Elon Musk vs Sam Altman | The Implosion of Thinking Machines | Can VC Survive Public Pricing?

If a company as structurally sound and dominant as Figma is seeing its valuation questioned in the public markets, what hope is there for the rest of the software industry? This serves as the anchor for a broader anxiety ripple through the venture capital ecosystem. We are currently witnessing a massive sifting mechanism: the separation of "AI-native" hyper-growth from the "boring" SaaS middle class. Between the executive exodus at OpenAI, the looming legal battle between Musk and Altman, and the sudden pivot toward advertising in LLMs, the playbook for building (and exiting) a tech company is being rewritten in real-time.

Key Takeaways

• The SaaS "Grind" is Unfundable: Public markets are bifurcating companies into "high-growth AI" and "slow-growth legacy." If you are a mid-stage SaaS company growing at 50% without an AI story, venture capital interest evaporates.
• Talent Sovereignty in AI: The departure of top executives like Mira Murati from OpenAI proves that top-tier researchers prioritize intellectual challenge over equity; they will leave billions on the table if the mission stagnates.
• The Musk vs. Altman Lawsuit is Asymmetric: Elon Musk doesn’t need to win legally to win strategically. The discovery process alone, airing internal emails and diaries, serves as a "traffic accident" that slows OpenAI down.
• Ads are the Future of LLMs: Just as Google and Facebook eventually embraced ads, OpenAI’s shift to monetization via search/display is inevitable and likely to become a multi-billion dollar revenue stream immediately.
• Late-Stage VC has Shifted: Investors are moving away from the risky Series B "middle" and preferring to back massive, established winners (like Replet or ClickHouse) at high valuations, effectively treating private markets like public growth funds.

The Great Valuation Bifurcation: Figma vs. The Field

The prevailing sentiment in venture capital has shifted from optimism to a stark pragmatism. When analyzing the public markets, we see companies like Figma—despite being excellent businesses—trading down from their unicorn-era highs. This creates a crisis of confidence for founders and investors alike: if the best-in-class assets aren't getting premium multiples, what happens to everyone else? The answer lies in how the market now sorts growth. The market isn't dead; it is simply filtering with extreme prejudice. Companies perceived as "ex-growth" are being discarded at low valuations, while those attached to the AI trend (like Palantir trading at 70x forward sales) are awarded astronomical premiums. Venture capital remains, at its core, a trend-following business.

The "Grind" is Not in the VC Model

For a founder running a solid SaaS company—perhaps $50M to $75M in revenue, growing at 50% year-over-year—the reality is harsh. In previous cycles, this performance would guarantee a massive growth round. Today, it guarantees a "pass."

When the grind isn't in your MO, you move on. The probability of a mid-stage SaaS company exploding into something amazing is rounding error zero. So as an investor, that's not attractive.

The advice for these founders is direct: stop relying on venture capital. If you cannot linearly convert your product into an AI-native platform with massive tailwinds, you must transition to profitability. The days of converting high revenue multiples into cash through M&A or IPOs without the underlying free cash flow are largely over.

The Implosion of Teams: Why Talent Leaves OpenAI

The recent departures of key figures like Mira Murati and Barret Zoph from OpenAI signal a unique dynamic in the AI sector. While observers might panic at the "implosion," seasoned investors view this through a different lens: it is essentially a seed round dynamic playing out at a $150 billion scale. In early-stage startups, founder incompatibility is the leading cause of failure. OpenAI is experiencing this same friction, just with extra commas in the valuation. However, the driving force here isn't just personality clashes; it is the nature of the talent market.

Mission Over Money

We often underestimate the motivations of S-tier AI researchers. This is a labor market where the talent holds all the leverage. These individuals are not motivated solely by vesting schedules. They are motivated by the "Transformer paper" moments—the chance to solve unsolved problems. If a researcher feels a lab has become too corporate, too product-focused, or intellectually stifling, they will leave. The portability of their skills is absolute. A top researcher can walk out of OpenAI and raise huge capital for a new venture the next day, or simply join a rival lab that promises them the freedom to work on what they love. For non-AI native companies, recruiting this level of talent is nearly impossible; if you aren't working on the frontier of AGI, you aren't hiring the frontier of talent.

