Pillar 04

Talent for the AI Era.

The interview questions that defined engineering hiring for two decades are not just outdated; they are now actively misleading. Inverting a binary tree on a whiteboard is a poor proxy for whether someone will build the right agent, write the right spec, or hold the right judgment about when to let the model do the work.

The questions that actually matter now

What was the last agent you wrote, and what did it do? What kinds of tasks have you automated in your own workflow over the last six months? Walk us through a spec you wrote for an AI-assisted change: what made it good, and what did the model still get wrong? Show us a prompt library you actually use. When did you last decide not to use the LLM, and why? Where do you draw the line between human review and agentic execution in your work?

These questions surface the things a modern engineering hire actually needs: fluency with prompting, comfort with non-deterministic systems, judgment about agent design, exposure to spec-driven and agentic-centric development cycles, and a working theory of when AI helps and when it hurts. The candidates worth hiring will have crisp answers. The ones who don't are signaling something important.

What we do

Engineering interview redesign

A workshop-and-deliverable engagement that produces a new interview loop: revised question set, calibrated rubrics, take-home exercises that allow AI use (with attention to how it is used), and reference-check prompts that get past hiring-manager talking points.

Engineering job architecture for the AI era

Most engineering ladders were written before AI moved up the stack. We help organizations rethink the role definitions, the seniority signals, and the career paths, including the question of which roles should exist at all in an agentic operating model, and what an "AI engineer" actually means inside your firm.

Lean leadership sourcing

Where it helps, we source the lean leadership talent your AI initiatives need: fractional CIO/CTO support drawn from senior enterprise operators and from founders running their own AI-forward platforms. We are deliberately not a body shop, and we will tell you when you do not need an additional hire.

AI engineering bench

Access to current AI engineers: practitioners up to date on prompting techniques, agentic-centric development cycles (ACDC), AI security, spec-driven development, and the rest of the rapidly-moving toolchain. Engaged the same way our advisors are: lean, fit-for-purpose, time-boxed.

Who this is for

Engineering leaders who can feel their hiring loop slipping out of sync with the work the team now actually does. Talent partners and HR leaders who want to update the playbook before they hire a hundred more people against the old one. Founders building an AI-native engineering function from scratch.

To discuss your situation, get in touch.