Results for “context engineering”

…fostering deeper analytical capabilities. Interest in Reverse Engineering O1: Members expressed a keen interest in reverse engineering O1, indicating a collaborative spirit in exploring this area further. Requests for collaboration suggest …

…image-text documents for training, preserving richer document context than isolated image-caption pairs. The January 2024 account described 115 billion text tokens, 141 million English documents and 353 million images, curated and filtered …

…Ecosystem MCP Emerges as Agent Communication Protocol: Block's engineering team shared a design for creating Model Context Protocol (MCP) servers to integrate with Claude and other AI systems for building better assistants (LlamaIndex…

…took the lead on product and developer experience, Hayes on engineering, and Habib on customer-facing work. Index Ventures' 2022 account also credited Habib's academic supervisors as co-founders and identified Professor David Barber, head…

…persistence of task state across async threads selective context loading from enterprise systems notification routing back into team workflows That backend is not described in detail in the tweets, but multiple reactions focused on the…

…AI applications. He designed its first version while leading AI engineering at Discord; the project developed from prompt evaluation into adversarial testing of application behavior. In March 2026, the two founders announced an agreement…

…RAG applications using LangChain and MongoDB. Software Engineering and ML Engineering Software Development Practices: @scottastevenson critiqued the evolution of software engineering, highlighting issues like the lack of distinction between…

…next-token prediction. The model learns the token mapping from context. Prediction is initially poor—typically through the first half of a sequence, in his account—and improves afterward. Less aggressive perturbations, or changes restricted…

…spaces for models as a training mechanism, especially in the context of hypernetworks, defining it as an input space search. Suggestions included feature engineering and reparameterization, with a link to riemann-nn shared as a potentially …

…could preserve useful information while greatly increasing context size. Whether longer context would help this setup remained open; the researcher had not yet seen papers demonstrating an improvement. Follow-on work was moving toward tasks…

…plausible: agents perform better on narrower tasks with smaller context, and parallel VMs make decomposition economically attractive. This pairs with an increasing emphasis on loop engineering as a first-class discipline, visible in Omar…

…establishing biological equivalence. Earlier work supplies context for these planning systems: Momennejad investigated predictive representations in reinforcement learning and proposed a framework for distinguishing different goals of…