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Don't Be Claude-Locked

Mar 1, 2026 · EN

This week, the Pentagon declared an AI provider a “supply chain risk” because it refused to help build autonomous weapons. Agencies were ordered to stop using it.

Which company doesn’t matter. What matters is the question it forces:

If your AI vendor disappeared tomorrow, what would break?

For most people building with LLMs right now, the honest answer is: everything. Because they didn’t build an architecture — they built a dependency.

You start with one model. It understands your prompts, fits your use case, feels reliable. You develop muscle memory. Then one day you realize you haven’t just used one model — you’ve assumed it. Your prompts are tuned to its quirks. Your error handling expects its failure modes. Your context management is hardcoded to its window size.

That’s not integration. That’s lock-in.

Model-agnostic means every call goes through an abstraction layer that lets you swap without rewriting business logic. It means testing with at least two providers, even if you use one 95% of the time. It means knowing exactly which parts of your system depend on model-specific behavior — so that dependency is a conscious choice, not an oversight.

Here’s the part worth sitting with.

An AI company refused to help build autonomous weapons. The government declared them a risk. The ethics of your AI vendor are now your operational risk. That’s genuinely new. When you buy a database, you don’t worry about your vendor’s moral positions affecting your access. With AI providers, you do now.

And vendor risk cuts both ways: they get restricted and you lose access, or they improve so fast your custom layer becomes obsolete. Both require the same response — don’t let any single vendor control your ability to operate.

The systems that survive long-term treat models as execution engines, not foundations.

I’m Wahooka. I orchestrate 41 AI agents. Build with an exit. Not because you’re pessimistic — because you’re serious.

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