The 2025 AI Engineering Report
summary
Survey of 500 AI practitioners finds broad use of LLMs: 94% apply them to two or more use cases and 82% to three or more, with code generation and content assistants leading. 70% use RAG and fine-tuning is far more common than expected, with 40% of fine-tuners citing Laura or Qura (parameter‑efficient methods). Models update monthly for over 50% (17% weekly); 70% update prompts monthly while 31% have no prompt management. 65% use vector databases; evaluation ranks as the top pain point and less than 20% report agents working well.
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