GEPA vs Prompt Learning: Benchmarking Different Prompt Optimization Approaches
We introduced Prompt Learning on July 18, 2025 — an approach that builds simple feedback loops for optimizing LLM applications. A week later, DSPy...
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We introduced Prompt Learning on July 18, 2025 — an approach that builds simple feedback loops for optimizing LLM applications. A week later, DSPy...
AI engineer and educator Mike Taylor explains DSPy in a clear, approachable style, showing how its modular structure, portable programs, and built-in...
By Chris Potts (Stanford Professor ) Event: Bay Area DSPy Meetup (Nov 18, 2025) ... We wouldn't dream of manually setting the weights of a neural...
How Danny used DSPy to give AI taste: 00:47:52
With this update, it has now fully evolved into a harness that seamlessly plugs into existing multi turn Agent environments. ( @aisdk based agents...
ACE (Agentic Context Engineering) is a framework for improving LLM applications by treating context as an evolving playbook, refined through...
DSPy Signature to break multi-part questions into atomic, self-contained sub-queries, plus classifies them. Code Snippet.
Agents are becoming more capable but slower: while simple chatbots respond in about two seconds, agents that perform tasks like web search, database...
Announcing DSCloj! A declarative way to do prompt engineering in Clojure. It is inspired by DSPy library in Python. In it’s current shape API looks...
Lee Butterman’s recent experiment, "DSPy on a Pi," demonstrates that sophisticated prompt optimization is achievable on low-cost edge hardware like a...
The open LLM Ops platform - Traces, Analytics, Evaluations, Datasets and Prompt Optimization ✨ | Language: TypeScript | License: Other
DSPy: The framework for programming—not prompting—language models | Language: Python | License: MIT License
This blog post is a technical walkthrough of how we improved the coding agents used in the AI data scientist. With the actual data, and evaluation...
DSPy quick review in Chinese. 隨著模型性能提升, Prompt Engineering 的重要性不如數年前那麼顯著。 今年一個非常受歡迎的項目 DSPy 提出了一個革新性的概念:「Programming—not prompting」,主張讓程式自動生成...
A cool thread yesterday used GPT4 ($50), a 500-word ReAct prompt, and ~400 lines of code to finetune Llama2-7B to get 26% HotPotQA EM. Let's use 30...
lru_cache cache decorator applied to ensure faster throughput and stopping needless regeneration.
Added ability to use a seperate prompt_model to use to evolve the program.
The pretty much "official" DSPy framework for Typescript | Language: TypeScript | License: Apache License 2.0
Token-Oriented Object Notation keeps your nested Sorbet structs intact—something flat CSV rows simply can’t do when you prompt large language models....