Labs Become Consultants: OpenAI & Anthropic's New Play

In this episode of No-BS AI Briefing, host Vikash breaks down the significant strategic shift as OpenAI and Anthropic launch enterprise AI consulting joint ventures, redefining how they capture value and compete with solution providers. We also cover Mistral AI's exciting debut of Mistral Medium 3.5 and the innovative Vibe remote agents, enabling truly autonomous, long-running background tasks for builders. Get insights into the imminent Claude "Jupiter" model update, Sierra's massive $950M funding round validating enterprise AI applications, and Cisco's acquisition of Astrix Security, signaling the growing importance of AI agent security. For a practical takeaway, Vikash challenges builders to audit their AI products for "consulting-readiness." Hit follow to stay ahead with concise, opinionated briefings without the hype.

Transcript

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Anthropic and OpenAI just became consulting firms overnight. Mistral AI launched a new model, and more importantly, the infrastructure for truly autonomous agents. And we are breaking down what these huge moves mean for your products and your roadmap right now. This isn't hype, it's a strategic shift that could redefine how builders capture value in AI. NoBS AI Briefing brought to you by Proactive AI. Welcome back. I'm your host Vikash, and this is where builders get straightforward AI news without the fluff. First up, today we're talking about Anthropic and OpenAI launching enterprise AI consulting joint ventures. I mean, think about that for a second. Anthropic announced a whopping $1.5 billion joint venture, partnering with financial giants like Blackstone, Hellman and Friedman, Goldman Sachs, and General Atlantic. Their goal? To build a dedicated enterprise AI consulting arm, specifically targeting private equity portfolio companies. But here's the kicker. Almost simultaneously, OpenAI announced it's doing the exact same thing, following this same playbook with its own asset manager partners. What does this signal? It's a massive shift. Moving these big labs from just licensing models to offering full-stack enterprise AI services. For us builders, this isn't just news. It validates enterprise AI services as a truly major commercialization path. We should expect to see increased demand for deep integration, custom implementation, and those highly domain-specific solutions. It also creates partnership opportunities if you're already in that space. But let's be real, it also means the major labs are moving further up market, aiming to capture more of that value themselves. It's a strategic move that really shakes things up. Next, Mistral AI debuted Mistral Medium 3.5 and something really interesting called Vibe Remote Agents. So Mistrel released their new Mistral Medium 3.5, which is a dense model clocking in at 128 billion parameters, boasting an impressive 77.6% performance on SWE bench. That's solid. But the truly innovative part, they introduced vibe remote agents. These aren't just simple tool using agents. We're talking about asynchronous cloud-based coding tasks that run in persistent sandboxes, giving you completion notifications. Plus, they've added a work mode to their Lachar platform, enabling multi-step workflows complete with tool chaining and state management. For builders, this is a game changer. Vibe agents enable long-running background agent tasks that go way beyond just simple single-shot tool use. It lowers deployment friction significantly because you get persistence, error recovery, and async execution all out of the box. That means you can start prototyping really complex workflows much faster without having to wrestle with intricate infrastructure management yourself. Imagine the possibilities there for background automation. Also making headlines Anthropic's Claude Jupyter model is reportedly in red testing ahead of a May 6th event. Handy AI reported that Anthropic is actively red teaming a new Claude model. It's codenamed Clod Jupyter V1P, and this testing is happening right before Anthropic's conference, slated for May 6th. That timing, it very strongly suggests an imminent announcement. Now we don't have any specific capability or release details yet, which is typical for these things. But for us builders, this means a near-term model update is very likely coming our way. So you'd better start preparing to evaluate and potentially migrate your existing systems. We need to monitor that May 6th event closely for any API changes, new features, or performance improvements. And it's safe to assume that availability for developers will follow shortly after that announcement. It's time to get ready for whatever Jupiter brings. Moving on to funding, Sierra just raised a staggering $950 million for enterprise AI applications. Sierra, led by the well-known Brett Taylor, successfully closed this massive round with Tiger Global and GV leading the charge. This isn't just another big funding round, it's a huge validation for the entire category of enterprise AI applications and workflow automation. Sierra is positioning itself as a foundational platform for AI native business processes, which to me is incredibly exciting. Why does this matter for builders? Well, it reinforces what we've been saying. Enterprise AI is a highly fundable and rapidly growing market. This kind of investment signals robust investor confidence, moving well beyond just basic chatbots and into truly mission-critical workflows. If you're building in the enterprise space, this is a powerful confirmation of your direction. And finally, Cisco acquired Asterix Security for approximately $400 million. Cisco made a significant move by acquiring Asterix, a company that specializes in securing non-human identities and autonomous AI agents. What's interesting