Kujenga miundombinu ya programu zenye nguvu za AI kuhusisha kuchagua mbinu sahihi ya AI, kushughulikia sifa za kipekee za AI (kutokuwa na uamuzi sawa, gharama, chelekezo, hitilafu), na kujenga kwa kutegemea utegemezi karibu na AI ambayo si kamili kwa asili. Inachanganya uhandisi wa programu na mawazo mahususi kwa AI.
Kuchagua mbinu ya AI
→ PROMPTING (LLM APIs) → for most LLM tasks (simplest); good prompts go far
→ RAG → to ground answers in your own/current DATA (reduce hallucination)
→ FINE-TUNING → for specific behavior/style prompting can't achieve
→ TRADITIONAL ML → for structured prediction/classification with data
→ PRE-BUILT services → vision, speech, etc. (don't reinvent)
→ match the approach to the problem (often: prompting + RAG for LLM apps)
