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Is AI actually coming for your job, or is it just the most powerful lever for human growth we’ve ever seen?
I explored this and much more in a fascinating podcast with Chris Meah. Watch or listen to get the full picture.
Chris is an entrepreneur, educator, and founder of School of Code and Mia Labs. we discussed the reality of navigating the "cliff edge" of automation. His philosophy? AI should make us more human, not less.
Chris’s advice for leaders? Stop trying to predict every outcome. Give your teams a license and a sandbox to experiment, and let them find the value on the ground.
After exploring these ideas and more with Chris, it became very clear that the future isn't about AI vs. humans. It's about supercharging humans to solve bigger, more meaningful problems.
The Architecture Behind AI-Native Revenue Automation
In our new white paper, The Architecture Behind AI-Native Revenue Automation, Tabs CTO Deepak Bapat breaks down what it actually takes to apply AI to revenue workflows without breaking the books.
You’ll learn why probabilistic reasoning isn’t enough for finance, how Tabs pairs LLMs with deterministic logic, and why a unified Commercial Graph is the foundation for scalable, audit-ready automation. From contract interpretation to cash application, this paper goes deep on where AI belongs—and where it absolutely doesn’t.
If you’re evaluating AI for billing, collections, or revenue operations, this is the architecture perspective most vendors won’t show you.
Key Themes
The Transition from Fear to FOMO: Leaders have switched from being apprehensive about AI to having a fear of missing out (FOMO) resulting in board-level pressures to have an AI strategy.
AI Literacy as a Decision-Making Tool: Leaders do not need deep technical expertise but rather AI literacy, an intuitive understanding of what the technology is and its purpose.
Focus on What Won’t Change: Rather than chasing every technological shift, organisations should identify what will not change for their customers (e.g., the need for faster service or human connection) and use AI specifically to facilitate those core values.
The 0% to 80% Rule: Don’t obsess about forcing AI to do 100% of a task. The real value is using AI to take tasks you were previously doing at 0% and accelerating them to 80%.
The Senior Chef Mindset: As AI handles the syntax of our work (like coding or writing), our value shifts to taste. We need to be like senior chefs knowing what good looks like, a skill that requires human experience and judgment.
Top Lessons for Leaders
Simplify your toolkit: You don't need 1,000 different AI tool subscriptions. Chris himself shed 95% of his tools, focusing on core models like Claude and Gemini to avoid "analysis paralysis".
Embrace the "Tortoise and Hare" mindset: You can only be a "hare" (staying on the bleeding edge) in one or two directions. Make sure those directions are where your competitive advantage lies.
Building Intuition: Chris argues that leaders don't need to be coders; they need "AI literacy" to build an intuitive understanding of the tools to make decisions at pace.
Focus on Growth, Not Just Efficiency: Use AI to free people from low-value tasks so they can pour effort into high-value, culture-driven growth
That’s it for this edition, for more delivery leadership insights, subscribe to the Change Leaders Playbook podcast series on Youtube, Spotify, Apple and Audible.
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