Independent, practitioner-led interviews for executive hires and potential technical cofounders. We test for judgment, leadership, and the ability to build and scale AI-driven products—so you know who can truly deliver.
Why practitioner-led interviews matter
- Early-stage companies live or die by leadership quality; a mis-hire at the top can cost quarters of burn and miss the market window.
- AI and infra-heavy products need leaders who understand latency, data, cost-to-serve, and model lifecycle—not just “shipping software.”
- Storytelling and references alone are not enough; structured conversations with experts reveal how candidates think, lead, and execute under pressure.
- Culture and team balance drive velocity. Pairing research-minded leaders with production-minded operators keeps roadmaps real and delivery predictable.
- Investors scrutinize leadership. Independent assessments de-risk your raise or acquisition before term sheets and retention packages go out.
How we add value
We run deep, respectful interviews that mirror real decisions leaders face—technical, product, and organizational. You receive a clear readout: strengths, risks, and the conditions where each candidate will thrive.
What we evaluate
- Technical judgment: Ability to choose the right abstractions, manage latency and cost, and balance speed with reliability for AI-driven products.
- Product and market sense: How they tie technical decisions to user value, differentiation, and go-to-market timing.
- Execution and leadership: Operating cadence, hiring philosophy, incident posture, and how they build accountable teams.
- AI/ML rigor: Approach to data quality, model evaluation, safety/abuse handling, and roadmap credibility given talent and data access.
- Communication and collaboration: Clarity with boards, founders, and cross-functional partners; ability to bring non-technical stakeholders along.
How we run the process
1) Role alignment (Day 0–1)
Calibrate on the mandate, stage, and success outcomes for the role; align on what “must-have” looks like.
2) Interview design (Day 1–2)
Craft scenarios tied to your product and stage—scaling AI/infra, roadmap tradeoffs, hiring plans, and risk handling.
3) Candidate conversations (Day 2–7)
Conduct structured, practitioner-led interviews that probe depth, judgment, and leadership approach.
4) Readout and recommendation (Day 4–9)
Deliver a concise report: strengths, risks, deal-breakers, and onboarding considerations.
5) Offer and onboarding support
Support reference angles, offer structure, and the 30/60/90 plan that sets the leader up to win.
Who this is for
- Founders hiring a CTO, Head of Engineering, or technical cofounder and wanting a second set of expert eyes.
- Boards or investors evaluating leadership during a raise or acquisition.
- Companies adding AI leadership and needing proof of depth, not just AI on a resume.
Engagement models
- Single-candidate assessment: One structured interview and a focused readout.
- Slate assessment: Multiple candidates scored consistently to inform final selection.
- On-call partner: We join your process as an ongoing interview panelist for exec and staff-plus hires.
