Fine-tuning forgets. RAG leaks context. Hypernetworks build the model your agent needs on demand.
AI Summary
Enterprise teams keep watching the same thing happen. An AI agent demos beautifully, goes to production, and stalls: it runs for a short stretch, then needs a human to top up its context and check its output, and the promised efficiency drains into supervision. The agent did the work; you did the watching.
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