Turn one raw idea into a structured company decision flow:
- research before optimism
- department debate before commitment
- board verdict before execution
- intervention-driven replanning when assumptions change
Most AI tools give you one polished answer.
TOBECEO gives you a process:
- Research
- Department plans
- Cross-department roundtable
- Synthesis
- Board decision with scorecard
You can chat with agents at any stage and promote important chat turns into formal interventions.
- Web Console at root path
- Flask API for project, planning, timeline, diff, and chat
- CLI for quick local planning drafts
- Persistent project/task state with SQLite
- Chinese and English conversation modes
- Stage history replay and employee-level roundtable logs
- founders pressure-testing early ideas
- product teams evaluating strategic bets
- accelerators and startup programs
- builders who want structured pushback, not generic encouragement
python -m pip install -e .[dev]
tobeceo-api
Open:
tobeceo-plan "AI copilot for independent gyms" \ --summary "Help gym owners automate retention and upsell workflows." \ --constraint "Keep CAC under control" \ --metric "Monthly retention > 90%"
curl -X POST http://127.0.0.1:8000/api/projects \ -H "Content-Type: application/json" \ -d '{ "title": "AI interviewer for junior candidates", "summary": "Automated pre-screening with role-specific rubrics.", "constraints": ["Avoid biased scoring"], "metrics": ["Interview completion rate > 70%"], "language": "en-US" }'
curl -X POST http://127.0.0.1:8000/api/planning/generate \ -H "Content-Type: application/json" \ -d '{"project_id":"<PROJECT_ID>"}'
Call generate repeatedly to move through stages.
curl -X POST http://127.0.0.1:8000/api/projects/<PROJECT_ID>/chat \ -H "Content-Type: application/json" \ -d '{"agent":"research", "message":"What is the biggest go-to-market risk?"}'
curl "http://127.0.0.1:8000/api/projects/<PROJECT_ID>/plans/diff?from=<V1>&to=<V2>"researchdepartment_designroundtablesynthesisboard
The scorecard and recommendation are produced at the board stage.
Screenshot 1 Screenshot 2 Screenshot 3
Optional environment variables:
IBC_HOSTdefault127.0.0.1IBC_PORTdefault8000IBC_DATA_DIRdefault.dataIBC_LLM_API_KEYIBC_LLM_BASE_URLIBC_LLM_MODELIBC_LLM_TIMEOUT_SECONDSdefault45
Without LLM config, the app still runs in deterministic demo mode.
This repo includes Render deployment support via render.yaml.
- Stronger board debate mechanics
- Checkpoint-aware selective recomputation
- Multi-user auth and workspace isolation
- Managed DB option for production
- Automated quality regression evaluation
Issues and pull requests are welcome.
If you want to contribute quickly, start with:
- new domain test cases
- better intervention heuristics
- richer board scoring dimensions
- UX improvements for plan diff and timeline views
Apache-2.0