Search Results: ContextEngineering

MemoV introduces a revolutionary memory layer for AI coding agents, capturing every prompt, plan, and code change in a separate timeline beyond Git. This open-source framework enables granular context tracing, 5x faster debugging, and cleaner version control workflows for developers.

Introducing Prompt Context, a specialized integrated development environment for context engineering that enables developers to build, version, and link prompt logic as reusable cards. This tool addresses the chaos of unstructured inputs by converting them into structured, executable context for AI agents, applications, and collaborative teams, potentially accelerating AI development cycles.

Today's AI agents possess remarkable reasoning skills but suffer from crippling amnesia, forgetting interactions after each session. We dissect the critical challenge of engineering memory into LLMs—exploring short-term vs. long-term systems, explicit vs. update strategies, and the hard problems of relevance and bloat. Discover why solving memory isn't just about storage, but building a smarter cognitive architecture.

Web automation agents consistently fail in production due to context overload and memory accumulation, creating a painful demo-to-production gap. Simplex reveals how borrowing Anthropic's multi-agent approach slashes failure rates by compressing context and scoping tasks, enabling 60+ minute workflows.