lev-os Planning Workflow — The Foundation of Agentic Development
Core Philosophy: "Planning tokens are a lot fewer and cheaper than implementation tokens."
The models are far smarter when reasoning about a detailed plan that fits within their context window. This is the key insight behind spending 80%+ of time on planning.
Why Planning Matters
- Measure twice, cut once — becomes "Check your plan N times, implement once"
- A very big, complex markdown plan is still shorter than a few substantive code files
- Front-loading human input in planning enables removing yourself from implementation
- The code will be written ridiculously quickly when you start enough agents with a solid plan
THE EXACT PROMPT — Plan Review (GPT Pro Extended Reasoning)
Carefully review this entire plan for me and come up with your best revisions in terms of better architecture, new features, changed features, etc. to make it better, more robust/reliable, more performant, more compelling/useful, etc. For each proposed change, give me your detailed analysis and rationale/justification for why it would make the project better along with the git-diff style change versus the original plan shown below:
<PASTE YOUR EXISTING COMPLETE PLAN HERE>
THE EXACT PROMPT — Integrate Revisions (Claude Code)
After GPT Pro finishes (may take 20-30 minutes), paste output into Claude Code:
OK, now integrate these revisions to the markdown plan in-place; use ultrathink and be meticulous. At the end, you can tell me which changes you wholeheartedly agree with, which you somewhat agree with, and which you disagree with:
```[Pasted text from GPT Pro]```
Process Overview
1. INITIAL PLAN (GPT Pro / Opus 4.5 in web app)
└─► Explain goals, intent, workflows, tech stack
2. ITERATIVE REFINEMENT (GPT Pro Extended Reasoning)
└─► 4-5 rounds of revision until steady-state
3. MULTI-MODEL BLENDING (Optional but recommended)
└─► Gemini3 Deep Think, Grok4 Heavy, Opus 4.5
└─► GPT Pro as final arbiter
4. CONVERT TO BEADS (Claude Code + Opus 4.5)
└─► Self-contained tasks with dependency structure
└─► See: beads-workflow skill for task graph creation
5. POLISH BEADS (6+ rounds until steady-state)
└─► Cross-model review, never oversimplify
What Makes a Great Plan
| Good Plan | Great Plan |
|---|---|
| Describes what to build | Explains WHY you're building it |
| Lists features | Details user workflows and interactions |
| Mentions tech stack | Justifies tech choices with tradeoffs |
| Has tasks | Has tasks with dependencies and rationale |
| ~500 lines | ~3,500+ lines after refinement |
Essential Elements
- Self-contained — Never need to refer back to external docs
- Granular — Break complex features into specific subtasks
- Dependency-aware — What blocks what?
- Justified — Include reasoning, not just instructions
- User-focused — How does each piece serve the end user?
Common Mistakes
- Starting implementation too early — 3 hours of planning saves 30 hours of rework
- Single-round review — You continue to get improvements even at round 6+
- Not using GPT Pro — Extended Reasoning is uniquely good for this
- Skeleton-first coding — One big comprehensive plan beats incremental coding
- Losing context — Convert plans to beads so agents don't need the original
References
| Topic | Reference |
|---|---|
| All exact prompts | PROMPTS.md |
| Real-world examples | EXAMPLES.md |
| FAQ | FAQ.md |