OpenAI and Anthropic Have a Trillion-Dollar Problem

DeepSeek reportedly reached a $1 billion annualized revenue run rate while giving away its AI models and infrastructure. Meanwhile, OpenAI is pursuing expensive subscriptions and enormous infrastructure spending.The numbers are interesting. DeepSeek reportedly achieved an 82% API gross margin, compared with OpenAI's reported 39% gross margin in the first quarter.But the bigger story is the strategy.DeepSeek is releasing model weights, research, and even its inference framework, betting that it can win by offering efficient, low-cost AI rather than locking everything behind subscriptions.In this video, I break down why I think DeepSeek is playing a different game from OpenAI and Anthropic, what its potential Huawei chip partnership could mean, and why we believe in the same open-source, local-first approach with OpenMonoAgent.Can DeepSeek's open-source strategy beat OpenAI's subscription-based business model?

The AI industry could need $10 trillion in infrastructure investment over the next decade. Amazon says demand for AI computing is stretching years into the future, but there's a much bigger question: who's going to pay for all of this?OpenAI and Anthropic are growing fast, but the cost of building and operating this infrastructure is staggering. Some estimates suggest data centers would need to generate $8.5 trillion in revenue to justify the investment. I'm not convinced the financial math works.I think we're eventually going to hit a funding wall. That doesn't mean AI disappears. The technology is here to stay, and open-weight models could give smaller businesses a major advantage without depending on expensive subscriptions and cloud providers.So what do you think? Is this the biggest financial bubble in tech history, or are we underestimating how much AI demand will grow?

Anthropic's revenue is growing fast. But I think there's a much bigger problem hiding behind those numbers.We're talking about a company that reportedly has more than $518B in future AI compute commitments.That's an enormous amount of money to spend on infrastructure, especially when the revenue growth may already be slowing.And here's what really bothers me.Anthropic keeps talking about being profitable on an adjusted basis.Adjusted profits. Adjusted margins. Adjusted cash flow.Okay, but what does the business actually cost to run?You can't keep celebrating revenue growth while ignoring the enormous cost of building and operating these AI models.Then there's Amazon and Google.They're investors, infrastructure providers, and major distribution partners for Anthropic. That's a lot of dependence on companies that are also building competing AI products.And now we're hearing about potential IPO valuations approaching $2T.I don't buy it.I think Anthropic is going to have a very difficult time getting through the financial scrutiny that comes with going public. And even if it does, I don't see how a $2T valuation makes sense based on the numbers being discussed.I've said it before. Revenue is not profit, and growth doesn't automatically mean you've built a sustainable business.The AI industry needs to start paying attention to what these companies actually spend, not just what they bring in.Would you invest in Anthropic at a $2T valuation, or do you think the AI bubble is getting out of control?

Anthropic just made a major move to stop other AI labs from copying Claude, but there's a catch that could hurt its own business.The company says its new defenses have reduced the amount of Claude's reasoning that competing labs can extract by up to 99%. Tens of thousands of accounts have been blocked, and trillions of tokens of suspected distillation traffic have been turned away.Here's where things get interesting.Those accounts weren't necessarily using Claude for free. Some were paying customers generating enormous amounts of API traffic.So what happens to Anthropic's revenue when that activity disappears?The company is trying to protect its intellectual property, which makes sense. But cutting off paying traffic could affect growth expectations, especially with questions surrounding a potential IPO.And there's another problem. Paying Claude customers are also losing access to some reasoning details, while certain blocked requests can still incur charges.At StartupHakk, we've been advocating for local-first AI because businesses shouldn't have to depend entirely on models and pricing rules they don't control.Anthropic may be protecting Claude, but the financial consequences could be much bigger than people expect.Do you think Anthropic is making the right move, or could this crackdown end up hurting its business?

Microsoft is developing its own 137B-parameter coding model and bringing powerful AI agents directly to Windows PCs. With Nvidia's new hardware and GitHub Copilot's hybrid approach, more AI workloads could run locally instead of relying entirely on the cloud.Here's what's interesting.Microsoft spent years helping OpenAI grow. Now it's building its own models and infrastructure that could reduce its dependence on OpenAI. Meanwhile, Nvidia wins on both sides by supplying the hardware for cloud AI and local machines.But there's a catch. Running large AI models locally requires serious memory, the most powerful hardware isn't cheap, and Microsoft's approach still depends on the cloud for certain tasks.At StartupHakk, we've been advocating for local-first AI because businesses should have more control over their models, data, and infrastructure.The question is whether Microsoft can make local AI powerful and affordable enough to change how we use AI.Would you buy a Windows PC specifically to run AI locally, or would you rather stick with cloud AI?

