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As model performance converges, prompt optimization is the new competitive edge. In this session, we revisit DSPy to cover the state of prompt...
We present Artemis, a no-code evolutionary optimization platform that jointly optimizes agent configurations through semantically-aware genetic...
DSPy’s built-in usage tracking gives you aggregate token counts after a program runs. That’s fine for simple pipelines. But when you’re debugging...
Quick Primer on GEPA# GEPA (Genetic-Pareto) is a reflective optimizer. It evolves prompts by having an LLM critique failures and propose...
New technical example: @cocoindex_io plau @DSPyOSS for structured extraction from intake forms. This demo shows how to build a fully-typed,...
Compounding Engineering is a philosophy where every task you complete makes the next one easier. This isn't just about reusing code—it's about...
In this work, we introduce agent symbolic learning, a systematic framework that enables language agents to optimize themselves on their own in a...
Comparing DSPy, GEPA-AI, and Synth AI on the LangProBe benchmark suite
Building production AI agents with DSPy is straightforward—until you need multiple specialized submodules, each with its own tools and behaviors. At...
Building reliable LLM systems isn’t about chasing a “magic prompt” — it’s about a disciplined, iterative development cycle. DSPy treats LLM pipelines...
Building a research agent with CodeAct where the LLM generates Ruby code on the fly.
In complex agent systems, you might have chained multiple prompts together. You can provide all these prompts together for GEPA to consider and...
This paper reformulates prompt engineering as a classical state-space search, treating prompts as "states" and edits as "transitions." By using...
A tool that serves DSPy programs as HTTP APIs with Docker config, OpenAPI specs, MCP support, and more.
DSPy Pune meetup, December 13, 2025, 4 p.m. and DSPy Bengaluru - Quarterly Meetup, December 20, 2025, 10 a.m.
Show a video on integrated output with claude desktop.
Codex-Agent is a module that wraps the OpenAI Codex SDK in DSPy signatures for type-safe, stateful coding agents. Each instance maintains its own...
Koantek’s AscendAI Agent Factory redefines how enterprises build and deploy AI agents on Databricks. Powered by Agent Bricks and DSPy’s “programming...
DSPy is a research paradigm. We're not trying to building whatever reaches the largest userbase. We're trying to realize a very specific vision and...
The paper introduces Agent-Omni, a framework that overcomes current limitations of multimodal large language models (MLLMs), which typically support...