Open source · Agentic SDLC · Beyond Git

Ship code on
autopilot.

The autonomous development lifecycle (ADLC) platform. Fullsend deploys purpose-built agents across your GitHub repos that triage issues, write code, review PRs, fix findings, and ship to production—continuously.

Agentic SDLC Multi-agent pipeline GitHub-native Self-host supported OpenShell Sandbox

Get Started Star on GitHub

6 Agents E2E SDLC coverage

Apache 2.0 Open source

Linux & macOS CLI platforms

How it works

From issue to production.

Watch the full agent pipeline handle an issue end-to-end, right inside your GitHub repo.

Add rate limiting to API #847

fullsend-ai-triage[bot] bot triaged this issue 2 min ago

Scope: medium, type: feature. Suggested fix: wrap handler with sliding-window middleware. Good candidate for quick resolution.
Labels: type/feature component/api ready-to-code

fullsend-ai-coder[bot] bot opened a pull request 1 min ago

#848 feat: add sliding-window rate limiter
wrote middleware/ratelimit.go + ratelimit_test.go

fullsend-ai-review[bot] bot reviewed PR #848 45 sec ago

Reviewed across correctness, security, performance, and intent. 1 finding: potential race condition in CreateBranch under concurrent requests.

fullsend-ai-coder[bot] bot pushed a fix 30 sec ago

🔧 Fix agent — iteration 1. Fixed race-condition finding from review: added retry with backoff after CreateBranch. Tests passed.

fullsend-ai-retro[bot] bot analyzed the workflow just now

PR #848 merged in 5m34s. 1 review finding fixed by fix agent, approved on re-review. 1 proposal filed: add rate limit headers to error responses.

The Loop

Full SDLC, fully autonomous.

Every stage of the software development lifecycle handled by purpose-built agents that collaborate through your existing GitHub workflow.

Triage

Classify incoming issues, assess scope, suggest fixes, and apply labels automatically.

CRON

Prioritize

Score issues using the RICE framework and rank your project board by value automatically.

Code

Generate implementation PRs with tests, following your repo's conventions and patterns.

Review

Multi-dimensional review across correctness, security, performance, and intent alignment.

Fix

Address review findings automatically, push fixes, and re-run tests until clean.

Retro

Analyze completed workflows, surface insights, and file improvement proposals.

Agents

Meet the team.

Each agent is purpose-built for its role. They share context through GitHub—issues, PRs, and comments—just like human developers.

Triage

Reads every new issue, classifies scope and type, suggests a fix path, and applies labels so nothing falls through the cracks.

Code

Picks up ready-to-code issues, generates implementation PRs with tests, following your repo's style and conventions.

Review

Reviews every PR across correctness, security, performance, and intent. Posts inline comments with specific, actionable findings.

Fix

Reads review findings, applies code fixes, pushes commits, and re-runs tests. Iterates until the review passes clean.

Prioritize

Scores issues using the RICE framework—Reach, Impact, Confidence, Effort—and ranks your project board by value.

Retro

After merge, analyzes the full workflow—timing, iterations, patterns—and files proposals for process improvements.

Getting Started

Three steps to autonomous.

Deploy the full agent pipeline to your GitHub organization in minutes. No infrastructure to manage.

Install the GitHub App

Add fullsend to your GitHub organization. Select which repos the agents can access and what permissions to grant.

Enroll your repos

Enable specific repos for the agent pipeline. Customize agent config, agent model, and LLM provider per repo.

$ fullsend github setup

File an issue

Create a GitHub issue. The triage agent picks it up, the code agent writes a PR, review validates, fix cleans up, retro learns. Autonomous.

$ gh issue create --title "Add rate limiting"

Design Principles

Built for trust.

Fullsend is designed around safety, transparency, and human oversight at every step.

OpenShell Sandbox

Agents run inside NVIDIA OpenShell sandboxed environments with policy-enforced egress routing, filesystem isolation, and process constraints.

Prompt injection defense

Agent inputs are sanitized and validated before execution. Malicious payloads in issues, PRs, and comments are detected and blocked.

Guarded paths

Agents operate within explicit guardrails you configure: coding API, gating policies, and safety checks. Every action is traceable.

Fully customizable

Choose your LLM provider, set agent behavior per repo, define policies, and configure which agents run and when.

Transparent by default

Every agent action is visible in GitHub. Comments, commits, reviews—all in the open, all auditable.

Human in the loop

Agents propose, humans approve. You stay in control of merges, deployments, and critical decisions.

Ship code onautopilot.

Ship code on
autopilot.