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UID:pretalx-2025-S3TDZB@cfp.in.pycon.org
DTSTART;TZID=IST:20250913T105000
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DESCRIPTION:Prompt engineering has become a core skill in working with LLMs
 \, yet writing effective prompts is tedious\, inconsistent\, and often req
 uires multiple attempts. Most prompt development today is done manually\, 
 relying on trial and error\, which doesn’t scale well\, especially in pr
 oduction environments where consistency is crucial. This talk presents a p
 ractical approach to optimizing prompts by treating them as evolving tools
 . The process includes refining prompts based on feedback and ensuring the
  outputs meet structure and quality requirements\, with the help of Pydant
 ic to validate and enforce output standards. This helps create stable\, pr
 oduction-ready prompts through continuous and iterative improvement.
DTSTAMP:20260317T115350Z
LOCATION:Track 1
SUMMARY:Mastering Prompts with Feedback and Pydantic - Mahima Arora\, Aarti
  Jha
URL:https://cfp.in.pycon.org/2025/talk/S3TDZB/
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