What began as a bruising corporate feud between Elon Musk and OpenAI is now pulling Meta into the legal storm, as the ChatGPT-maker asks the court to force Mark Zuckerberg’s company to hand over documents linked to Musk’s attempted takeover.

In a court filing made public Thursday, OpenAI revealed that it subpoenaed Meta back in June for records that could shed light on whether Zuckerberg or his company coordinated with Musk and his AI startup, xAI, during Musk’s unsolicited $97 billion bid to buy OpenAI earlier this year. The filing states that OpenAI’s legal team had learned Musk communicated with Zuckerberg about xAI’s interest in purchasing the company, including “potential financing arrangements or investments.” It remains unclear whether any such documents exist, and OpenAI ultimately rejected Musk’s approach.

Meta objected to the initial subpoena in July, prompting OpenAI’s lawyers to now seek a court order that would compel Meta to turn over the evidence. In addition to documents on Musk’s takeover attempt, OpenAI also wants access to Meta’s communications on “any actual or potential restructuring or recapitalization of OpenAI” — an issue at the heart of Musk’s lawsuit against the company.

Responding to inquiries, Meta spokesperson Andy Stone pointed to a section of the filing where OpenAI itself acknowledges that neither Meta nor Zuckerberg signed Musk’s letter of intent to acquire the firm. Beyond that, Meta declined further comment.

This legal tug-of-war comes against the backdrop of intensifying rivalry between OpenAI and Meta. In 2023, Meta poured resources into building a frontier AI model capable of outperforming OpenAI’s GPT-4, filings in a separate case revealed. But by early 2025, Meta’s AI projects were lagging the industry standard — reportedly infuriating Zuckerberg, who has since doubled down.

That spending spree means a court-ordered disclosure could carry significant financial implications for Meta. If Zuckerberg’s discussions with Musk touched on potential joint ventures or financing, the documents could reveal how seriously Meta weighed investing in or even acquiring pieces of OpenAI at a time when it was already funneling vast sums into AI. Any evidence showing overlap between Meta’s hiring strategy and Musk’s xAI ambitions could also raise questions among investors about whether the social media giant was hedging its bets or considering partnerships in the escalating AI arms race.

In recent months, the Facebook parent has escalated efforts by raiding talent from OpenAI itself. Among the biggest hires was Shengjia Zhao, a co-creator of ChatGPT, who now leads Meta Superintelligence Labs. Meta has also invested heavily in outside ventures, including a $14 billion stake in Scale AI, and has reportedly held talks with other AI companies about potential acquisitions.

That backdrop makes any possible coordination between Musk and Zuckerberg even more intriguing. Less than two years ago, the two billionaires exchanged barbs about fighting in a physical cage match — a spectacle that never materialized. Yet, the escalating arms race in AI may have pushed them closer to pragmatic cooperation, at least on paper.

The briefing made public on Thursday forms part of Musk’s wider lawsuit with OpenAI. The Tesla and SpaceX chief, who co-founded OpenAI in 2015, is challenging its restructuring into a for-profit entity with a public-benefit arm — a shift designed to attract deep-pocketed investors and pave the way for a potential IPO. Musk contends the move betrayed OpenAI’s founding mission and is seeking to derail it.

Meta’s lawyers, however, want the court to shut down OpenAI’s request for evidence, arguing that Musk and xAI themselves are better placed to provide the information. They also claim Meta’s internal discussions about OpenAI’s restructuring or recapitalization are irrelevant to Musk’s case.

In today’s Tekedia Daily podcast, I focus on effective enterprise AI strategy. The podcast emphasizes that AI is more than just a technological tool; it’s a catalyst for profound business transformation. A successful strategy must be built on four key pillars: having a clear vision tied to the company’s strategic goals, ensuring a quantifiable value realization, planning for widespread adoption, and proactively managing risk.

