From d56467a716793c674c3369e257929ce342c18186 Mon Sep 17 00:00:00 2001 From: bgagent Date: Wed, 13 May 2026 15:06:24 +0000 Subject: [PATCH] docs(readme): update README to reflect Slack, Linear, and nudge features Add Slack and Linear as first-class submission channels to the What is ABCA, The Use Case, and Getting started sections. Enumerate all five channels explicitly (CLI, REST API, webhooks, Slack, Linear). Add mid-run steering (bgagent nudge) to the key characteristics list. Link to SLACK_SETUP_GUIDE.md and LINEAR_SETUP_GUIDE.md from the manual installation section. Co-Authored-By: Claude Sonnet 4.6 Task-Id: 01KRGXT60S89PE4RWC90P8G2V8 Prompt-Version: 1c9c10e027a2 --- README.md | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index d0a124fc..8cc771f3 100644 --- a/README.md +++ b/README.md @@ -21,11 +21,11 @@ **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 platform is built on AWS CDK with a modular architecture: an input gateway normalizes requests from any channel (CLI, REST API, webhooks, Slack, Linear), 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, 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. +Users submit tasks through the **CLI**, **REST API**, **webhooks**, **Slack** (@mention the bot in any channel), or **Linear** (apply a label to an issue). 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: @@ -34,6 +34,7 @@ Key characteristics: - **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 +- **Mid-run steering** — send guidance to a running agent with `bgagent nudge` - **Learns over time** — the more you use it, the more it self-improves ## How it works @@ -132,6 +133,10 @@ Install [mise](https://mise.jdx.dev/getting-started.html) if you want to use rep Follow the [Developer Guide](./docs/guides/DEVELOPER_GUIDE.md) to set up your environment and deploy the application to your AWS account. Then, follow the [User Guide](./docs/guides/USER_GUIDE.md) to learn how to use the system. +Optional integrations to enable additional submission channels: +- **Slack** — submit tasks by @mentioning the bot and get threaded progress notifications. See the [Slack setup guide](./docs/guides/SLACK_SETUP_GUIDE.md). +- **Linear** — apply a label to an issue to trigger a task; the agent posts progress comments back on the issue. See the [Linear setup guide](./docs/guides/LINEAR_SETUP_GUIDE.md). + ## Documentation A documentation site is available containing all design documents, roadmap and guides to deploy and use the platform. You can access it [here](https://aws-samples.github.io/sample-autonomous-cloud-coding-agents/).