Watch CogOS work.
Over the shoulder.
Real walkthroughs showing every step, every agent, and every decision CogOS makes. Pick a scenario and follow along.
Build a production-ready REST API in 90 seconds
You need a FastAPI backend with PostgreSQL, auth, tests, and docs. CogOS decomposes this into parallel agent tasks, produces working code, and validates the result before you see it.
The Planner breaks the task into 5 subtasks — project scaffold, database models, auth logic, API routes, and test suite. Each subtask is routed to the agent best suited for it. The Python and PostgreSQL modules inject domain-specific prompt extensions so every agent writes idiomatic code.
The Coder writes real, importable Python — not pseudocode. Each file follows FastAPI conventions the Researcher agent found. The cog-code-python module ensures async patterns, type hints, and Pydantic models are used correctly.
Debug a failing production service end-to-end
A Python worker is crashing with a cryptic database error at 3 AM. CogOS traces the error path, identifies the root cause, writes the fix, and generates a regression test — all before your coffee is ready.
Step 1: Read the error traceback
CogOS reads the failing file and the traceback. The Researcher agent identifies the stack: worker.py → db_client.py → psycopg2.OperationalError: connection pool exhausted.
Step 2: Trace the connection pool logic
The cog-db-postgres module tells CogOS that psycopg2 pool exhaustion usually means connections aren't being returned. CogOS uses filesystem.read to inspect db_client.py and finds a missing finally block.
Step 3: Identify the root cause
The reviewer confirms: get_connection() checks out a pool connection but early returns on error without returning it. Over time this drains the pool.
The bug is subtle. The get_connection() function has a try/except that catches auth errors and returns None — but the connection was already checked out from the pool before the auth check. Returning None leaks the connection. CogOS found this because the cog-db-postgres module flagged pool-exhaustion as a known pattern.
Containerize and deploy to AWS ECS
You have a working app and need it on AWS with Docker, an ECS task definition, a load balancer, and a CI/CD pipeline. CogOS uses its cloud and container modules to generate everything you need.
The Planner maps the full deployment pipeline. The cog-cloud-aws module knows ECS, ECR, ALB, and IAM conventions. The cog-infra-docker module ensures multi-stage builds and proper layer caching. Together they produce production-grade configs, not toy examples.
Why Terraform? The Architect agent chose it over raw AWS CLI scripts because the cog-cloud-aws module's prompt extensions recommend IaC for any deployment with more than 2 resources. The IAM role is scoped to exactly the permissions the ECS task needs — no wildcard actions.
Scaffold a full-stack app with tests, CI, and docs
Start from nothing — a blank directory — and end up with a React frontend, FastAPI backend, PostgreSQL database, test suites, a GitHub Actions CI pipeline, and documentation. CogOS coordinates all 10 agents across the full stack.
All 10 agents contribute. The Planner decomposes into 8 subtasks. The Architect designs the folder structure and API contract. The Researcher gathers React 18 + FastAPI patterns. The Coder generates 22 files across frontend and backend. The Tester writes 38 tests. The Documenter writes a README. The Reviewer checks everything.
Try these yourself
Install CogOS and run any of these examples on your own machine. Free, local, open source.