How we restructured Airtable’s entire org for AI | Howie Liu (co-founder and CEO)
1. Re-found Mission AI-Native
If your existing company cannot execute its mission with a fully AI-native approach, consider selling it and starting a new, AI-native version of that mission.
2. Clean Slate AI Mission
For existing companies, take a clean-slate approach to your mission by imagining how you would execute it using a fully AI-native approach if starting from scratch today.
3. CEOs: Become ICs Again
CEOs should revert to an “ICCO” (Individual Contributor CEO) role by getting hands-on, building, and leading initiatives, especially in the AI era, to understand product details intimately.
4. Structure for Fast & Slow AI
Restructure your company into a “fast-thinking group” for rapid AI capability development and a “slow-thinking group” for deliberate, foundational work, to accelerate AI investments and ensure durable growth.
5. Embrace AI-Native Urgency
Adopt the intensity and urgency of an AI-native company, constantly asking if you are executing as fast and leveraging new capabilities as effectively as they are.
6. Aggressively Invest in AI Compute
Aggressively invest in AI compute cycles for high-value problems, even if seemingly costly, because the strategic insights gained can provide invaluable returns.
7. Break Down Role Silos
Break down role silos across all departments (e.g., marketing, sales) by encouraging individuals to become more “full stack” and outcome-oriented, reducing dependencies and increasing self-sufficiency.
8. Cultivate Hybrid Unicorn Skills
Encourage product managers, engineers, and designers to develop cross-functional skills, becoming “hybrid unicorn types” who can understand and contribute to adjacent disciplines.
9. Baseline Proficiency in All Roles
Aim to be at least “minimally good” at all three core product development roles (PM, engineering, design), even if specializing in one, to foster a multidisciplinary approach.
10. Embrace Growth Mindset in AI
Individuals across all roles (PM, engineering, design) should embrace a growth mindset and proactively learn new skills to become more effective and versatile in the AI era.
11. Stay Connected to Product Details
As a founder or leader, prioritize staying connected to the product details and the core work you love, even as responsibilities expand, to maintain passion and drive.
12. Explore AI Products & Side Projects
Continuously use a wide range of AI products (even outside your company’s offerings) and create small side projects to gain experiential understanding of new capabilities and form factors.
13. Experience New AI Releases
Stay constantly abreast of new AI product releases and capabilities by experiencing them directly, as the pace of innovation is weekly, not yearly.
14. Approach AI with Play & Curiosity
Encourage a mindset of “play” and curiosity when exploring AI tools, rather than just checking a box, to foster deeper learning and discovery.
15. Build Fun & Useful Projects
Choose personal or work projects that are both useful and enjoyable to build, as this intrinsic motivation will drive deeper learning and skill development in AI tools.
16. Build Your Own Projects
To truly learn and develop product sensibilities, actively engage in building your own projects through trial and error, rather than just observing others’ work.
17. PMs: Become Hybrid Prototypers
Product Managers should develop hybrid skills, becoming prototypers with strong design sensibilities to thrive in the AI era.
18. Prioritize Interactive AI Demos
Prioritize interactive prototypes and demos over static decks or PRDs when evaluating AI product ideas, as the real proof and feel of an AI product comes from direct interaction.
19. Embrace AI Experimentation & Iteration
Shift from deterministic, timeline-driven execution to a model of constant experimentation and iteration, especially for AI product development.
20. Start with Vibes, Not Evals
For novel AI product experiences, prioritize “vibes” (open-ended, broad testing) over formal evals initially, to discover what works and understand the range of possibilities before narrowing down.
21. Use Evals for Iterative Improvement
Once a product’s basic form factor and core use cases are established, use evals for iterative improvement and empirical testing (like A/B testing) to refine performance.
22. Ship Rapidly, Cohesively
Ship major new product capabilities on a near-weekly basis, aiming for a cohesive product experience that moves at a breakneck pace, like AI-native companies.
23. Block Time for AI Play
Encourage employees to block out dedicated time (a day or a week) to play with various AI products relevant to the company’s domain, fostering curiosity and learning.
24. Reduce Standing 1-on-1s
Reduce standing one-on-one meetings to free up time for more timely, urgency-driven, and insight-informed discussions, fostering agility and responsiveness.
25. Prioritize Urgency-Driven Meetings
Prioritize meetings that are urgency-driven and informed by timely, high-value insights (“real alpha”) to maximize their impact and avoid unproductive discussions.
26. Sell If No AI Advantage
If your existing product or business doesn’t offer a clear advantage for an AI-native approach to your mission, consider selling the company and re-founding the mission with a fresh, AI-native start.
27. Use AI as an Expert Tutor
Leverage AI tools like ChatGPT as an “expert tutor” for learning new skills (e.g., software engineering, design), asking open-ended questions to understand how to build things.
28. Cultivate Humility & Gratitude
Approach life and work with a spirit of humility and gratitude, as this mindset fosters open-mindedness, attracts opportunities, and can become a self-fulfilling prophecy for positive outcomes.