The Manifesto
We are uncovering better ways of building systems in an era where machines can build anything — but humans must account for everything.
Intent is the primary artifact.
Implementation is a compiled derivative.
Governance is earned through the loop.
AI has not made software development less human.
It has made the human part more visible by stripping away everything that was merely mechanical. The valuable part was always the thinking — and the accountability for it.
When AI generates the implementation, the specification becomes what code used to be. You do not patch intent; you refine it. You do not debug the agent; you clarify the brief.
We Value · Over
Both sides matter. When AI can generate implementation, produce output at scale, and simulate process compliance, the left side is where human accountability is non-negotiable.
Intent
Implementation is inexpensive when AI generates it. What cannot be delegated is the decision about what to build and the accountability for that decision. If the AI produces the wrong result, the failure belongs to the person who commissioned it — not the machine that built it.
When we default to implementation-first: we build accurately but wrongly — and the accuracy of the output makes the mistake harder to detect and more expensive to correct. The agent produces precisely what was asked for. What was asked for was wrong.
Direction
Production capacity is abundant. The scarce resource is accountable judgment. Direction means choosing the right problems, defining constraints, deciding what not to build, and being answerable for those choices.
When we default to production-first: we ship quickly into drift — discovering misalignment only when users or incidents reveal what a specification would have caught before a line was generated. Speed has a direction problem. Without direction, it compounds.
Flow
The bottleneck is validation, not implementation. Value should flow continuously when validation confidence is met — not on a schedule. Every gate must earn its place. Artificial delays are waste.
When we default to release-first: we create delivery ceremonies that obscure whether value is actually flowing. A team can complete every sprint on time, ship every Tuesday, hit every velocity target, and still deliver nothing of value — because the sprint clock ran out before anyone asked whether the feature solved the actual problem.
Governance
Process compliance can be faked. Accountability cannot. Governance means active, continuous ownership of what AI systems are doing — confidence thresholds, scope limits, reasoning trace audits, drift detection. The question is never "did we follow the process?" but "is the system doing what we said it would, and do we stand behind it?"
When we default to process-first: we satisfy the procedure while the system goes ungoverned. Process compliance can be observed, audited, and certified. Accountability for AI system behavior requires more than a checklist.
The values inherit. The bottleneck moves.
DoCoDeGo does not contradict Agile's values — it inherits them and extends them into a world Agile did not anticipate. Teams practising Agile well are already close to DoCoDeGo.
Eight specific frictions →Beyond the four pillars
DoCoDeGo reflects how knowledge work has changed.
The Anti-Complexity Principle
Any addition to the framework must not increase the net ceremony burden on a team at any maturity stage unless the increase in governance burden is proportional to demonstrated AI autonomy risk at that stage.
Governance scales with autonomy, not with organizational size or headcount. A Stage 1 team faces low AI autonomy risk; their governance must be correspondingly light. A Stage 4 team operates autonomous agents with high autonomy risk; their governance is necessarily substantial.
This principle exists because complexity is commercially advantageous to consultants and naturally accretes in frameworks that lack a structural constraint against it. The principle does the structural work that good intentions alone cannot do.
What DoCoDeGo is not
- Not Not anti-Agile.
It is post-Agile. Agile solved the right problem for its era.
- Not Not a tool.
No specific AI model, platform, or vendor is required.
- Not Not a process.
It is a framework of values and principles that teams adapt to their context. There is no correct implementation of DoCoDeGo, only more or less aligned ones.
- Not Not contingent on AI being limited.
The framework assumes AI capability will continue to improve — and that human accountability for what gets built and run does not diminish as a result. The stronger the AI, the more important it is to know who decided to use it, for what, and under what constraints.
- Not Not finished.
This is a living document. Intent evolves as understanding deepens.
DoCoDeGo is an anagram of
The name is the claim. The practice is the proof.
Teams that hold DoCoDeGo write code they can stand behind — not because they followed a process, but because they knew what they were building before they built it.
"DoCoDeGo is the art. We are the artists. Art never fades."
The framework is real.
The community is forming now.
DoCoDeGo is in Alpha. The framework is documented, the practices are battle-tested at small scale, and the next release is being shaped in public.
If it produces anything, it should produce engineers and teams who think more clearly about what they are building and why.
Discord is where specs are debated, the framework gets sharper, and decisions land in writing. The conversation is the artefact.