🔄 Autonomous Dev Loop (Issue → PR)

Overview

Implement end-to-end autonomous development workflow that takes GitHub issues and produces tested, reviewed pull requests without human intervention.

Problem

Current AI assistants require constant human guidance and supervision. No capability to autonomously complete full development cycles from requirements to production-ready code.

Solution

Build autonomous development pipeline with hard quality gates:

Workflow Steps

1. Issue Analysis: Parse requirements, extract acceptance criteria
2. Planning: Generate detailed implementation plan with file changes
3. Implementation: Apply minimal, verifiable code changes
4. Testing: Generate comprehensive test suite and verify passes
5. Review: Quality analysis, security check, performance review
6. Integration: Create PR with full documentation and artifacts

Quality Gates (Hard Stops)

• ✅ Compilation Gate: All code must compile cleanly
• ✅ Test Gate: All tests pass with coverage thresholds
• ✅ Lint Gate: Code quality standards enforced
• ✅ Security Gate: No vulnerabilities or exposed secrets
• ✅ Performance Gate: No significant regressions

DevLoop Engine

struct DevLoop {
    planner: PlannerAgent,
    coder: CoderAgent,
    tester: TesterAgent,
    reviewer: ReviewerAgent,
    fixer: FixerAgent,
    policy_guard: PolicyGuard,
}

impl DevLoop {
    async fn execute(&self, issue: GitHubIssue) -> Result<PullRequest>;
}

Artifacts Generated

• plan.md: Detailed implementation strategy
• changes.patch: All code modifications
• tests.log: Test execution results
• coverage.json: Code coverage analysis
• security.json: Security scan results
• performance.json: Performance benchmarks
• review.md: Quality assessment report

CLI Interface

# Execute autonomous dev loop
grimoire devloop --issue 123 --policy secure --budget cost=$2/time=20m

# Preview mode (no changes)
grimoire devloop --issue 123 --dry-run --explain

# Resume failed devloop
grimoire devloop --resume <run-id> --from-step testing

Policy Profiles

• Secure: Read-only mode, manual approval for PRs
• Standard: Automatic testing, human review before merge
• Aggressive: Full automation with post-merge monitoring

Implementation Plan

1. Build issue parsing and requirement extraction
2. Implement planning agent with task decomposition
3. Add code generation with impact analysis
4. Build comprehensive testing pipeline
5. Add quality review and security scanning
6. Integrate with GitHub PR workflow

Success Criteria

• 80%+ of simple issues completed without human intervention
• All generated PRs pass CI/CD pipelines
• Zero security vulnerabilities in generated code
• 90%+ test coverage on new code
• Generated code quality matches human standards

Timeline

12-16 weeks for MVP, 20-24 weeks for production deployment

Dependencies

• Project Graph (#4287)
• ToolGraph Engine (#4288)
• Multi-Agent System (#4289)
• Testing Infrastructure