The real AI revolution isn't about the technology. It's about who you become when you stop fighting it and start forging yourself in its fire.
AI First Manifesto
Beyond vibe coding to systematic AI-first product development philosophy
61 minutes total reading
Series Posts
Complete
Most leaders add AI tools to human workflows. The breakthrough is designing collaboration architecture where human judgment and AI capability compound each other from the ground up.
Scaling AI First isn't 'more tools for more teams.' It's mode discipline, runnable playbooks, and iteration systems that make capability compound across functions.
Culture doesn't just eat strategy for breakfast. Culture will devour your AI transformation, shit out the bones, and ask for seconds.
Most leaders want AI transformation results without undergoing the leadership metamorphosis it requires. Here's what AI-first leadership actually demands.
Working with organizations on AI adoption feels like deja vu. The same resistance patterns I saw during the waterfall-to-agile transformation. What made agile successful wasn't better processes, it was establishing clear values. AI transformation needs the same thing.
Frequently Asked Questions
What does AI First actually mean?
A values-driven approach that designs work around human-AI partnership from the start. It changes identity, workflows, and decisions so capability compounds, not just tool usage.
How is AI First different from 'using AI tools'?
Tools get added to old workflows. AI First redesigns collaboration architecture with clear rules for who leads when, results-first workflows, and iteration systems that improve both humans and AI.
What is collaboration architecture?
A structured design across three layers: collaboration rules (human-led, AI-led, collaborative), outcome engines that prioritize results over comprehension, and feedback forges that compound learning each cycle.
How do we scale AI First across the organization?
Standardize modes, package wins as runnable playbooks, and install a cadence. Publish a mode map, one KPI, evaluation rubrics, and a weekly generate-evaluate-iterate-scale loop.
What cultural shifts are required for AI First?
Make avoidance more costly than adoption, measure what threatens resistance, align incentives so AI-assisted work becomes the baseline, and tie advancement to AI fluency.
What does AI-first leadership require?
Model the change: learn in public, trade control for trust, treat failures as intelligence, and lead through principles rather than process approvals.
What are the AI First Manifesto values?
Leverage over Skill, Experimentation over Permission, Openness over Protection, Amplification over Replacement, Collaboration over Control. Principles guide decisions faster than governance.
How do we start in 30 days?
Pick one workflow. Write the mode map, define one KPI, build a results-first workflow, run weekly cycles, and publish the playbook when the numbers move.
How do we measure ROI of AI First?
Cycle-time, time-to-first-output, DORA metrics, CSAT, win rate, close time, month-end close, exception ratio trend, playbooks adopted, and percent of AI-assisted work.
What failure modes should we avoid?
Vibe coding, committee paralysis, tool dumping without standards, perfectionism over iteration, and micromanaging AI instead of collaborating.
What order should I read the series?
1) Identity Revolution, 2) Collaboration Architecture, 3) Scaling Collaboration, 4) AI First Culture, 5) AI-First Leadership, 6) Principles Over Process.
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