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KNKartik N V J Kkartiknvjk.hashnode.devOct 6 · 5 min read

Eval the Signature, Not the Program: How I Fixed My DSPy Evaluation

Last month I shipped a DSPy RAG pipeline that looked done. I compiled it with MIPRO, the hold-out numbers were solid, CI was green. Two days into real traffic the quality complaints started. Retrieval

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SPSandeep Pawarfabric.guruSep 25 · 13 min read

Introducing Fabric-RLM

For the past 5 months, I have been working on a side project to build Fabric-RLM, a Python library built for Fabric using Recursive Language Model. I am super excited to finally share it and show how

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CMChaeyeon Mia Leemiainflorence.hashnode.devAug 4 · 10 min read

GEPA: How Prompt Evolution Beats Reinforcement Learning Without Touching Model Weights

You've spent 40 GPU-hours fine-tuning a model with GRPO. It works great — until your downstream pipeline changes, or the base model gets upgraded, and you're back to square one. Meanwhile, your engine

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JKJangwook Kimeffloow.hashnode.devApr 30 · 10 min read

DSPy 3.x: Compile and Optimize LLM Pipelines Automatically

If you've spent hours rewriting the same prompt to squeeze out a few more correct answers, DSPy offers a different deal: describe what your LLM pipeline should do, then let an optimizer figure out the best prompts automatically. DSPy (Declarative Sel...

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XYXiao Yaoblog.appliedaihub.orgApr 3 · 14 min read

LangChain, DSPy, and the Physics of Probability Engineering

A thread on r/PromptEngineering last week opened with a genuinely sharp question: "Is 'probability distribution engineering' just a fancy way of saying 'be more specific'? And isn't that just DSPy run

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TFTheresa Fruhwuerthllmshowto.comJul 24, 2025 · 14 min read

LLM Evaluation: Using DSPy to decompose an LLM Judge

Introduction I have been tinkering with LLMs at work and outside now for quite a while and one of the most pressing issues compared to traditional machine learning is the unsolved problem of how to evaluate them. Evaluating LLM outputs is exponential...

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PTPraghadeesh T K Sblog.praghadeesh.comJul 13, 2025 · 4 min read

Bored of Prompt Engineering? Try DSPy

With the advent of LLMs in the recent few years, we stumbled upon something called Prompt Engineering - let’s speak a few words about it to set the context right and then let’s venture into DSPy What is Prompt Engineering? Prompt Engineering is the ...

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BNBosire Nyakundibuildwithbos.hashnode.devJul 2, 2025 · 10 min read

Systematic Prompting in the New Era of Software

💡 This blog post draws inspiration from Andrej Karpathy's insightful talk, "Software is Changing" which I highly recommend watching! It offers a fascinating perspective that will broaden your understanding of the topic. Those who watched Andrej's ...

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SASimeon Adebolacircuitmaverick.hashnode.devMar 27, 2025 · 5 min read

How to Build Efficient RAG Pipelines Using DSPy

What is DSPy DSPy(Declarative Self-Improving Language Programs) is a framework for building AI applications. Unlike its counterparts i.e. Langchain, Llamaindex, it emphasizes programming the LLM model over prompt engineering. In this tutorial, you wi...

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GGitHubOpenSourcegithub-open-source.hashnode.devMar 12, 2025 · 3 min read

Revolutionizing LLM Development: LangWatch - Your All-in-One LLM Ops Platform

📝 Quick Summary: LangWatch is an LLM Ops platform designed to monitor, experiment with, and optimize LLM pipelines. It offers features such as a drag-and-drop optimization studio, quality assurance tools with evaluators and dataset management, and m...

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#dspy

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Trending tags this week

Eval the Signature, Not the Program: How I Fixed My DSPy Evaluation

Introducing Fabric-RLM

GEPA: How Prompt Evolution Beats Reinforcement Learning Without Touching Model Weights

DSPy 3.x: Compile and Optimize LLM Pipelines Automatically

LangChain, DSPy, and the Physics of Probability Engineering

LLM Evaluation: Using DSPy to decompose an LLM Judge

Bored of Prompt Engineering? Try DSPy

Systematic Prompting in the New Era of Software

How to Build Efficient RAG Pipelines Using DSPy

Revolutionizing LLM Development: LangWatch - Your All-in-One LLM Ops Platform