Shaun Anderson

Schrödinger’s rankings

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.

The reason the ai engines dont cite the same stuff is a) they fan out in wildly different ways b) have different patterns around how much they cite by domain and c) even have slightly different objectives around what and why they cite. They could use exact same search index and theyd be citing totally different stuff.

1️⃣ Most AI tools give you an assistant. Agency gives you a team. Agency demonstrates what an actual Agentic Agency looks like: specialised AI employees working together under your direction. You remain the CEO. The team does the groundwork. By your command.

While some still debate what AI search optimization should be called (GEO, AEO, LLMO…), companies have already answered the question that actually matters: who does the work 👇 I did a poll asking who's in charge of AI Search Optimization in the company you work at/with and after 1,212+ votes, the debate is settled: * 86% The SEO team * 9% An AI Search team *with* SEOs * 1% An AI Search team *without* SEOs * 2% Another digital marketing team That's 95% of companies where SEOs are leading or directly involved in AI search efforts. Only 1% have handed it to a team without SEOs. Yes, my audience skews SEO but even with that bias, a 95 to 1 ratio is hard to argue with! The reality is that AI search optimization is being executed by the people who already understand *search* as a discovery/marketing channel... the pillars have been expanded, not replaced. So rather than debating the name, the real questions to focus on are: ⭐️ Are SEO teams being resourced and enabled to take on this expanded scope? ⭐️ Are they being included in the AI conversations happening at the exec level? ⭐️ Are they measuring beyond traffic to show AI search business impact? Remember: Just buying an AI search optimization tool isn't a real strategy! Ownership without enablement is accountability without support. ✅ If you're an SEO who's been handed AI search: congratulations, and also, negotiate: Expanded scope should come with expanded support. ✅ If you're a leader who's assigned it to your SEO team: make sure they have a seat at the table where AI strategy decisions are made, not just the ticket queue. It's time to focus on what actually matters: AI search growth 🙌