Introduction

ABCA

Autonomous Background Coding Agents on AWS

What is ABCA

ABCA (Autonomous Background Coding Agents on AWS) is a sample of what a self-hosted background coding agents platform might look like on AWS. Users can create background coding agents, then submit coding tasks to them and the agents work autonomously in the cloud — cloning repos, writing code, running tests, and opening pull requests for review. No human interaction during execution.

The platform is built on AWS CDK with a modular architecture: an input gateway normalizes requests from any channel, a durable orchestrator executes each task according to a blueprint, and isolated compute environments run each agent. Agents learn from past interactions through a tiered memory system backed by AgentCore Memory, and a review feedback loop captures PR review comments to improve future runs.

The use case

Users submit tasks through webhooks, CLI, or Slack. For each task, the orchestrator executes the blueprint: an isolated environment is provisioned, an agent clones the target GitHub repository, creates a branch, works on the task, and opens a pull request.

Key characteristics:

• Ephemeral environments — each task starts fresh, no in-process state carries over
• Asynchronous — no real-time conversation during execution
• Repository-scoped — each task targets a specific repo
• Outcome-measurable — the PR is either merged, revised, or rejected
• Fire and forget — submit, forget, review the outcome
• Learns over time — the more you use it, the more it self-improves

How it works

Each task follows a blueprint — a hybrid workflow that mixes deterministic steps (no LLM, predictable, cheap) with agentic steps (LLM-driven, flexible, expensive):

1. Admission — the orchestrator validates the request, checks concurrency limits, and queues the task if needed.
2. Context hydration — the platform gathers context: task description, GitHub issue body, repo-intrinsic knowledge (CLAUDE.md, README), and memory from past tasks on the same repo.
3. Agent execution — the agent runs in an isolated MicroVM: clones the repo, creates a branch, edits code, commits, runs tests and lint. The orchestrator polls for completion without blocking compute.
4. Finalization — the orchestrator infers the result (PR created or not), runs optional validation (lint, tests), extracts learnings into memory, and updates task status.