AI at the Core vs AI at the Edge

Move AI from edge to core: make models the primary logic layer, with code orchestrating prompts, tools, and safeguards.

Sep 29, 2025 0m 29s

Oji Udezu

Expert Insights

Oji argues that the real shift isn't “Agile vs. not, it's AI at the core vs. AI sprinkled on top. When models become the engine, development goes super-speed, scope gets managed differently, and teams must deliver outcomes, not ingredients.

Hear Oji explain:

Why the old Agile playbook breaks in a world where dev moves 10× faster, and why we need a new shared language for building.
How AI-at-the-core (not the edge) lets teams ship end-to-end outcomes instead of dashboards and docs.
What it means to win differently with infinite personalization across product and growth, plus the new KPIs.

AI at the core is when you build with your model at the core, when like more than 50% of your code base is model based... Because what models are essentially is a large block of code you can direct. Versus you need to write because it knows the world so well that all the if then statements are built into it already.

— Oji Udezu, Co-Author, ProductMind

THE NEW DEFAULT angle

Here’s how to prepare your team for the shift toward model-driven development:

Reframe coding logic. Move from explicit instructions to model-guided code flows.
Invest in model-based development skills. Equip your team to handle an AI-heavy codebase.
Anticipate efficiency gains. Leverage AI’s built-in conditional logic for faster outcomes.
Redefine team roles. Adapt dynamics to align with a software stack where AI is the core engine.