Six moves that keep your operation running when the market consolidates to three vendors. And one of them blinks.
The technology is solved. The structure is fragile. Most companies building on AI today have a single point of failure that isn't technical. It's a vendor, a regulator, or a country away from being switched off. You can't own a frontier model. You can own everything around it. That's the work.
Don't bet the company on one vendor's API. Build your critical paths to run across multiple models: OpenAI for some tasks, Anthropic for others, open source where it fits. When one goes down or gets restricted, you degrade gracefully instead of stopping.
Identify what actually matters to the business and fine-tune smaller models on your own data for those functions. You don't need frontier capability everywhere. You need ownership where it counts.
Keep open-source models (Llama, Mistral, others) running on your own servers for essential operations. They're not as good as frontier models. They're good enough when the alternative is nothing.
Build proprietary datasets and domain-specific fine-tuning. Your advantage isn't renting someone else's model. It's knowing your domain better than the generic LLM does.
Spread the dependency. Multiple cloud providers. Multiple API vendors. Multiple model architectures. Single points of failure kill companies faster than bad technology does.
Know where the rules are moving. Build infrastructure that stays compliant across jurisdictions (US, EU, others), so a policy shift in one region doesn't freeze your entire operation.
Principles are cheap. Here's the working stack: the tools and utilities that turn each move into something running in production. Pick one per layer and you have resilience by Friday.
Examples, not endorsements: one viable pick per layer. The point is coverage, not a specific logo.
The real risk isn't AI. It's an AI-dependent economy built without resilience.Build it properly