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Roadmap

A practical roadmap for autonomous AI engineering.

This view combines the repository roadmap with the recent product direction visible in merged PRs: dependable autonomous workflows, inspectable execution, and safer self-hosted deployment.

ProjectOverview and metricsRoadmapNow, next, and success signalsReleasesLatest release and changelog viewCommunityContribution entry points and governance

Active themes from recent PRs

The public roadmap remains the source of truth, but recent merged work adds useful context for evaluators who want to understand where Open ACE is heading right now.

  • Make autonomous workflows dependable enough for real repository work, including pause, retry, timeout, review, and merge behavior.
  • Improve evaluator confidence with timeline summaries, full-text milestone views, final code changes, and release/project transparency.
  • Keep remote execution practical across Docker, package installs, macOS, Windows, source installs, and additional CLI agents such as ZCode.

Tracked roadmap lanes

The source of truth remains ROADMAP.md in the repository. During each site build, the content is parsed into stable sections that can be rendered with stronger visual structure.

Now

  • Make the first-run experience reliable with Docker Compose, SQLite/PostgreSQL setup, and clear default credential handling.
  • Keep README, docs site, and documentation links in sync across Chinese and English.
  • Publish focused starter issues for documentation, first-run bugs, UI polish, and connector examples.
  • Add GitHub repository topics: `ai-governance`, `ai-workspace`, `enterprise-ai`, `llmops`, `flask`, `react`, `self-hosted`, `claude-code`, `qwen-code`, `codex`.

Next

  • Publish GitHub releases with changelog notes, Docker image tags, and upgrade instructions.
  • Add a safe public demo path that does not expose shared admin credentials.
  • Improve production deployment docs for TLS, secrets, backups, SSO, and Kubernetes.
  • Add example dashboards and sample datasets so evaluators can understand the product before connecting real logs.

Later

  • Create connector guides for additional AI tools and model gateways.
  • Add richer audit reports for security, compliance, and cost allocation.
  • Provide Helm chart packaging and versioned migration playbooks.
  • Publish user stories and screenshots from real adoption scenarios.

Success Signals

  • New users can run Open ACE locally in under 10 minutes.
  • The project has tagged releases, working docs links, and a visible maintainer workflow.
  • External contributors can find good first issues and understand what kind of help is wanted.
  • Teams can evaluate Open ACE without sharing production data or credentials.