posts · 2026-08-20

This one's worth opening because OpenAI finally put a concrete IPO window on the table and shared internal numbers to back it up. CFO Sarah Friar told staff the company will go public by 2027, possibly sooner, and framed the IPO as "just another form of funding" — a line aimed at calming both employees and the market. The numbers: Q2 revenue hit $6.7B, up 18% quarter-over-quarter. Enterprise annualized revenue jumped 50%, and weekly active users for coding and office products crossed 20 million. But here's the comparison that stings: Anthropic reported $11.5B in Q2 revenue and a $65B annualized run rate. OpenAI is now visibly behind on the top line. I'd discount the upbeat tone a bit. The timing of this all-hands is hard to ignore. The revenue lead left after 8 months, the product head stepped down in July, and a veteran exec just announced his departure. Sharing growth metrics and an IPO timeline right now reads like a deliberate attempt to project stability. Greg Brockman told CNBC the turnover "isn't that unusual," but investors will be watching whether more names head for the door in the coming months.

This piece nails the structural difference between how the US and China block NVIDIA. The US plays a transparent cat-and-mouse game: four rounds of public export rule updates, and NVIDIA responds each time by trimming specs to stay just under the line—A800, H20, 5090D V2. The rules are clear but always lag behind engineering workarounds. China operates in reverse: zero written bans, but a combo of regulator meetings, customs rejections, case-by-case NDRC approvals, antitrust probes, and rare-earth leverage quietly kills NVIDIA's product lines one by one. The H200 case is the clearest example. The US approved over 400,000 export licenses; Chinese customs blocked entry within hours, and only 20,000 units actually cleared over six months. FT reported a telling sequence: regulators first confirm Huawei's chips match the NVIDIA variant in real workloads, then shut the import door. Huawei's CloudMatrix 384 clusters 384 910C chips to beat GB200 NVL72 by ~40% in system performance, but at 4x the power draw. It's a brute-force swap: cheap electricity and chip volume for per-chip performance. One gap worth noting: every China-side action in this story is sourced to media reports and anonymous officials, not a single public document. That's not a reporting flaw—it's evidence of how the machine works.

This piece clicked for me because it cuts through the "AI kills middlemen" debate with a clean framework. Middlemen earn two types of rent: information rent from knowing things others don't, and liability rent from being the one who signs and pays when things go wrong. AI vaporized the first. The second hasn't moved. Across 30+ companies surveyed, the survivors are all piling into liability-heavy positions. EvenUp requires lawyer sign-off on every document. Boundless enforces four rounds of human review. Xometry routes all complex drawings to engineers. These aren't transitional crutches—the human review is the product. Clients pay for a professional's signature on the line. The cautionary tale is Convoy. Raised $900M, hit a $3.8B valuation, ran out of money in 2023, sold tech assets for $16M. It wasn't an algorithm failure. It was a business model that earned neither information rent nor liability premium in a commodity freight market. I'll remember the closing heuristic: figure out who signs and who pays when things go wrong before evaluating anything else. Beats any framework.