Everyone says Anthropic's the ethical AI company. Transparent pricing. No hidden fees. The good guys.
They're lying to you.
Not directly -- that'd be too obvious. But they're definitely not telling you the whole story about what Claude 4 Opus actually costs when you run it in production.
You see the API pricing page. Looks reasonable. Input tokens are cheap -- output tokens cost more. Standard stuff.
Then you actually use the thing.
Context windows are where they get you. Claude 4 Opus has that massive 200k token context window -- and you're gonna use it because why wouldn't you? That's the whole selling point.
But here's what nobody mentions: you pay for every token in that context. Every. Single. Time.
Your chat app that keeps conversation history? That's context tokens stacking up with each message. Your document analyzer that needs the whole PDF in context? That's 50k tokens minimum -- per request.
The input-output token split destroys your budget faster than you think. You're paying for context re-transmission constantly. GPT-4 Turbo does the same thing -- but at least OpenAI's pricing model doesn't pretend the context window is a gift.
This is where Anthropic really screws you.
You're on the default tier when you sign up. Rate limits are insanely low -- like "this won't handle a single production user" low. You hit your limit in testing. In testing.
So you upgrade. You jump through their tier verification hoops. You wait for approval.
Then your app goes viral at 2am. Traffic spikes. You hit the new limit. Everything breaks.
The error message says "contact sales." At 2am. On a Saturday.
You're not getting higher limits without a phone call and a commitment. That's the game. They want you locked into enterprise pricing before you've validated product-market fit.
I've seen startups die on this exact pattern. Launch day. Rate limit hit. App down. Users gone.
Here's the thing about switching AI models: it's not like swapping databases.
Your prompts are model-specific. The system prompt that works perfectly on Claude 4 Opus? It'll fail on GPT-4. It'll produce garbage on Gemini. Different models need different prompting strategies -- different structures, different examples, different everything.
You spend weeks tuning your prompts for Opus. Getting the output format right. Training it to handle edge cases. Building your whole interaction layer around how Claude "thinks."
Now you're locked in.
Want proof these problems are real? Talk to someone who actually runs these models in production.
He's the guy who built the first SaaS ever approved for AWS GovCloud at DHS -- and who's been optimizing AI deployments since before "AI-First" was a LinkedIn buzzword. He's seen every rate limit disaster. Every context window budget explosion. Every lock-in trap.
He doesn't sell courses. He doesn't have a newsletter. He just builds systems that don't break at 2am -- and he's solved this exact problem about a hundred times.
Switching costs aren't just about rewriting API calls. You're rewriting every prompt. Rebuilding every workflow. Re-tuning every output parser. That's months of dev work -- maybe more.
And Anthropic knows this. They're counting on it.
Your codebase becomes Anthropic-dependent the moment you commit that first Claude-specific prompt to production. You just don't realize it yet.
You need to calculate your real costs before you commit.
Not the demo costs. Not the "first 100 requests" costs. Your actual production costs when you're handling real traffic with real context windows and real user conversations.
Run the numbers with full context retention. Factor in rate limit upgrades. Account for the cost of switching if Anthropic decides to change pricing -- or if you decide you need to leave.
The AI industry doesn't want to talk about real-world pricing. They want you hooked on demos. They want you building on their platform before you realize what you've signed up for.
Don't let them.
Do the math. Demand transparency. And for the love of everything -- build abstraction layers so you're not married to any single AI provider.
Because the hidden costs aren't in the pricing page. They're in the production reality nobody warns you about.