As a partner at Khosla Ventures, a firm renowned for its bold, often contrarian bets on transformative technologies, Ethan Choi isn’t shy about speaking his mind. The investor is notably vocal about his belief that artificial intelligence (AI) poses a massive, existential threat to entry-level jobs, a phenomenon he interprets as a fundamental shifting social contract in the modern workforce. His insights are not merely theoretical; Choi’s professional trajectory has positioned him at the forefront of AI’s impact, having personally led significant investments in several groundbreaking AI-first companies.

Known for a steadfast founder-first conviction, Choi’s investment philosophy extends beyond just AI, having also backed pivotal enterprise software and fintech infrastructure companies throughout his career. His journey to Khosla Ventures in 2024 followed a distinguished tenure at Accel, where he served as a partner. At Accel, he was instrumental in leading and managing high-profile growth investments in a diverse portfolio of companies, including cybersecurity leader 1Password, marketing automation giant Klaviyo, and the innovative financial technology platform Pismo, which was notably acquired by Visa. His portfolio also boasted e-commerce platforms like Nuvemshop and commercetools. Prior to his impactful time at Accel, Choi sharpened his investment acumen at Spectrum Equity, where he supported companies such as the online learning platform Lynda.com (later acquired by LinkedIn), the mindfulness app Headspace, the visual workspace Lucid Software, and the photo editing tool PicMonkey (acquired by Shutterstock). This rich background underscores his deep understanding of technological evolution and market dynamics across various sectors.

I recently had the opportunity to speak with Choi, delving deeper into his provocative predictions regarding the disappearance of entry-level jobs. Our conversation also explored the evolution of his investing philosophy, specifically how he has transitioned from a growth-stage focus to embracing a more stage-agnostic approach, reflecting the accelerating pace of technological change. This interview, edited for brevity and clarity, reveals a visionary investor grappling with the profound implications of AI on careers, education, and the very fabric of the economy.

Crunchbase News: You’ve had a prolific run the past couple of years, leading deals in Ramp, ClickHouse, Vercel, Glean, Bridge and others. How are you managing that volume?

Choi: It has undeniably been an intense stretch, a period characterized by rapid deployment of capital into promising ventures. About seven deals happened just last year, which, by any industry standard, was an insane pace and a testament to the sheer volume of innovation we’re witnessing. This year, however, has seen a bit of a calmer cadence, allowing me to shift my focus more intensely on settling in with the companies I’ve already invested in. The goal now is to provide deeper strategic support and help nurture their growth in this dynamic environment.

You’re currently researching the disappearance of entry-level jobs. As a parent, that sounds a bit scary to me. What are you seeing?

It’s a massive conundrum, and one that has profound societal implications. I’m seeing its tangible effects even in my own daily workflow. I leverage sophisticated AI models to rapidly get up to speed on complex technical capabilities – for instance, asking about ClickHouse’s indexing methodology versus Snowflake’s, all in voice mode while I’m driving. The AI is capable of pulling from countless research papers and technical documentation, synthesizing information faster and more comprehensively than any human could possibly achieve. I describe it as feeling like I have an “Ironman suit” on, augmenting my cognitive abilities exponentially.

The core problem is stark: if I, as an experienced professional, can effectively perform the work typically assigned to a junior associate myself, almost instantly and with superior efficiency, then those entry-level roles simply vanish. We are rapidly facing a world where the base-level, foundational work that companies traditionally relied on young professionals for is no longer a stepping stone but has become table stakes for everyone. This erosion of traditional entry points fundamentally alters the social contract between education, employment, and upward mobility, raising critical questions about how future generations will gain practical experience and professional footing.

If the “on-the-job” training era is over, where does that leave students and universities?

The burden of the first three years of “learning how to be a professional,” which historically occurred within the workplace, has to fundamentally shift to the universities. I look at the traditional U.S. model of general education requirements and often think, “Why are we still doing this?” We covered that foundational knowledge in high school. Universities, instead, should be transformed into dynamic environments where students are actively encouraged to use AI as a powerful tool to actually build things, to innovate, and to apply their knowledge directly to real-world problems from day one.

If you’re a computer science major today, the expectation upon graduation is dramatically different. You need to enter the workforce looking and delivering like a third- or fourth-year engineer, already proficient and productive. The bar has been unequivocally raised for everyone. While forward-thinking institutions like Vanderbilt and Arizona State University are proactively leaning into an “AI-first” curriculum, integrating AI literacy and application across their programs, many elite institutions are still conspicuously silent, grappling with how to adapt their venerable, often rigid, structures to this unprecedented technological paradigm shift.

Khosla is known for being contrarian. How does that translate to the growth stage in such a competitive market?

