Apple just sued OpenAI, and the wildest part is how they got caught: one candidate screenshotted confidential Apple files on his Apple work laptop hours before his OpenAI interview. Apple reads its own server logs. The recruiting pipeline generated its own evidence trail. The complaint says OpenAI's hardware chief Tang Tan, a 24-year Apple veteran, directed candidates still employed at Apple to bring "actual parts" (batteries, logic boards) to interviews for show and tell sessions. One candidate was surprised, saying he didn't even know you could take those out of the office. Apple also alleges Tan circulated an internal Apple offboarding document to coach new hires on dodging exit security checks, and that a departing engineer kept his Apple laptop, found a bug that still gave him access to Apple's cloud storage, and downloaded dozens of confidential hardware files after joining OpenAI. Then the supplier: OpenAI allegedly got one of Apple's manufacturing partners to demonstrate a proprietary metal finishing technique by letting the partner believe Apple had approved it. Over 400 former Apple employees now work at OpenAI. Apple says it flagged all of this to OpenAI in February and never got a response. Five months later, it filed. The ask reveals the strategy. Apple wants an injunction barring OpenAI from using the secrets, the return of every file, and full discovery into io, right as OpenAI preps its first device launch and an IPO. If a judge grants it, OpenAI may have to prove the device was built clean, component by component, before it ships. The device was supposed to run on the world's best hardware talent. Now its bill of materials is evidence.

Grok 4.5 from @spacexai places #2 on the APEX-SWE leaderboard at 51.2% Pass@1 (±6.0), behind Fable 5 (65.5% ±6.2) on our benchmark for real-world software engineering work. It leads Integration (65.0% Pass@1) and places #2 in Observability (37.3% Pass@1), covering multi-step build tasks and diagnosis/debugging respectively. The Integration lead maps directly to the agentic workflows Grok 4.5 was built for: multi-step coding tasks run in collaboration with Cursor. Grok models have improved 30.2 pp in a year on this benchmark: Grok 4 (21.0% Pass@1) to Grok 4.5 (51.2% Pass@1). Congratulations to the xAI and Cursor teams.