Furthermore, AI must influence all four key vectors of the business: customers, employees, technologists, and partners. This concept with AI at the heart – the AI centricity – ensures that all parts of the organization are interconnected and drawing from a shared AI-powered stack.

True success isn’t just about using AI to run existing processes; it’s about using it to transform the business model entirely. This requires redefining the roles of people, reinventing processes, and deploying new tools. The ultimate goal is to become an “AI-native” business, where AI is at the core of operations. Bank A  used IT to replace typewriters, Bank B used IT  to link all bank branches together, evolving a new business model where customer accounts are agnostic of location.

Good business is anchored on a great business model. The “One Oasis Strategy” highlights how a powerful, customer-facing product can create a loyal following that generates value in unexpected but highly profitable areas. Ultimately, the goal is not merely innovation for its own sake, but using AI to influence industrial intelligence and create products and services that customers genuinely love.

Podcast Video: Sign-up at Blucera and check Tekedia Daily podcast category under Training module.

Vibe coding won’t spell the end for productivity software — at least not anytime soon. That was the position of LinkedIn cofounder Reid Hoffman during an episode of his Possible podcast released on Wednesday.

Vibe coding, a term coined earlier this year by OpenAI cofounder Andrej Karpathy, refers to the growing practice of developers prompting AI systems to generate code. The approach has gained traction across Silicon Valley in recent months, with some companies even listing “vibe coding” as a necessary skill in their job postings.

Hoffman, however, cautioned against assuming that the rise of new technologies automatically means the decline of existing ones. Responding to a question on the longevity of tech shifts, he said people often “overpredict, in the new things, the death of the old.”

He pointed to the early years of mobile technology as an example. “A classic one is when mobile started growing, people said PCs are over. And what happens is PCs grow — like mobile grows a lot more — but PCs have continued,” Hoffman explained.

In his view, the same pattern will play out with vibe coding. Rather than wiping out productivity software, he believes the two will coexist and, in some cases, complement each other.

“For example, one of the memes right now is vibe coding is going to wipe out productivity software,” Hoffman said. “What I think you’ll see is productivity software will continue, and then vibe coding is going to add on to it.”

He added that the disruption won’t be immediate or absolute. “It’s not going to be like suddenly productivity software is going to go away. That’s the pattern that people need to understand.”

Hoffman, who is also a partner at venture capital firm Greylock Partners, underscored the point from an investor’s perspective. He said that emerging technologies often follow a cycle: they coexist with older systems for a while before eventually replacing them, but the replacement happens quickly when it does arrive.

“‘I want to bet on mobile, or I want to bet on, maybe, vibe coding,’” Hoffman said. “But it’s a very standard pattern that what happens is, it persists for a while. And then, by the way, when it dies, it dies very quickly, in a smaller number of years.”

The debate around vibe coding reflects a larger conversation happening in the software industry: whether AI-driven coding will fundamentally alter the way developers build applications and whether it signals the start of a new paradigm in productivity tools.

In fact, the landscape of productivity software already reflects Hoffman’s prediction of coexistence and integration rather than replacement. Microsoft, for instance, has not abandoned its flagship Office products but has instead layered AI on top of them through Copilot, an AI assistant that integrates with Word, Excel, and Outlook. Rather than vibe coding making Office irrelevant, the company is demonstrating how AI can enhance traditional productivity workflows.

Google is following a similar path, embedding its AI model Gemini into its suite of Workspace tools. Gmail can now draft responses automatically, Google Docs can generate or summarize text, and Sheets can analyze data patterns far faster than before. Here too, productivity software is not being displaced — it is being upgraded.

Even newer entrants like Notion, long considered a modern rival to legacy productivity apps, have embraced AI not as a side experiment but as a core feature. Its “Notion AI” can summarize meetings, draft project outlines, and manage knowledge bases within the same platform users are already accustomed to.

These examples show that rather than vibe coding sweeping away productivity tools, AI is becoming a complement to them — echoing Hoffman’s larger argument that new paradigms usually build upon existing ones before reshaping them.