The AI First Manifesto: Principles Over Process
By Derek Neighbors on September 5, 2025
Working with organizations on AI adoption feels like deja vu. The same resistance patterns I saw during the waterfall-to-agile transformation 20 years ago.
Companies building elaborate AI governance committees. Months of planning before anyone touches an AI tool. Process paralysis disguised as “responsible adoption.”
Here’s what I learned from agile: Values trump processes every single time.
The Agile Manifesto didn’t succeed because it had better processes. It succeeded because it established clear values that guided decision-making without requiring permission. It gave teams principles they could apply in any situation.
AI transformation needs the same thing. Not more governance committees. Clear principles about human-AI collaboration.
This is my attempt at providing that foundation.
The Transformation Pattern
Every major technology shift follows the same pattern. New capability emerges. Organizations see the potential. Then they immediately try to control it through familiar processes.
I watched this with agile development. Companies wanted the benefits of faster software delivery, but they couldn’t let go of their waterfall planning processes. They created “agile governance committees” and “sprint approval workflows.”
I remember one CTO who spent six months building an “agile readiness assessment framework” while his competitors shipped three major product releases. His team sat in planning meetings discussing their planning meetings. When I asked why they weren’t just… building software, he said they needed to “ensure agile compliance first.”
I watched brilliant engineers slowly lose their edge. They stopped making decisions. Stopped taking initiative. They’d been trained to wait for permission to think. Six months later, half the team had quit for companies that actually shipped products.
They missed the point entirely.
Agile worked because it established values that guided behavior: “Individuals and interactions over processes and tools.” “Responding to change over following a plan.” Simple principles that eliminated the need for elaborate governance.
Now I’m watching the same pattern with AI adoption.
Organizations see competitors shipping AI-enhanced products daily. They want that capability. But instead of establishing values about human-AI collaboration, they’re building governance frameworks that slow everything down.
Just last month, I watched a Fortune 500 company spend eight weeks debating whether employees could use ChatGPT for email drafts. Eight weeks. While they debated, their startup competitor launched an AI-powered feature that captured 15% market share.
The Fortune 500 company had 47 people in their AI governance committee. The startup had two values: “AI amplifies human judgment” and “Learn by doing.”
Guess which approach attracted the best talent? Guess which team worked weekends because they believed in what they were building?
They’re trying to process their way to transformation. It never works.
What’s Missing Now
The problem isn’t that organizations don’t understand AI’s potential. They do. The problem is they’re approaching AI adoption the same way they approach every other technology initiative, through process and control.
But AI is different. It’s not just another tool you deploy. It’s a fundamental shift in how work gets done. It requires new ways of thinking about capability, collaboration, and decision-making.
You can’t govern your way to breakthrough thinking.
What organizations need are foundational values about human-AI collaboration. Principles that help people make good decisions about AI usage without requiring permission for every interaction.
That’s what this manifesto provides.
The AI First Manifesto
We are discovering better ways of building organizations by partnering with artificial intelligence and helping others do the same. Through this work we have come to value:
Leverage over Skill
Experimentation over Permission
Openness over Protection
Amplification over Replacement
Collaboration over Control
That is, while there is value in the items on the right, we value the items on the left more.
Let me break down what each of these means in practice.
Leverage over Skill
Individual skill is valuable. Expertise matters. Years of experience create judgment that can’t be replicated overnight.
But when you multiply that skill through AI, you get something exponentially more powerful.
The person who combines their expertise with AI capability will outperform the person who relies on expertise alone. Every time.
This isn’t about replacing human skill. It’s about choosing to amplify it through AI rather than limiting yourself to what you can accomplish alone.
Experimentation over Permission
Planning without action is procrastination with a business plan.
Perfect information is a fantasy. While you’re chasing it, reality moves on without you.
I learned this the hard way early in my career. I spent months building the “perfect” requirements document for a software project. Interviewed every stakeholder. Documented every edge case. Created beautiful process flows.
By the time we started building, the market had shifted. Our perfect plan was perfectly useless.
The organizations winning with AI are the ones that start using it immediately and learn through practice. They experiment with new capabilities frequently. They trust their people to make good decisions about AI tools without requiring approval for every interaction.
They choose learning by doing over waiting for permission.
Openness over Protection
Your existing processes aren’t sacred. They’re habits that used to work.
When AI offers fundamentally better approaches, protecting the old way isn’t prudence. It’s fear dressed up as wisdom.
AI-first organizations stay open to changing their methods when AI offers better approaches. They welcome disruption as competitive advantage rather than seeing it as a threat to defend against.
They choose growth over defensiveness.
Amplification over Replacement
The fear that AI will replace human judgment is understandable. It’s also the wrong frame.
The choice isn’t between human intelligence and artificial intelligence. It’s between enhanced human capability and limited human capability.
AI-first organizations choose to amplify human judgment through AI rather than trying to replace human decision-making entirely. They understand that the best results come from humans and AI working together, not from either working in isolation.
They choose enhancement over replacement.
Collaboration over Control
Control is an illusion. You never had as much control as you thought you did.
With AI, that illusion becomes expensive. The energy you spend trying to control outcomes is energy not spent creating them.
