Carnegie Mellon University PhD student Michael Isaac, during an internship at cmpnd, implemented Flex, a new DSPy module that lets models rewrite program code, not just instructions, to optimize perfo…
A developer found that DSPy's compiled programs re-send up to 20 few-shot demonstrations on every inference call, adding significant token overhead that is invisible in the source code. The default op…
Demand for engineers skilled in LLM agent development has surged 300% year-over-year, making it the highest-leverage skill for 2026, according to LinkedIn workforce data from late 2024. Proficiency wi…
A developer's analysis of production AI agent failures reveals that self-correction prompts often degrade performance, causing errors such as hallucinated dependencies, infinite validation loops, and …
DSPy 3.3.0's MIPROv2 optimizer can automatically compile a support-ticket classifier prompt that beats a hand-tuned baseline, according to a tutorial by Mariana Souza. The approach uses a DSPy signatu…
A developer warns that the software supply chain for AI coding agents is vulnerable, citing a backdoored LiteLLM package on PyPI that was downloaded 47,000 times in three hours. The post details three…
Superlinked released SIE, an open-source inference engine that serves 100+ models for agent tasks through one OpenAI-compatible API, replacing separate model servers per task. The engine supports sear…
DSPy creator Omar Khattab's toolkit and its GEPA optimizer are the targets of a polemic by an unnamed developer who argues that treating LLM workflows as modular programs is 'backwards, rigid, and the…
DSPy shipped dspy.RLM, a Recursive Language Model module in version 3.1.2, to address context rot — the tendency of models to lose performance on long inputs before reaching their advertised context w…
A developer contributed an open-source feature to DSPy, adding a Together AI fine-tuning provider. The provider allows users to fine-tune models like Llama directly within the DSPy framework, eliminat…
A new DSPy Dashboard monitors performance, cost, and reliability of DSPy programs using OpenTelemetry trace data, tracking span kinds CHAIN, LLM, and TOOL across model usage, latency percentiles, modu…
SigNoz announced support for monitoring DSPy programs via OpenTelemetry, enabling real-time visibility into DSPy module calls and language model requests. The integration uses the OpenInference DSPy i…
AMD has released the Primus Tuning Agent, a tool that automatically searches for optimal training configurations for large language models by using a projection engine as a fast scoring oracle. In a c…
Simon Willison used DSPy to evaluate and improve the system prompts for Datasette Agent, an AI tool that executes read-only SQL queries. The research identified that including column names in schema l…
A new benchmark, dspy-security-bench, reveals that DSPy prompt optimization degrades adversarial robustness against harder prompt-injection attacks. Testing with AgentDojo's attack suite, optimizers l…
A developer built dspyer, an open-source tool that wraps LLM calls in Pydantic schemas to automatically correct malformed JSON, missing fields, or fabricated citations. The tool compiles to a standard…
AxLLM launches Ax, a multi-language LLM framework that uses typed signatures to replace prompt glue with automated prompt generation, parsing, validation, and retry loops. Built on research from DSPy,…
Researchers introduced GEPA, a prompt optimizer that uses an LLM to read execution traces and rewrite prompts, outperforming reinforcement learning by leveraging natural language reasoning about failu…
Decagon deployed self-evolving AI agents that automatically improve their own prompts without human intervention, using a feedback loop that tests and promotes winning versions. The team found that th…
A new free eBook titled 'Building Pragmatic AI Agents That Use Tools and APIs' provides a practical guide to constructing production-grade AI agents, covering five frameworks including DSPy and OpenAI…