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25,500 LLM evaluations on hiring bias, DevCon London recap, and the leadership problem

· 4 min read

re:cinq, think ai native

Newsletter #4

Welcome to the 4th edition of our newsletter.

It's been great to see this community keep growing, with more conversations, ideas, and people coming together to understand what AI Native means.

We hope the past few weeks have brought you some new ideas, useful conversations, or small steps forward in your own AI Native journey.

Let's get into it.

01 · From the blog

What we've been writing about

The Blind Spot in the Machine: What 25,500 LLM Evaluations Reveal About AI Hiring Bias

Blind Spot in the Machine: AI Hiring Bias

Bogdan, one of our engineers, ran 25,500 evaluations across ten LLMs to test for demographic bias in résumé screening. The headline: 45% of résumé pairs showed unjustified score shifts tied to changes in demographic markers like first names. The bias rarely shows up in the explanations themselves. The models invent different justifications for identical work history once the name changes.

Why AI Adoption Is a Leadership Problem

Why AI Adoption is a Leadership Problem

Pini, our CEO, argues that AI adoption succeeds or fails on the people side. The 2025 DORA report puts it well: AI works as an amplifier. A strong engineering team becomes meaningfully more capable; a weaker one gets worse. The post draws on Odevo's experience to show what changes when leaders actively coach teams through the transition.

Good Ideas Should Not Need Good Marketing to Survive (Part 2 of 2)

Good Ideas Should Not Need Good Marketing to Survive

Part 2 of Pini's EEEG framework series. He argues that platform economics currently reward engagement over substance, which forces valuable ideas to depend on marketing. AI changes that by making it easier for practitioners with deep knowledge but weak writing to publish. He proposes capturing insights structurally once, then rendering them in different formats.