It’s interesting because my personal investment philosophy has actually evolved to become largely stage-agnostic. While many in the industry still tend to put me in the “growth” bucket due to my past work, I’m increasingly doing much more seed and Series A investing. The rationale for this shift is compelling: in this new era, the historical metrics a company possesses today — be it revenue, user growth, or market share — don’t necessarily guarantee where they’ll be in even two years, because the rate of technological change, primarily driven by AI, is so incredibly high and disruptive.

I’ve essentially flipped my philosophy on its head: it used to be a balance of 80% metrics and 20% founders when evaluating opportunities. Now, it’s closer to 90% founders. The only true constant in this rapidly shifting landscape is the exceptional quality of the founding team and their innate ability to adapt, pivot, and execute with lightning speed. If code is being created 10x faster, a company might effectively face 50 years of technological and market change packed into a single decade. You absolutely have to back the extraordinary individuals who possess the resilience, foresight, and agility to handle that kind of intense, sustained stress and navigate such profound disruption.

You’ve predicted “mass carnage” for some software companies. Who survives the transition to an AI-native world?

We are undeniably moving from a market where companies were primarily valued by trading on revenue multiples to one that emphasizes free cash flow and traditional price-to-earnings (PE) multiples. That’s a fundamentally painful and often brutal transition for many established players. The market now critically needs to believe that a company is genuinely AI-native — meaning its core revenue streams are actively moving toward inference- and usage-based models, deeply integrated with AI, rather than relying solely on old-school, static seat licenses. This shift implies a complete reimagining of product, pricing, and value delivery.

I fully expect significant “carnage” for lightweight, horizontal applications and many mid-market companies, especially those that struggle to attract and retain top-tier applied AI talent. These companies will find it increasingly difficult to compete with new entrants building natively with AI from day one. I have a tremendous amount of respect for visionary founders, like those at Intercom or Airtable, who are effectively “burning the boats” — making radical, all-in commitments to reinvent their entire businesses around AI. It’s an incredibly difficult, high-stakes endeavor, but in this relentlessly evolving market, you either reinvent yourselves completely, or you risk being replaced by someone building natively with AI from inception, leveraging its capabilities to deliver superior value.

With your background in fintech infrastructure, where do you see the next “unconventional” opportunity in financial services that most growth investors are currently overlooking?

It’s now become somewhat consensus among leading investors, but I still believe it remains a fairly unconventional and often underestimated premise: that deeply entrenched systems of record can actually be ripped out and replaced. This applies not only to financial services but also to other traditionally conservative categories.

For example, we recently invested in DualEntry, a company that is boldly seeking to replace NetSuite and other core accounting systems. This is significant because the core accounting system is arguably the last system of record I would have ever thought might be under immediate threat of replacement. However, what we’re now seeing is that with the transformative power of AI, innovative startups can construct migration paths that simply didn’t exist before. Furthermore, AI enables them to achieve the depth and breadth of incumbent platforms in a mere fraction of the time and cost, creating a potent disruptive force in areas once considered impenetrable. This capability opens up opportunities to overhaul foundational infrastructure that was previously too complex or risky to touch.

Vinod Khosla often talks about “challenging the conventional wisdom” of founders. Can you share an example of a time you had to steer a growth-stage founder away from a “safe” path toward a much larger, albeit riskier, vision?

In general, there are countless times when a founder is meticulously thinking through a very risky but potentially game-changing product addition or a transformative acquisition. While I view a crucial part of our job as investors and board members as helping identify and meticulously manage potential risks inherent in these ambitious moves, the most important and impactful thing we can truly do is to give them the profound courage to take those calculated risks. These are the risks that possess the potential to be truly transformational, not just for their immediate business, but for the entire category they operate within, redefining market expectations and competitive landscapes. It’s about empowering them to swing for the fences, not just hit singles.

You’ve noted that talent density is the most important variable for success. In a market where AI is automating routine work, how has your criteria for what defines an “elite” executive hire changed?

Perhaps somewhat ironically, one of the main and most critical differences in our criteria for evaluating an elite executive hire today is whether this executive has “IC’d” (individual contributor’d) themselves. This means assessing if they can roll up their sleeves and personally perform most of the hands-on work required out of the gate, leveraging their own expertise augmented by AI tools. In an AI-driven world, the expectation is no longer just about managing teams or delegating tasks; it’s about executives being able to directly engage with the work, use AI to amplify their individual output, and demonstrate hands-on mastery. This fundamental shift ensures that leaders not only guide but can also actively contribute to the intellectual and technical heavy lifting, setting a powerful precedent for their teams and driving unprecedented efficiency and innovation.

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Illustration: Dom Guzman