Y Combinator's Stake in OpenAI (3 minute read)
OpenAI was seeded by an offshoot of Y Combinator called YC Research in 2016, when Altman was running YC. Y Combinator owns about 0.6% of OpenAI. At OpenAI's current valuation, that stake is worth over $5 billion.
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Anthropic is working on Orbit, its upcoming proactive assistant (2 minute read)
Orbit is a briefing and insights system in Claude and Claude Code that can produce personalized briefings with actionable insights drawn from connected work tools. Anthropic's Code with Claude developer conference will be held in San Francisco on May 6, London on May 19, and Tokyo on June 10. It is uncertain whether Orbit will be formally unveiled on stage or quietly rolled out.
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Automating AI Research (8 minute read)
AI is rapidly approaching end-to-end automation of its own R&D, with major gains in coding, experiment execution, and long-horizon task autonomy. Benchmarks show models now handle complex engineering and scientific workflows, manage other agents, and increasingly outperform humans on key subproblems. If trends hold, there's a ~60% chance of self-improving AI systems by 2028, leading to recursive progress, massive productivity gains, and a capital-heavy, human-light “machine economy.”
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Tuna-2 (GitHub Repo)
Tuna-2 outperforms both Tuna-R and Tuna across a diverse suite of multimodal benchmarks by using pixel embeddings. Meta plans to only release a foundation checkpoint rather than the full production-trained model weights. The release will have a small number of layers removed from both the LLM backbone and the diffusion head, but the remaining layers and all other components are fully preserved. Examples of images generated by the model are available in the repository.
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Consumer AI's ARPU problem (4 minute read)
ChatGPT's viral "smile" retention curve obscured a monetization gap because it tracked gross rather than net retention, with even the most engaged consumers capped at $20/month while Anthropic's $44B B2B revenue grows on per-user spend expansion. Consumer AI fails to capture value the way coding agents and legal AI do because users don't view answers or fun images as worth paying for and resist coughing up subscription dollars for savings they already pocket.
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Model-Harness-Fit (16 minute read)
Bustamante dissects Codex CLI, Claude Code, and GitHub Copilot CLI to show that frontier labs post-train models against specific harnesses, baking tool names, schemas, citation tags, memory rituals, and system prompt structures into the weights. Terminal-Bench 2.0 data backs the thesis: Claude Opus 4.6 scored 79.8% with ForgeCode versus 75.3% with Capy, and Cursor jumped from "Top 30 to Top 5" by changing only the harness, while OpenAI models default to patch-based file edits and Anthropic models to string replacement, with mismatches costing reasoning tokens.
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