The Provenance Manifesto
10-Minute Meetup Version
Topic: Decision provenance in the age of AI
Format: Compressed Markdown deck
Goal: Explain the idea, value, and principles in a short live talk
Slide 1
The Provenance Manifesto
Decision provenance in the age of AI
Addressing organizational context amnesia through the art of provenance.
"The history of every decision is the architecture of our future."
Slide 2
About Me
My name is Yauheni Kurbayeu.
- software engineering leader with decades of experience building and operating complex systems
- experienced in managing large engineering teams
- worked on enterprise platforms, large-scale SaaS products, and distributed engineering organizations
- increasingly focused not only on how systems are built, but on how the decisions behind them are made, preserved, and evolved
Provenance is an exploration of that idea.
Slide 3
The Problem
Software teams preserve:
- code
- tickets
- deployments
- infrastructure
- documentation
But they rarely preserve:
- why a decision was made
- which trade-offs were accepted
- which assumptions shaped it
- who owned it
We keep the artifact. We lose the reasoning.
Slide 4
Why This Matters Now
For a long time, this was a delivery problem.
Now AI is turning it into a governance problem.
AI is making the "what" cheaper:
- code
- plans
- architectures
- outputs
So the "why" becomes more valuable:
- intent
- constraints
- accountability
- decision ownership
AI accelerates execution. Provenance preserves accountability.
Slide 5
The Core Idea
Decisions should become first-class artifacts.
A meaningful decision should preserve:
- the problem
- the context
- the assumptions
- the alternatives
- the reasoning
- the owner
- the later evolution
Decision provenance explains why a system exists in its current form.
Slide 6
What Provenance Changes
It moves us:
- from undocumented intuition to traceable decisions
- from private memory to institutional memory
- from hidden assumptions to transparent reasoning
- from static documentation to evolving decision history
- from uncontrolled automation to governed human-AI collaboration
This is not just better documentation. It is a memory layer for reasoning.
Slide 7
The Principles
- Decisions are first-class artifacts
- Decisions must carry context
- Decisions evolve but are never erased
- Decisions must be queryable
- Decisions must be attributable
- AI must operate within decision governance
- Institutional memory is a strategic asset
Memory compounds.
Slide 8
The Value
Decision provenance helps organizations:
- reduce rework and repeated rediscovery
- onboard people faster
- make architectural change safer
- expose hidden assumptions
- improve incident, audit, and compliance reasoning
- give AI access to the reasoning layer, not only the artifact layer
The more AI generates, the more provenance matters.
Slide 9
What This Looks Like In Practice
Start by preserving major decisions around:
- architecture trade-offs
- scope and product choices
- incident responses
- policy and risk boundaries
- AI-assisted implementation plans
For each important decision, capture:
- why it was made
- what alternatives were considered
- what assumptions and risks existed
- who owns it
- how it changed over time
Slide 10
The Real Shift
The hardest part is not technical.
It is cultural.
Provenance is a mindset shift:
- decisions should not disappear into conversations
- reasoning should not remain private
- AI should not operate outside visible governance
Provenance is not primarily about tools. It is about how organizations remember.
Slide 11
Closing
The real divide is not:
- human-written vs AI-generated
The real divide is:
- opaque outputs vs traceable reasoning
If we cannot reconstruct how a conclusion was formed, then even a polished result is still just a well-presented guess.
Discussion
- Where does your organization lose decision context today?
- Which decisions are most worth preserving?
- How should AI participate in governed organizational memory?