Backend
- Frontend
- QA
- BI
- Project manager
- Software architect
- DevOps
- Backend
- .NET 10
- ASP.NET Core
- Apps
- Web
- Desktop
- Mobile
- Data
- PostgreSQL
- Redis
- Vector database
- AI
- Claude Opus 5.5
- OpenAI
- Groq
- GLM 5.3
- Client's model of choice
- Integrations
- GitHub
- GitLab
- Forgejo
- Jira
- Control
- Pull-request approval
- Merge rules
- CI/CD
- Infrastructure
- AWS (EU region)
- Cloudflare
