# OpenAI’s Chip Bet, Databricks’ Agent Stack, and Open Models’ New Push

*By AI News Digest • June 25, 2026*

The clearest theme today was verticalization: OpenAI moved into custom chips, Databricks widened its enterprise-agent infrastructure push, and open models posted stronger reasoning and coding signals. The digest also covers a $200M AI-for-AI startup launch and fresh governance and copyright pressure.

## The stack is getting more vertical

### OpenAI unveils its first custom inference chip
OpenAI introduced Jalapeño, its first AI chip, built with Broadcom for LLM inference workloads across ChatGPT, Codex, the API, and future agentic products [^1]. Greg Brockman said the chip was designed from scratch in nine months, accelerated by OpenAI’s own models, with strong performance per watt [^2].

**Why it matters:** OpenAI explicitly framed Jalapeño as an expansion of its full-stack platform from products and models into infrastructure [^1].

### Databricks widens its enterprise-agent infrastructure push
At its 2026 Data + AI Summit, Databricks launched Omnigent, an open-source meta-harness for sharing and controlling agents across Claude Code, Codex, Cursor, and custom tools, with contextual security policies and spend controls [^3][^4]. It also pushed LTAP as a way to let agents work from live operational data without brittle CDC pipelines, and framed the broader effort as a move to become the operating system for enterprise agents [^3][^4][^3].

**Why it matters:** This is a bet on the surrounding agent stack—harnesses, permissions, collaboration, and data access—not just the model layer [^5].

## Open models keep adding stronger evidence

### GLM-5.2 posts new reasoning and coding signals
ARC Prize reported that Z.ai’s GLM-5.2 reached 22.8% on ARC-AGI-2 and 77.0% on ARC-AGI-1, with performance described as comparable to GPT-5.4 and GPT-5.5 at low reasoning effort [^6]. François Chollet called it the strongest ARC-AGI-2 result so far from an open-source model, and a separate Reddit-posted benchmark write-up reported that GLM-5.2 matched Claude Opus on 45 terminal-bench coding-agent tasks while costing about 46% as much with prompt caching; the model is now also available in Cursor via Fireworks [^7][^8][^9].

**Why it matters:** The newest open-model gains are showing up in both reasoning tests and agentic coding workflows, not just lower-cost chat.

## AI-for-AI attracted a major new bet

### MirendilAI launches with a $200M seed around self-accelerating R&D
MirendilAI formally launched with a $200 million seed round led by a16z and Kleiner Perkins, with a major investment from NVIDIA, and said it is focused on self-accelerating AI R&D as a way to speed scientific progress across domains [^10]. The company says its founding team includes 20 researchers and engineers from Anthropic, xAI, Google DeepMind, and OpenAI, while Martin Casado said the launch points to an autocatalytic phase of AI model development [^10][^11].

**Why it matters:** AI improving AI is moving from a research ambition into a well-funded company thesis. That matters because Jack Clark separately said he would bet on recursive self-improvement arriving toward late 2028, with the potential to compress progress timelines further [^12].

## Governance and legal pressure kept broadening

### The debate moved from cyber risk to deployment limits and IP
Anthropic said it maintains red lines against domestic mass surveillance of Americans and fully automated weapons, and Jack Clark said the company is in daily discussions with the U.S. government over export-control policy for models like Fable because of cyber and bio concerns [^12]. Demis Hassabis separately warned that bio and nuclear risks may sit beyond today’s cyber issues and called for an international standards body to test frontier systems [^13].

**Why it matters:** The policy boundary is expanding beyond model access into explicit use red lines and testing standards. Separately, Gary Marcus highlighted a new publishers’ copyright lawsuit against Microsoft and OpenAI over alleged unauthorized content use [^14][^15].

---

### Sources

[^1]: [𝕏 post by @OpenAI](https://x.com/OpenAI/status/2069770172802773292)
[^2]: [𝕏 post by @gdb](https://x.com/gdb/status/2069809298612621629)
[^3]: [Why the Frontier Ecosystem must be Open — Matei Zaharia and Reynold Xin, Databricks](https://www.latent.space/p/databricks)
[^4]: [The Agent Cloud: Databricks’ Bet on the Future of AI — Matei Zaharia and Reynold Xin](https://www.youtube.com/watch?v=Yp_u1NpbkJg)
[^5]: [𝕏 post by @latentspacepod](https://x.com/latentspacepod/status/2069857879847526632)
[^6]: [𝕏 post by @arcprize](https://x.com/arcprize/status/2069845152773099854)
[^7]: [𝕏 post by @fchollet](https://x.com/fchollet/status/2069858556552298519)
[^8]: [r/LocalLLM post by u/entelligenceai17](https://www.reddit.com/r/LocalLLM/comments/1uemsjc/)
[^9]: [𝕏 post by @leerob](https://x.com/leerob/status/2069904679551611080)
[^10]: [𝕏 post by @bneyshabur](https://x.com/bneyshabur/status/2069860934148079800)
[^11]: [𝕏 post by @martin_casado](https://x.com/martin_casado/status/2069901037088211068)
[^12]: [Is AI Really Taking All the Jobs? Anthropic Co-Founder Reveals the Data](https://www.youtube.com/watch?v=OG3s4pojdZY)
[^13]: [DeepMind Chief Demis Hassabis Says Google’s Still Winning AI Talent | Semafor Tech](https://www.youtube.com/watch?v=hb9JPW_DkpQ)
[^14]: [𝕏 post by @GaryMarcus](https://x.com/GaryMarcus/status/2069943216678527131)
[^15]: [𝕏 post by @cecianasta](https://x.com/cecianasta/status/2069891575128195324)