Stop Tinkering With Strings: A Practical Tour of DSPy and Reflective Prompt Evolution
Why Stanford's DSPy framework treats prompts as compiled artifacts, and how GEPA — the ICLR 2026 Oral — outperforms reinforcement learning with 35x fewer rollouts.
Why Stanford's DSPy framework treats prompts as compiled artifacts, and how GEPA — the ICLR 2026 Oral — outperforms reinforcement learning with 35x fewer rollouts.
Exploring Microsoft Research's Data Formulator, the concept-binding paradigm, and how its AI agents remove the tidy-data tax from visualization authoring.