Elon Musk vs. Sam Altman: The Lawsuit as Spectator Sport

The legal battle between Elon Musk and OpenAI is shaping up to be the "gift that keeps on giving" for the tech industry. While the core legal argument—that OpenAI defrauded Musk by pivoting from non-profit to for-profit—has significant hurdles to clear, the lawsuit is an asymmetric win for Musk.

The Discovery Trap

Musk’s goal may not be to recover his $30 million donation, or even to win a share of the company. His win condition is likely the chaos of the process itself. Litigation forces discovery. Diaries, emails, and internal memos from 2017—when tensions were high and ambitions were unchecked—will become public record.

If you're the kind of person who slows down at a traffic accident, in other words, if you're like 90% of humanity, you're going to be slowing down every time the depositions come out. It's going to be great.

For OpenAI, this is a massive distraction during a critical product cycle. For Musk, who has already endured the "pain" of public scrutiny during the Twitter acquisition, there is no downside. He has already been "bad-facted" to death; he is immune to the shame that might damage a standard CEO. This makes him a dangerous litigant who is willing to burn the house down to prove a point.

The Inevitability of Ads in AI Discovery

The introduction of advertising into ChatGPT and SearchGPT was inevitable. History shows that even companies that philosophically oppose ads—like Google in 2000 and Facebook in 2005—eventually succumb to the business model because it is the only way to monetize free users at scale. However, viewing this as a negative user experience might be shortsighted. The potential for "Answer Engine Optimization" (AEO) and discovery ads in LLMs is enormous.

High-Intent Real Estate

Current search engines have become cluttered and difficult to navigate for discovery. If you ask an LLM for the best 65-inch TV for a bright room, the intent is incredibly high. An ad served in this context—specifically bidding on that high-intent conversation—is valuable information, not just noise. If OpenAI can capture even a fraction of the "discovery" market from Google, the revenue implications are staggering. We could see a billion-dollar ad business emerge within quarters, not years. The auction dynamics for this prime real estate will likely be robust, with advertisers willing to pay high CPMs to be the "suggested answer" in a conversational interface.

The New Late-Stage Playbook: Replet, ClickHouse, and the "Fidelity" Model

Despite the gloom in mid-stage SaaS, massive rounds are still happening. Replet’s recent valuation at $9 billion and ClickHouse at $15 billion highlight a shift in how capital is deployed. Investors are increasingly adopting a "Fidelity-style" approach to private markets: finding the category winner and piling in, regardless of the valuation.

• Replet: The bull case here is product velocity. The leap from a "broken" coding environment to a seamless, agent-based developer platform has been orders of magnitude better in just 12 months. Investors are betting that AI coding agents will fundamentally change software creation.
• ClickHouse: This represents a bet on the explosion of data analysis required by AI. As AI models require more data crunching, the "OLAP" (Online Analytical Processing) category expands. ClickHouse is being anointed the winner of this category, much like Snowflake or Databricks before it.

The Death of the Series B?

The current environment suggests that the most dangerous place to be is the middle. Investors prefer to own a large chunk of a seed company (high risk, high reward) or a small slice of a guaranteed late-stage winner (low risk, reliable growth). The "competitive Series B"—paying 100x ARR for signs of product-market fit—is currently viewed as the "sucker's game" of venture capital.

Conclusion

The tech ecosystem is undergoing a violent rotation. The safety net of the "ZIRP" (Zero Interest Rate Policy) era is gone. Founders can no longer rely on a rising tide to lift all boats; only those with specific AI-enabled hulls are floating. For investors, the strategy has simplified: buy the absolute winners at any price, or fund the dreamers at the very beginning. For everyone in between—the $50M SaaS companies, the non-profit researchers, the mid-tier platforms—the message is clear: adapt your model to the AI reality, or prepare for the grind.