TLDR Tech / Data
No Dumb Questions: What is the AI bottleneck? How does context engineering fix it?
The bottleneck slowing AI adoption is context engineering: LLMs can draft a reply or write code but require humans to manually gather threads, connect to internal tools, configure permissions, and validate outputs, making setup cost exceed time saved for infrequent tasks. The gap widens for proprietary work because general-purpose LLMs were not trained on a company's internal processes and procedures.
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