Latest / The Series A Show with Fexingo: Early-Stage Funding, Pitch Decks, and Startup Milestones / Why Startups Are Offering Earnouts to Hire Top AI Talent
Transcript
- Lucas: Luna, I’ve been tracking how startups are trying to hire senior AI engineers without getting crushed on salary. The latest tactic I keep hearing about is the earnout — not the M&A kind, but a performance-based equity grant that vests if the employee stays and hits specific milestones. Luna: So it’s like a golden handcuff with a bonus trigger tied to outcomes, not just time served? Lucas: Exactly. And it’s getting popular because the math is brutal right now. A senior AI engineer at Google or Meta is making maybe $400,000 in total comp. A Series A startup can’t match that in cash, but they can offer a grant that could be worth two or three times that if the company hits its next round or exit. Luna: Right. And the earnout structure gives the employee a real reason to stay through the rocky early years. Lucas: Let me give you a concrete example. I talked to a founder last week — an AI infrastructure startup, just closed their Series A at a $30 million cap. They hired a senior ML engineer from Amazon by offering 20,000 options vesting over four years with a one-year cliff. But they added an earnout: if the company exits — either IPO or acquisition — within five years, that engineer gets an additional 10,000 options on top. That’s essentially a retention bonus tied to the exit. Luna: So the earnout is a second tranche that only vests upon a liquidity event. That aligns incentives — the engineer wants to build toward a sale or IPO, not just coast. Lucas: Exactly. And it’s not just about retention. It’s a signal to the employee that their work directly contributes to the exit value. Some startups are even tying earnouts to specific product milestones: launch a feature, hit a certain revenue run rate, deploy the model in production. That way the earnout feels earned, not just a lottery ticket. Luna: This is reminding me of something I’ve been seeing in the news. Palantir’s stock dropped about 6% this past week. It’s down to around $128. That kind of volatility in a public company’s equity reminds us that even options in a promising startup can lose value if the exit doesn’t happen — or happens at a lower price. Lucas: That’s a great point. No equity is guaranteed. And that’s why earnouts are interesting: they give the employee upside if the company does well, but they also create a psychological contract. You’re not just an employee — you’re a stakeholder in the exit outcome. Luna: Before we go deeper — I want to mention something quickly. A few listeners have started supporting us through buy me a coffee dot com slash fexingo. That’s how we keep this show ad-free and focused on exactly these kinds of practical topics. If you find these conversations useful for what you’re building or running, that link is buy me a coffee dot com slash fexingo. It genuinely helps. Lucas: Yeah, it makes a difference. So back to earnouts — one variation I’m seeing is the ‘double-trigger’ earnout. The options vest only if the employee is still employed AND a specific event happens, like a Series B round or a revenue target. This is especially common in later-stage startups where the exit is closer but still uncertain. Luna: Double-trigger essentially protects the company from giving away equity to someone who leaves before the event. It’s a common feature in M&A earnouts for founders, but applying it to employee grants is newer. Lucas: Right. And it flips the traditional vesting model on its head. Standard vesting is time-based: you get your shares if you stay four years, period. Earnouts add a performance dimension. That’s a big shift in how startups think about compensation. Luna: What about the downside? If an employee joins and the earnout targets are too aggressive, they could feel like they’re being set up to fail. Or if the company hits the target early, the employee might cash out and leave. Lucas: Those are real risks. That’s why good earnout design is critical. You want the target to be ambitious but achievable, and you want the earnout period to overlap with the employee’s remaining vesting schedule. Some startups are using tranches: a small earnout if the company raises the next round, a larger one if it exits. That way the employee stays engaged through multiple milestones. Luna: I’ve also heard of ‘earnout cliffs’ — where the employee must stay at least 18 months to qualify for any earnout. That prevents someone from joining, hitting a quick milestone, and leaving. Lucas: Exactly. And this is especially relevant in AI right now. The talent war is intense. Companies like OpenAI, Anthropic, and Google are offering huge packages. Startups can’t compete on base salary, but they can offer more upside if the company grows. Earnouts make that upside feel more tangible. Luna: There’s also a connection to the trend of usage-based pricing we talked about in earlier episodes. Both are about aligning incentives — the