Agentic Context Engineering (ACE) improves LLM systems by evolving their context instead of their weights, using three agents—Generator, Reflector, and Curator—to maintain a playbook through small, de…
TextGrad, a framework for automatic 'differentiation' via text feedback from large language models, was published in Nature on 19th March 2025. The framework, which implements backpropagation through …
Via v0.4.0 introduces a CLI prompt engine that learns from a developer's codebase history, improving prompts over time by storing successful patterns and past failures. Inspired by the MemAPO research…
Researchers introduced SPEAR (Sandboxed Prompt Engineer with Active Roll-back), a code-augmented agentic optimizer that autonomously rewrites prompts using a Python sandbox for structural error analys…