The 10-20x Methodology for AI-Accelerated Software Development
"Stream coding isn't about faster coding. It's about documentation so clear that code writes itself."
AI tools promise 10x productivity. GitHub Copilot, Cursor, Claude Code—they make coding 55% faster.
But projects still take the same time to ship.
Why? Because faster typing doesn't solve:
- Strategic decisions AI can't make for you
- Context that gets lost between prompts
- Technical debt created at 10x speed
This gap between task velocity and project velocity is the Velocity Mirage.
Stream Coding is a documentation-first methodology that makes AI-generated code deterministic.
The 40/40/20 Split:
- 40% Strategic Thinking (Phase 1) — Solve hard problems before coding
- 40% AI-Ready Documentation (Phase 2) — Specs so complete AI has zero decisions
- 20% Execution + Quality (Phases 3-4) — Code streams out automatically
Real Results (5Levels Case Study):
- 7 production modules in 4.5 hours
- 46 intelligence endpoints (77 total backend API)
- Zero bugs in generated code, 21 minutes average per tested module
Note: The case study focuses on backend intelligence modules—Stream Coding's sweet spot. For frontend, use the methodology for behavior (components, state, logic) and complement with AI design tools for visuals. See Chapter 4 for details.
The SKILL.md file is designed for Claude's Skills feature.
How to use it:
- Claude Web/Desktop: Upload via Skills interface (Settings → Features → Skills)
- Claude API: Use the Agent Skills API to load the skill programmatically
- Claude Projects: Alternative—add to project knowledge. Claude will search it when needed, though Skills provide better integration.
For other AI editors: SKILL.md uses Claude-specific formatting (progressive loading, YAML frontmatter). If you're using Cursor, Windsurf, or other tools, you'll need to adapt it:
- Extract core principles (Phase structure, Document Types, Clarity Gates)
- Create a condensed version for your
.cursorrulesor project settings - The full methodology lives in the manifesto chapters—use those as reference
What it does: When loaded as a Claude Skill, it gives Claude the complete Stream Coding framework as a persistent reference. Claude will recognize your documentation structure, understand which phase you're in, and apply appropriate rigor.
The methodology itself is tool-agnostic. The SKILL.md is just the Claude-optimized implementation.
The /manifesto folder contains the complete methodology:
| Chapter | Topic |
|---|---|
| Chapter 1 | The Velocity Mirage |
| Chapter 2 | Why AI Tools Alone Fail |
| Chapter 3 | The Missing Middle |
| Chapter 4 | The 4-Phase Methodology |
| Chapter 5 | Day 2 & The Rule of Divergence |
| Appendix A | Templates & Checklists |
| Appendix B | Research & SDD Positioning |
| Appendix C | 5Levels Case Study (Git-Verified) |
| Advanced Framework | Document Architecture (v3.3) |
The /templates folder contains ready-to-use frameworks:
- Strategic Blueprint — Answer the 7 Phase 1 Questions
- ADR Template — Document architecture decisions with rationale
- Clarity Gate Checklist — The mandatory Phase 2→3 gate
"When code fails, fix the spec—not the code."
Traditional development iterates on code. Stream Coding iterates on documentation.
Every manual code edit without updating the spec creates Divergence—technical debt that breaks the stream. The methodology works because it treats code as a compiled output of documentation, not the source of truth.
✅ Technical founders building greenfield products
✅ Solo developers and small teams (1-5 people)
✅ Anyone tired of AI-generated spaghetti code
✅ Backend/business logic focused (see Chapter 4 for frontend approach)
❌ Not for large enterprises (see GitHub Spec-Kit, Tessl, Kiro)
❌ Not for hackathons or throwaway prototypes
❌ Not for teams who can't commit to documentation-first
Stream Coding aligns with industry research:
- McKinsey (2025): Top performers see 16-30% productivity gains through "end-to-end PDLC implementation" and "structured communication of specs"
- DORA (2025): 7.2% delivery instability increase for every 25% AI adoption without foundational systems
- METR (2025): Developers 19% slower with AI despite feeling 20% faster
The methodology isn't magic, it's systematic application of spec-driven development at founder scale.
Stream Coding is open source under CC BY 4.0. You're free to use, adapt, and share with attribution.
Found an improvement? Open an issue or PR.
Created by Francesco Marinoni Moretto while building 5Levels, a LinkedIn relationship intelligence platform.
The methodology emerged from building 7 production modules in 4.5 hours, and documenting exactly how.
CC BY 4.0 — Use freely with attribution.
"Stream Coding methodology by Francesco Marinoni Moretto (github.com/frmoretto/stream-coding)"
In memory of my beloved father Guido