AI Startup Interview Guide:
What Early-Stage Companies Look For

Startup processes are shorter and less standardized: (1) Founder/CTO call (30-60 min) - fit and interest, (2) Technical discussion or pair programming (1-2 hours) - real problems, not LeetCode, (3) Take-home project (optional, 4-8 hours) - build something real, (4) On-site or final round (2-4 hours) - meet the team, cultural fit. Total timeline: 1-3 weeks. Process may compress if they're hiring urgently or extend if fundraising.

Key differences: (1) Real problems over algorithm puzzles—expect to discuss their actual codebase or product challenges, (2) Breadth over depth—can you handle frontend, backend, infrastructure?, (3) Take-home projects are common—they want to see how you actually work, (4) Code quality matters less than functionality—does it work and can you ship it?, (5) System design is more practical—'how would you build our MVP?' not 'design Twitter.' Show you can solve real problems with minimal guidance.

Founders evaluate: (1) Ownership mindset—do you wait for permission or take initiative?, (2) Velocity—can you ship fast without perfect requirements?, (3) Culture fit—will you thrive in ambiguity and change?, (4) Passion—do you care about the problem they're solving? Prepare to discuss: why this startup, what you'd build in the first 30 days, how you've handled ambiguity. Ask them: what's the biggest technical challenge, how do you prioritize, what does success look like in 6 months?

Equity evaluation: (1) Get the full picture—number of shares, total outstanding, valuation, vesting schedule (typically 4 years with 1-year cliff), (2) Understand dilution—future funding rounds will reduce your percentage, (3) Calculate scenarios—what's your equity worth at 2x, 5x, 10x current valuation?, (4) Consider stage—pre-seed (0.5-2%), seed (0.25-1%), Series A (0.1-0.5%), later stages (less). Negotiation tips: equity is more negotiable than salary, ask for acceleration on acquisition, understand exercise windows if you leave.

Watch for: (1) Founders can't articulate the problem they're solving, (2) No discussion of runway or burn rate when you ask, (3) Unclear equity terms or reluctance to share cap table basics, (4) Technical debt they dismiss rather than acknowledge, (5) Unrealistic timelines ('we'll be profitable in 6 months'), (6) High turnover they can't explain, (7) Over-promising on compensation ('equity could be worth millions'). Trust your gut—if something feels off, it probably is.

It probably isn't, and you should hold the money. Most cohort dropouts are people who couldn't articulate what they were shipping when they signed up. That's why the consult exists, and why I turn down most applications. If we get on the call and you can't tell me what you'll have shipped at the end of week 8, I'll point you to the AI Native Engineer community until you can.

Yes, the cohort works for people shipping their first serious AI system whether the goal is to land a senior role or to launch a product. The shipped system serves both equally well.

You need to be able to code in Python or TypeScript. Complete beginners can follow the classroom they get access to before the cohort sessions to come in well-prepared.

You'll spend 3 hours every Tuesday in the live session and roughly 3 hours of async work in between, for 8 weeks. The Tuesday session time is fixed.

It's a four-figure investment that we discuss during the 30-minute consult, alongside whether the cohort is the right fit for your project.

Yes, most attendees do. The live session is one Tuesday a week and the async work fits around your existing schedule, as long as you can carve out roughly 6 hours a week.