Are AI coding tools actually replacing programmers, or just changing how software gets built? In this episode of Hidden Layers, Ron Green sits down with Dr. ZZ Si and Michael Wharton to unpack what has shifted with modern coding agents, what has not, and where the hype breaks down.
They share concrete examples from their own workflows, including how coding tools have moved from autocomplete to handling larger chunks of work, and why the real bottleneck is no longer writing syntax, but defining intent, architecture, and product direction. The conversation also explores how these tools are reshaping team velocity, why senior engineers tend to get more leverage from AI than junior developers, and the risks of weakening the talent pipeline if companies stop investing in early-career engineers.
The episode closes with a candid look at what skills will matter most in an AI-assisted world, how abstraction layers are changing the role of programmers, and whether we may already be near peak computer science graduates.
00:00 – The rise of AI coding tools
03:07 – How workflows are changing
06:27 – Team velocity and delivery speed
08:19 – Product thinking vs. engineering execution
09:46 – Is programming actually dying?
11:41 – What “programming” means now
15:23 – Senior vs. junior developer leverage
16:33 – The developer talent pipeline
18:21 – Ego, identity, and automation
19:08 – Before vs. after: building with AI
22:30 – Debugging and fixing issues with AI
24:42 – Spec-writing and product shaping with AI
26:49 – The future of computer science grads
29:20 – Closing reflections