here is that Asterix was backed by Menlo Ventures and none other than Anthropic itself. This acquisition is a clear signal. For builders, it means that agent security is no longer a niche concern. It's rapidly becoming a strategic imperative as autonomous AI agents move closer to production environments. If you're building agents, you really need to prioritize authentication, authorization, robust audit trails, and proper containment mechanisms for those agents. This deal very clearly validates the entire AI security tool space and importantly highlights potential exit paths for startups in this critical area. The enterprise AI services shift while labs are becoming consulting firms. This story for me is the most important and interesting of the batch, and here's why. Both Anthropic and OpenAI are making this really aggressive move. They're shifting from simply licensing their foundational models, you know, charging for API calls to becoming full stack service providers. They're literally reshaping how they capture value and how they compete in the market. What happened? For the past couple of years, these labs primarily focused on competing against each other based on raw model quality and API pricing. They largely left the complex, messy work of enterprise integration and implementation to third parties, to the consulting firms, and to product companies like yours. But now we're seeing both Anthropic and OpenAI launching these massive joint ventures with major financial institutions. They're going direct, they're adopting a technology plus services playbook aiming to deliver end-to-end outcomes for enterprises. I mean, it's a classic move in enterprise tech, but seeing the foundational model labs do it, that's new. Why does it matter right now? This isn't just some theoretical market shift. It's happening. It changes the competitive landscape for everyone. For product builders, it means the API arbitrage play just building a thin wrapper around a foundational model is shrinking. The value is moving further up the stack. Enterprises aren't just looking for an API endpoint anymore. They're looking for complete solutions that actually work within their complex, messy environments. So this shift directly impacts market dynamics, product roadmaps, and even how development teams structure themselves. Who should care about this? Honestly, everyone building an AI. Founders, you need to rethink your value proposition. Are you just consuming an API or are you creating deep proprietary domain expertise that labs can't easily replicate? Product managers, you've got to consider how your product fits into this new full-stack offering. Are you a partner or are you now a potential competitor to the very labs whose models you use? Engineering leaders, this affects your build versus buy decisions and how you approach integration. Even indie hackers, you need to understand where the defensible modes are because simply relying on model access might not be enough long term. How I'd think about it as a builder. Look, this is about strategic positioning. If I'm a startup, I can't out capital anthropic or open AI. What I can do is focus on hyper-specialization, developing deep domain expertise in a specific vertical or for a particular use case that these massive broad JVs might struggle to address with the same agility or nuance. Or I could become a best in class implementation partner for these labs, bridging the gap between their offerings and unique enterprise needs. The key takeaway is that the value is really accruing at the application layer at the solution level. Enterprises want outcomes, not just components. The risk here is that these well-funded JVs start hoovering up the big enterprise deals, leaving smaller, less complex problems for the rest of us. It's a good time to double down on your unique differentiation. My no BS take. This isn't just hype. The funding scale is real, and the explicit move into consulting by the major labs is a strategic play born from market demand and likely pressure to grow beyond pure API revenue. There's execution risk, of course. Consulting is a very different beast from software development, but the intent is clear. They want a bigger piece of the pie. Builders need to pay attention, understand their new place in the ecosystem, and adapt fast. If you're finding this useful, hit follow in your podcast app right now. It takes two seconds and it's the best way to make sure you don't miss the next briefing. If you want one practical takeaway from today's episode, here it is. Audit your AI product to make it consulting ready. This doesn't mean you become a consulting firm, but you need to understand the full life cycle of getting your product into a customer's hands and delivering actual value. Here's how to try it in under 30 minutes. First, list your top three use cases that customers actually get value from. Next, for each use case, note down exactly what customers need in terms of implementation, customization, training, and ongoing support to achieve that value. Finally, identify the gap between what your product provides out of the box and what those customers typically need. Why is this specific experiment worth your time right now? Because with the major labs moving into services, every AI product needs to implicitly or explicitly address the full solution stack. Understanding your own product-to-service gap now will help you either build out those capabilities, streamline your integration process, or find ideal partners before the market fully shifts. It's about being proactive, not reactive. That's it for today's NoBS AI briefing. If this helped, follow the show in your podcast app and share it with one builder you know. And if you've got questions or topics you want covered, connect with me on LinkedIn and send them over. See you in the next briefing.