Tracer Bart Mode: Autonomous AI Epic Orchestration
Tracer's Bart mode executes full project epics via AI agents: breaks specs into parallel tasks, reviews progress against intent, adapts plans, and escalates only when needed—no babysitting required, free with any coding agent.
Bart Mode Replaces Agent Babysitting with Adaptive Orchestration
Traditional AI coding agents require constant oversight: you run tasks, monitor failures, and fix them manually, limiting automation to partial workflows. Tracer's Bart mode solves this by adding a smart orchestrator layer that handles entire epics—large features composed of multiple tickets. It decomposes your initial prompt into detailed specs and tickets (e.g., project scaffolding, database setup, authentication flows, API endpoints, UI screens), then executes them in parallel batches using any hooked-up coding agent like Claude Code, Gemini 1.5 Flash (free tier), or Kilocode ($25 free credits).
Unlike 'Ralph loops'—dumb retries without awareness—Bart reviews each batch's output against specs, updates tickets or plans based on new insights, and adapts intelligently. It only escalates to you for true ambiguities, letting you start an epic (e.g., 'build a dashboard with authentication and API integration to manage AI agents') and return to a completed, functional result. This leverages current model capabilities (e.g., Opus at 4.7 reasoning effort) for reliable autonomy, shifting from step-by-step guidance to full workflow execution.
Team collaboration integrates humans and AI in one artifact: invite members to refine specs in real-time before execution. Post-build, it auto-runs a reviewer mode to detect vulnerabilities, then delegates fixes to agents.
Streamlined Workflow from Prompt to Deployed Code
Install Tracer as an IDE extension (Cursor, VS Code, Windsurf) via download or store search—it opens a left-panel dashboard as your command center. Use four modes sequentially:
- Epic: Input prompt plus context (images, files); select model profile (Balance for speed/cost mix, Frontier for top-tier quality). AI iterates with you on tech stack, backend choices, generating a thorough implementation plan with mind maps, data models, user flows, and UI descriptions.
- Phases: Chat to clarify vague ideas pre-epic.
- Plan: Refine file-by-file breakdowns post-specs.
- Review: Debug issues autonomously.
Submit the questionnaire to auto-generate tickets. Enable Bart mode, tweak tickets/tech stack if needed, then /execute. It reasons via tool calling (reads specs/tickets), batches tasks, codes (e.g., full-stack dashboard with auth login, agent creation/deploy on localhost), verifies alignment repeatedly, and coordinates tools for functionality.
In a demo, a single epic prompt yielded a working dashboard: mock login, agent CRUD with model selection/functions, API integration—all scaffolded, without manual intervention beyond initial specs.
Outcomes: Production-Ready Builds Without Hype Trade-offs
You trade manual task-running for set-it-and-forget-it execution, producing refined code faster—e.g., full dashboard from prompt while 'coding crap coffee.' Free entry: run any agent tier (no Tracer lock-in). Drawbacks: still needs clear initial specs; complex epics may require mid-run steers via ticket updates. Ideal for spec-driven dev, it verifies outputs rigorously, reducing blind autonomy risks. Start free at Tracer to test on your IDE/projects.