MANGROVE

THE

MANGROVEMANIFESTO

AI commoditised both the production and the knowledge of software engineering.
What remains scarce is domain knowledge, judgment, and context.

01

Working code
over artefacts

PROCESS

02

Full context
over coordination

ORGANISATION

03

Accountability
over estimation

CONTRACT


01 / The Root

One thing changed.

AI commoditised both the production and the knowledge of software engineering.

Two dimensions. Both matter.

PRODUCTION CAPACITY

Building is cheap

AI writes code fast. What took a team weeks takes hours. The raw cost of turning an idea into working software collapsed. This is the dimension most people notice first.

ACCUMULATED KNOWLEDGE

Expertise is abundant

AI knows every architecture, every language, every design pattern, every security vulnerability, every testing strategy, every deployment pattern. It has read, effectively, every technical book ever written.

What remains scarce.

Domain knowledgeUnderstanding THIS business, THIS problem, THIS customer
JudgmentDeciding what matters, what to prioritise, when to stop
ContextUnderstanding THIS system, THIS market, THIS moment
TasteKnowing what "good" looks like for THIS situation

The human's role isn't “person who writes code with AI help.”

It's “person with domain judgment directing an AI that has comprehensive technical knowledge.”


02 / The Consequence Tree

Everything else is derivative.

First, second, and third-order consequences — traced to their root.

FIRST ORDER

The bottleneck shifted to direction and comprehension

2NDArchitecture judgment becomes the highest-leverage activity — AI amplifies good decisions and bad ones equally
2NDSecurity and quality become built-in, not bolted on — they’re just more code
2NDLegacy systems become comprehensible — AI can read, analyse, and explain any codebase
2NDDue diligence goes deeper — AI-generated code needs experienced judgment to evaluate
3RDExperience matters more, not less — a junior directing AI gets correct code that misses the point
3RDThe CTO role shifts from managing builders to directing strategy
FIRST ORDER

One person + AI replaces a team

2NDDelivery cost drops — fewer people, less coordination, faster cycles
2NDFull system context in one mind produces more coherent architecture
2NDScale through domain experts owning bounded contexts, not headcount
3RDOne person can hold an entire legacy system and plan the migration path
3RDIntegration complexity reduces — one mind understands both sides of the connection
FIRST ORDER

Iteration becomes nearly free

2NDExplore by building, not planning — the prototype is the spec
2NDTests, docs, security come free — they’re just more code
2NDCommitment is possible — scope is knowable through building
3RDFixed price becomes honest — T&M loses its rationale
3RDThe iron triangle dissolves — quality rises without trade-off
3RDDiscovery is faster AND more thorough — AI brings knowledge to exploration

03 / Three Values

Three root values.

Each addresses a different domain. Everything else derives from these.

01

PROCESS

Working code over artefacts

The foundational shift. Building is the discovery. When a working prototype costs less than the meeting to discuss the specification, the spec becomes the build. But it goes deeper: artefacts didn’t just exist because building was expensive. They existed to transfer knowledge between people — architecture documents shared decisions, coding standards ensured consistency, design reviews transferred expertise. If AI holds that knowledge and one person directs, the transfer function of these artefacts disappears too.

Replaces: spec-first development, knowledge-transfer documents, design-by-committee

02

ORGANISATION

Full context over coordination

The human’s value isn’t technical knowledge anymore — AI has that. The human’s value is domain knowledge and judgment. One experienced engineer who understands the business problem, directing AI with comprehensive technical knowledge, is a more capable unit than a team of specialists. AI’s knowledge is broader than any individual specialist’s, and one mind’s judgment is more coherent than a committee’s. This is why experience matters more, not less. AI amplifies judgment. A junior directing AI gets technically correct code that misses the point.

Replaces: Scrum ceremonies, specialist silos, knowledge as competitive advantage

03

CONTRACT

Accountability over estimation

When building is cheap, commitment is honest. T&M contracts existed because uncertainty was genuine — nobody could predict what building would cost. Now discovery is faster and more thorough: AI brings knowledge to exploration, knows what questions to ask, what patterns apply, what risks to flag. You build to discover scope, then commit to delivering it. Fixed price becomes honest. The buyer gets what the original Agile Manifesto promised but rarely delivered: real accountability.

Replaces: T&M billing, estimation theatre, scope creep as business model


04 / What It Means

What this means for you.

BUYER

If you’re buying software

  • Demand working prototypes before committing budget, not slide decks
  • Expect fixed-price commitments based on proven scope
  • Look for partners who demonstrate, not who present
  • Your leverage increased — building is cheap, mediocre isn’t acceptable
BUILDER

If you’re building software

  • Your value is domain knowledge and judgment, not keystrokes or technical trivia
  • AI amplifies good architecture and bad equally — your judgment is the filter
  • Experience matters more, not less — a junior gets correct code that misses the point
  • Ship working software early — the cost of being wrong is a conversation, not a quarter
LEADER

If you’re running a team

  • One person with full context + AI outperforms a coordinated team with fragments
  • Process overhead has a new, much lower, break-even point
  • Hire for judgment and domain depth, not just technical skill
  • The org chart that made sense when building was expensive may not make sense now

The problems haven't changed.
The economics of solving them have.

AI commoditised both the production and the knowledge of software engineering.
Three values capture what that means. Everything else is commentary.


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