The hardest part of embracing AI isn’t learning the technology. It’s letting go of the illusion that you can control outcomes through process. I still catch myself wanting to create the “perfect prompt template” instead of just… talking to the AI and seeing what happens.
That discomfort you feel when you can’t predict exactly what AI will produce? That’s where breakthrough thinking lives.
AI-first organizations work with AI as a collaborative partner, not as a tool they must completely control. They build processes that assume AI collaboration rather than processes that restrict AI usage.
They choose partnership over micromanagement.
The Principles Behind the AI First Manifesto
We follow these principles:
-
Our highest priority is multiplying human capability through AI leverage, not perfecting individual skills alone.
-
We start using AI tools immediately and learn through practice, rather than waiting for perfect training or approval.
-
We welcome AI disruption to current methods, seeing change as competitive advantage rather than threat.
-
We choose AI enhancement of human judgment over AI replacement of human decision-making.
-
We work with AI as a collaborative partner, not as a tool we must completely control.
-
We measure success by what we accomplish with AI, not by how well we work without it.
-
We experiment with new AI capabilities frequently, from daily tasks to strategic decisions.
-
We build processes that assume AI collaboration, not processes that restrict AI usage.
-
We trust AI-augmented individuals to make good decisions without requiring permission for every AI interaction.
-
We stay open to changing our methods when AI offers better approaches, rather than protecting existing workflows.
-
The best results emerge from humans and AI working together, not from either working in isolation.
-
We regularly reflect on how to improve our AI collaboration and adjust our approach based on results, not theory.
These principles address the specific resistance points I see in organizations:
- Fear of losing control (principles 5, 8)
- Perfectionism paralysis (principles 2, 7, 9)
- Protecting existing methods (principles 3, 10)
- Replacement anxiety (principle 4)
- Individual expertise ego (principles 1, 6, 11)
Why This Matters Now
Organizations are at a crossroads. They can either embrace AI-first transformation or get left behind by competitors who do.
The choice isn’t really about technology. It’s about values.
Do you value process over principles? Control over collaboration? Protection over adaptation?
The organizations that choose the left side of this manifesto will build the future. The ones that don’t will become case studies in how breakthrough technologies get neutered by bureaucracy.
What This Changes
For Leaders: You get clear values that guide AI decisions without requiring endless committees and approval processes. Instead of asking “What’s our AI governance policy?” you ask “What do our values tell us about this AI decision?”
For Teams: You stop asking permission and start making decisions. You can experiment with AI tools because you understand what the organization values, not because you’ve navigated the approval maze.
For Organizations: You build capability instead of committees. You move fast because people know what matters, not because you’ve optimized your bureaucracy.
The Implementation Reality
This isn’t theoretical. Here’s how to use this manifesto:
Start with Values: Share these five values with your team. Discuss what each one means in your specific context. Get alignment on what you’re choosing to value more.
Test the Principles: Use the 12 principles to guide specific AI adoption decisions. When someone asks “Should we use AI for this?” refer to the principles instead of creating a new approval process.
Measure by Outcomes: Stop measuring how well you follow process. Start measuring how much you accomplish. Ask “Are we multiplying human capability?” not “Are we following the AI governance framework?”
The goal isn’t to eliminate all process. It’s to establish values that make most processes unnecessary.
The Series Culmination
This manifesto represents everything we’ve explored throughout this AI First series:
Identity transformation requires new values about capability and collaboration. You can’t think AI-first while holding onto pre-AI values.
Collaborative architecture emerges from principles about human-AI partnership. Technical design follows from value decisions.
Organizational scaling happens when everyone shares the same values about AI adoption. You don’t need to manage what people naturally do based on shared principles.
Cultural transformation is fundamentally about changing what you value. Culture follows values.
Leadership evolution means modeling these values in your own AI usage. You lead AI transformation by embodying AI-first principles.
The manifesto distills all of this into actionable values and principles that any organization can adopt.
Final Thoughts
The Agile Manifesto transformed software development by establishing clear values over rigid processes. It gave teams permission to make good decisions without requiring approval for every choice.
The AI First Manifesto does the same for organizational transformation in the age of artificial intelligence.
Values trump processes every single time.
When you establish clear principles about human-AI collaboration, you eliminate the need for elaborate governance frameworks. People make good decisions because they understand what matters.
When you don’t establish those values, you get governance committees and approval workflows. You get talented people leaving for companies that trust them to think. You get left behind while competitors ship AI-enhanced products.
The organizations that embrace these principles will build the future. The ones that don’t will become case studies in how breakthrough technologies get neutered by bureaucracy.
But here’s what I really want you to understand: If your team still needs permission to experiment with AI, you’re not transforming. You’re managing the status quo in a new wrapper.
You’re that CTO building agile readiness frameworks while competitors ship products.
Stop building AI governance committees. Start building AI capability. Pick one process document that’s slowing down AI adoption and scrap it this week. Replace it with a principle.
The choice is yours. But choose quickly. The AI-first transformation is happening with or without you.
What AI governance process in your organization could be replaced with a principle this week? Start there.
Ready to replace governance committees with actual capability? Vibe Alliance helps leaders implement AI-first transformation through principles, not process documents.
