The New AI Product Skill Stack (LLMs, Eval, Data Loops) — Explained

AI is changing product management fast — and “adding AI to the roadmap” isn’t a strategy.

In this episode of Experts in the Loop, we sit down with Alex Zenoviev (Head of Product at Neo Intelligence and co-founder of Genelab, one of Australia’s strongest AI product communities) to unpack what it actually takes to be an AI product leader in 2026.

You’ll hear Alex’s journey from engineering into product, why teams beat lone geniuses in modern product building, and the real skills product leaders need to ship useful AI features without the hype.

Chapter markers:
00:00 Intro + meet Alex Zenoviev (Neo Intelligence, Genelab)
01:12 Community mindset + why commitments matter
01:34 Stop tool-hopping: go deep on one tool
03:52 Alex’s background: web dev → product (starting 2011)
05:08 Working with technical teams (and why product clicked)
11:57 How Genelab started (and balancing career + family)
24:39 What makes great product teams: diversity of thought
33:46 How AI is changing the product role (AI PM vs PM)
35:20 The new AI product skill stack: LMs, evals, prompt engineering
36:58 Real example: using AI automation with a sales team
41:15 Data assets as the real moat (data loop thinking)
46:30 Tooling check-ins + automation/prototyping stack (Manus, Relay, DevRev)
48:00 Wrap up + thanks for joining us

What you’ll learn

• The new “AI product skill stack” (LLMs, evaluation, prompt craft, automation)
• Why most AI features shipped in a rush don’t land with users
• How to think about data as a growth loop (better product → better data → better product)
• How to choose an AI toolset without constantly jumping platforms
• What building an AI community teaches you about product, career growth, and leverage

Topics we cover

• AI product management and leadership in 2026
• AI strategy vs AI theatre (and why “put AI on the roadmap” is not enough)
• LLM fundamentals for product people (what matters, what doesn’t)
• Evaluation and quality control for AI features
• Data, context, and reducing hallucinations
• Community building (Sydney meetups, workshops, and why in-person still wins)

Who this episode is for

• Product Managers and Product Leaders working on AI features
• UX and Design folks partnering with AI product teams
• Founders building AI-enabled products
• Anyone trying to move from “AI curiosity” to real-world product impact

If you’re building AI products (or want to), this one will help you think clearer, ship smarter, and avoid the common traps.

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