Forget SpaceX: Here's The Blockbuster IPO I'm Waiting For

Anthropic confidentially filed its S-1 on June 1, putting a potential IPO as soon as 2-3 months away. The article highlights Anthropic's rapid revenue run-rate growth from $9 billion at the end of 2025 to over $30 billion in April, with the figure possibly above $40 billion now, and notes its late-May Series H valuation of $965 billion. The piece argues Anthropic could be a cheaper public AI listing than SpaceX on a price-to-sales basis, making the IPO notable for AI and venture investors.

Analysis

The real signal here is not the headline valuation comparison; it’s the market beginning to separate “AI infrastructure beneficiaries” from “AI application monopolies.” A pure-play frontier model company with a credible revenue ramp approaching hyperscale status is exactly the kind of asset public investors will over-allocate to on the first few prints, which can pull capital away from adjacent winners like cloud, semis, and model-access distributors. That should be mildly negative for second-tier AI software names that trade on narrative rather than durable usage, because a public comp with faster growth and cleaner unit economics compresses the scarcity premium.

The more interesting second-order effect is on Alphabet. If a major model vendor validates that enterprise willingness to pay is real and accelerating, it reduces skepticism around high AI capex at the hyperscalers and should support the thesis that AI is still under-monetized rather than overbuilt. That’s incrementally constructive for GOOGL over a 6–12 month window, because search and cloud can absorb more AI spend if model economics are proving out; it’s less helpful for names whose AI angle is purely optionality and not monetization.

The market is likely underestimating the IPO overhang risk to private-markets sentiment. If this lists at a rich multiple, late-stage venture marks across AI will stay elevated, but if first-day performance is merely “good” rather than explosive, it can trigger a repricing of private AI rounds funded at increasingly aggressive assumptions. That matters because the next 1–3 months are about capital rotation and comp discovery, not just one listing.

Contrarian view: the best trade may be to fade the implied scarcity premium in the most loved AI proxies, not to chase the IPO itself. The article assumes public investors will reward purity, but in practice they often punish concentration risk once the lock-up and cap-table complexity become visible. The setup favors owning the monetization layer with diversified revenue exposure and shorting the most crowded “AI story” names if implied multiples overshoot.

Key Decisions for Investors

• Buy GOOGL on any post-IPO AI-compression dip over the next 1-2 weeks; target 8-12% upside over 6 months as the market re-rates AI capex durability, with downside limited to normal multiple digestion.
• Short a basket of unprofitable AI software names versus long GOOGL (or MSFT if preferred) into the IPO window; the pair should work if public comp pressure forces investors to discriminate between real adoption and narrative premium, with a 3-6 month horizon.
• Avoid chasing the first-day IPO pop in the pure-play AI name; if it debuts at >30x run-rate sales, wait for 30-60 days of trading and consider a post-lockup fade if growth decelerates or margin disclosures disappoint.
• Use NVDA as a tactical hedge, not a core long, into the IPO cycle; if the market interprets the listing as evidence of still-rising AI demand, semis can catch a sympathy bid, but upside is likely capped without fresh capex revisions.
• If you need exposure to AI monetization, prefer quality compounders with multiple profit pools over single-product AI stories; the risk/reward is better in diversified platforms where AI is an option on top of existing cash flow, not the whole valuation.