Microsoft CEO Satya Nadella just made a serious point about AI security: businesses should treat AI models like potential insider threats.And Microsoft is already acting on it with new Execution Containers designed to keep AI agents isolated.OpenAI Codex is also adopting stronger sandboxing controls.I've been saying this for a long time. AI agents shouldn't have unrestricted access to your files, code, credentials, and business systems.At StartupHakk, we built OpenMonoAgent around sandboxing, command logging, and local-first AI because security shouldn't be something you add after something goes wrong.The future of AI isn't just about smarter models. It's about controlling what those models can actually do.Would you trust an AI agent with unrestricted access to your company's data?

The White House just accused Microsoft of abusing the H-1B visa system while American tech workers face layoffs.Now Microsoft, Adobe, and six major outsourcing firms have been suspended from the PERM green card program.But here's the twist.Hours after the crackdown, President Trump awarded Microsoft CEO Satya Nadella a national technology medal.Microsoft says 80% of its roughly 6,000 H-1B filings were for existing employees, not new hires.I've heard complaints about this system for years. American workers deserve a fair shot at these jobs, but immigrant employees shouldn't be trapped in a system where their future depends on one employer.And despite the headlines, this isn't a blanket H-1B ban. It's a freeze on a critical part of the green card process.So is the government actually fixing the problem, or are workers on both sides paying the price?What do you think?https://StartupHakk.com

Meta Is Betting Big on Muse. And It’s Winning.$27B a year.That's what Citi reportedly thinks Meta Muse could generate by 2030. Deutsche Bank's upside case goes even higher.And Meta doesn't have to play the same game as OpenAI and Anthropic.Instead of making money every time you burn another pile of tokens, Meta can give away enormous amounts of AI usage and take a small cut when Muse helps you actually buy something.Meta already has the users. It already has the distribution. It already has the advertising machine.Now Zuckerberg may have found the AI product to put on top of it.I've bashed plenty of his decisions in the past, but I'll give him this one: Muse is a real product.Would I use it? Absolutely.Would I give Meta my production data, banking information, or sensitive company data? No.For that, I still want AI running on infrastructure I own and control.

Microsoft had reportedly been on track to spend more than $1B a year with Anthropic.Some engineers inside Microsoft's Cloud and AI group reportedly had AI budgets reaching $100,000 a month.Now Microsoft is cutting those budgets, reducing Claude spending, and directing employees toward GitHub Copilot and its own ecosystem.Meta is doing something similar.Tens of thousands of Meta employees had been using Claude Code, but Meta has been expanding its own internal AI coding tools instead.And all of this is happening as Anthropic moves toward a potential IPO with 2 customers reportedly accounting for roughly 25% of its revenue.That's worth paying attention to.Because while some of the biggest companies in technology are learning that renting massive amounts of AI compute gets expensive very quickly, Anthropic is simultaneously warning about the dangers of powerful open-weight models.We see the open-weight story differently.Yes, powerful models can be misused. But open weights also let defenders run models against their own code, keep sensitive data inside their own infrastructure, modify the system, and build tools without depending on a closed provider to decide what they're allowed to do.Microsoft and Meta can afford to build their own AI infrastructure.The rest of us should at least learn how to own more of ours.Stop thinking of AI as something you have to rent forever. Learn the stack. Own the infrastructure.

91% of households pay for streaming.55% pay for cloud storage.Only about 2% pay for AI.For all the talk about AI taking over everything, almost nobody is actually writing a monthly check for it yet.Meanwhile, we're pouring enormous amounts of money into GPUs, semiconductors, data centers, and AI infrastructure.That's not a victory lap. It's a bubble check.The AI boom feels enormous if you live inside it every day, but the numbers show just how early we really are. Mass adoption hasn't happened yet—and when it does, it may look less like everyone buying a chatbot and more like AI disappearing into the software we already use.If you feel behind, you're not. Most people haven't even started.