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3 stars

Guido Scale – maturity model for SDD migration

by guimiran·Mar 2, 2026·2 points·0 comments

AI Analysis

MidBig Brain

CMMI extension for SDD migration, but lacks validation data and early adoption proof.

Strengths
  • Addresses a real pain: CMMI measures process but not SDD readiness—dual-axis framing is non-obvious
  • Framework separates process maturity from migration difficulty; orgs can be CMMI-3 but GUIDO-2
  • Honest caveat in submission shows self-awareness; whitepaper + assessment tooling included
Weaknesses
  • Zero adoption signal; framework published two weeks ago with no case studies, organizational validation, or evidence it predicts migration success
  • Static markdown on GitHub; lacks interactive assessment tool, scoring methodology, or consulting integration to prove utility
Category
Target Audience

Enterprise software quality/engineering leads, organizations adopting AI coding agents, transformation consultants

Similar To

CMMI · SAFe · TOGAF

Post Description

I've been working in software quality engineering for years and kept running into the same problem: organizations trying to adopt AI coding agents and failing — not because the tools were bad, but because their processes weren't ready.

CMMI measures process maturity. But it says nothing about how hard it will be to shift from code-centric to specification-centric development. Those are different questions.

So I built a 5-level framework that tries to answer both simultaneously: where you are, and how much work it will take to get to SDD with AI agents.

The levels go from GUIDO 1 (chaotic, very high migration effort) to GUIDO 5 (SDD-native, specs as living source of truth).

The key insight — which I think is non-obvious — is that you can be CMMI Level 3 and still be GUIDO 2. Process maturity and SDD readiness are not the same axis.

It includes a whitepaper, assessment folder, and real-world scenarios.

Honest caveat: this is v1.0, published two weeks ago, zero external validation so far. I'm sharing it here specifically because I want to know if this resonates with engineers who've actually tried to introduce AI agents into their dev pipelines — or if I'm solving a problem that doesn't exist the way I think it does.

What has your experience been? Did your organization skip levels and pay for it?

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