Troubled Labs, Agent harnesses & Massive rounds

TLDR;

Welcome back! First, I owe you an apology. Many of you have noticed the slower cadence these past two weeks. I’ve been mostly out of work due to personal reasons, but I can officially confirm I’m back.

There’s a lot to catch up on, so I’ll first send this email and another one on Saturday/Sunday based solely on news, so you can get back on track with AI. I promise you that, in two days, you’ll feel like I never left.

Let’s dive in.

FUNDING

Anthropic’s Margins Fall

Based on reports, Anthropic has quietly lowered its outlook for 2025 profitability, projecting a 40% gross margin after inference and selling costs, 100 basis points lower than the original expectation of 50%, because it is paying more than expected to run its models for customers on Google and Amazon infrastructure.

Internal projections showed inference costs coming in 23% above plan, dragging margins even as the company’s gross margin has rebounded sharply from a deeply negative level in 2024.

The revised outlook highlights how cloud dependence is squeezing leading AI developers. Despite what we thought until now, Anthropic appears less efficient than OpenAI, which has projected a roughly 46% gross margin in 2025, even after accounting for inference costs for free ChatGPT users.

Despite the margin reset, Anthropic is still forecasting explosive growth. The company expected $4.5 billion in 2025 revenue, nearly 12 times its 2024 total, driven primarily by API sales to businesses and developers, with subscriptions making up the remainder.

TheWhiteBox’s takeaway:

As we saw in the IPO prospectuses from Chinese Labs Zhipu and Minimax (and with OpenAI below), Labs continue to struggle to escape the high costs of progress (recall that Anthropic is talking about gross margins, meaning they aren’t considering operating costs—wages, R&D, and, of course, CapEx investments in hardware).

Thus, the profitability guidance remains, unsurprisingly, terrible. The problem? I believe it’s mostly out of their control. AI workloads are memory-bottlenecked, meaning the accelerators, priced at huge markups like NVIDIA’s 4x over production costs, are mostly underutilized; what could be theoretically done with two accelerators has to be done with four due to memory limitations.

Coupled with continuous pressure to lower prices because the underlying technology is mostly commoditized, it makes it literally the worst business possible: unprofitable, costs growing faster than revenues, and products with heavy competition and comparatively low differentiation.

The only reason to stay is that those who win will win big, but only after leaving an entire cemetery of companies behind.

With such a dark picture, it’s no wonder that Anthropic, as OpenAI, is leaning on massive fundraising: Anthropic is discussing a round above $10 billion at a reported $350 billion valuation, while OpenAI is in talks for financing that could reach $100 billion and value it around $750 billion.

And talking about OpenAI…

CAPITAL

OpenAI’s Desperate Capital Requirements

Talking about OpenAI, EpochAI has done a thorough analysis to estimate the “real costs” of AI. But what does ‘real’ mean here?

On rare occasions…

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