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Overview

CoderFlow is an enterprise platform that runs autonomous engineering agents inside your infrastructure. Instead of suggesting code, agents compile, test, validate, and fix legacy systems end-to-end — delivering verified, ready-to-commit results and 5–10x productivity gains.

What is CoderFlow?​

CoderFlow is a client-server system designed for enterprise teams working with complex codebases—including legacy systems like IBM i, COBOL, and RPG code. Rather than requiring developers to manually edit code and run tests, CoderFlow:

  • Submits coding tasks to AI agents (Claude, Codex, Gemini, Bob, Grok) running in isolated Docker containers
  • Lets agents execute code, compile, test, and validate changes automatically
  • Supports both headless execution (submit once, review results later) and interactive sessions (work within containers for guided work)
  • Manages multi-repository workspaces with build pipelines and test suites
  • Allows developers to review, iterate, and approve changes before committing

Key benefits:

  • Full Build-Test-Fix Loops: Agents don't just write code—they compile, test, and fix until validation passes
  • On-Premises Execution: Runs inside your infrastructure with your security controls
  • Legacy System Support: Handles IBM i, RPG, COBOL, and modern stacks (Node.js, Java, etc.)
  • Parallel Multi-Agent Execution: Run multiple agents concurrently with automated result comparison
  • Developer Orchestration: You control objectives; agents execute; you approve results
  • Skills Management: Create reusable prompt-based skills and assign them to environments

How It Works​

  1. Create a Task: You define an objective (e.g., "refactor function X" or "add feature Y") via CLI, Web UI, or API
  2. Agent Executes in Container: The server spins up a Docker container with your codebase, repositories, and build environment
  3. Full Validation Loop: The agent makes changes, compiles, runs tests, and fixes issues until all validations pass
  4. Review Results: Check the agent's work—summary, changes, test results, and commit message—all in one place
  5. Approve & Commit: Once satisfied, apply changes directly to your repositories

The entire process is transparent: you can watch the agent's progress in real-time or review the complete activity log afterward.

Key Features​

  • Environments: Pre-configured Docker images with your repositories, build tools, and dependencies
  • Tasks: Discrete coding objectives that agents execute autonomously or interactively
  • Parallel Agents: Run multiple agents on different tasks or the same task for comparison
  • AI Review & Judge Agents: Automated evaluation of agent results for quality and correctness
  • Container Isolation: Each task runs in its own secure, isolated container with time limits
  • Task Queueing: Automatic queue management with concurrency limits (default: 8 concurrent agents)
  • Real-Time Monitoring: Watch agent progress, activity feeds, and live logs
  • Multi-Repository Support: Clone and sync multiple Git repositories per environment
  • Build & Test Automation: Run build scripts, tests, and validation checks as part of task execution
  • Result Delivery: Summaries, file diffs, test reports, and ready-to-commit patches
  • Application Servers: Optional in-container app server for testing web interfaces
  • Scheduled Image Rebuilds: Keep Docker images fresh with automated rebuilds on a schedule