customer pays for what they use, the employee earns when the company achieves real milestones. Lucas: That’s a smart link. And rolling valuations, which we’ve covered a lot on this show, also fit here. When a startup uses a rolling valuation for its fundraising, the valuation can adjust based on performance. That makes earnouts easier to structure because you have a more dynamic view of the company’s worth. Luna: So earnouts work best in a flexible fundraising environment. If the valuation is fixed, the earnout might be too conservative. If it’s rolling, the earnout can expand with the company’s growth. Lucas: Right. And I think we’re going to see more standardisation of earnout terms. Right now, every deal is custom. Lawyers are spending hours drafting acceleration clauses and milestone definitions. If a standard template emerges — like the SAFE note did for equity — it could speed up hiring for early-stage startups. Luna: That would be huge. Imagine a standard ‘Series A AI Engineer Earnout’ that founders can just plug numbers into. It would lower legal costs and make the offer more transparent for the candidate. Lucas: One company I’m watching is a startup called Vanta — they do automated security compliance. They’ve been using a form of earnout for key hires since 2023. Their CTO got an earnout tied to hitting $10 million in ARR. That happened last year, and the earnout paid out in additional options. It’s a great case study. Luna: And what about the tax implications? If the earnout is structured as additional options, the employee doesn’t pay tax until exercise. But if it’s a cash bonus at exit, it’s ordinary income. Lucas: Right, and that’s a critical detail. Most startups structure earnouts as additional option grants so the employee gets the benefit of capital gains treatment if they hold the shares. But if the earnout is tied to a liquidity event, the options might be exercised automatically, which could trigger a tax bill. Founders need to explain that clearly. Luna: It’s a lot for a candidate to evaluate. You’re weighing base salary, standard options, earnout options, cliff, double-trigger, tax treatment. It’s almost like a mini mba in compensation. Lucas: And that’s why some startups are now including a ‘compensation explainer’ in their offer letters — a one-page summary that shows the total potential value under different scenarios. That transparency builds trust. Luna: I want to bring this back to the broader market. Looking at the big tech stocks this week — Apple down 3.5%, Microsoft down 5.1%, Google down 1%. Those are the companies competing for the same AI talent. If their stock keeps sliding, their equity comp becomes less attractive, and startups might have an easier time hiring. Lucas: That’s a really sharp observation. If Big Tech equity loses its luster, startups with well-structured earnouts could become more competitive. But the risk is that if the startup also slides — and many will — the earnout becomes worthless. So the employee is betting on the startup’s execution. Luna: It’s a calculated bet. And for a senior engineer who believes in the mission, it can be a great one. But for a risk-averse person, the big tech salary and stable equity might still win. Lucas: Absolutely. And that’s okay. Not every hire needs an earnout. But for the key hires — the ones who will make or break the product — a well-designed earnout can be the difference between getting a ‘yes’ or a ‘no’. Luna: What about the board’s perspective? If a startup issues too many earnout options, it dilutes existing shareholders. There’s a tension between attracting talent and protecting cap table value. Lucas: That’s the classic tension. But here’s the thing: if the earnout is tied to a valuation increase or exit, the dilution is offset by the value creation. A good board will approve earnouts for critical hires because the alternative — not hiring the person — is worse. Luna: And the earnout pool can be pre-approved as part of the option pool increase. Many Series A investors are okay with a larger pool if it’s reserved for performance-based grants. Lucas: Exactly. I think we’ll see more experimentation with earnout structures in the next year. With rolling valuations and usage-based pricing becoming more common, the compensation model is also evolving. It’s a fascinating time for startup compensation. Luna: For anyone listening who’s considering an earnout offer — ask about the specific triggers, the tax treatment, and what happens if the company is acquired before the earnout vests. Those details matter. Lucas: Great advice. And for founders: think about what milestones truly matter for your business. Tie the earnout to those, not just to time served. That way, your top talent is working toward the same goals you are. Luna: I’ll be watching how this plays out over the next few quarters. If Big Tech stocks keep slipping, earnouts might become the new normal. Lucas: And if they do, we’ll be here covering it. That’s it for this episode of The Series A Show. Until next time.