or, of GPUs, LPUs, and Goal Displacement
Context Engineering for AI Agents: Lessons from Building Manus
This post shares the local optima Manus arrived at through our own "SGD". If you're building your own AI agent, we hope these principles help you converge faster.
LukeW | Context Management UI in AI Products
They say context is king and that's certainly true in AI products where the content, tools, and instructions applications provide to AI models shape their behav...
Context Engineering
Context engineering strategies for AI agents: write, select, compress, and isolate context to optimize performance and manage long-running tasks.
Understanding TPUs vs GPUs in AI: A Comprehensive Guide
Explore the differences between Graphics Processing Units (GPUs) and Tensor Processing Units (TPUs) in AI.
Context Engineering | Meetup
"Context engineering is the delicate art and science of filling the context window with just the right information for the next step" - Andrej KarpathyLearn about tools, frameworks, and code that is in service of context engineering from practitioners in this space.Dive into the set of strategies fo
Context Rot: How Increasing Input Tokens Impacts LLM Performance
Large Language Models (LLMs) are typically presumed to process context uniformly—that is, the model should handle the 10,000th token just as reliably as the 100th. However, in practice, this assumption does not hold. We observe that model performance varies significantly as input length changes, even on simple tasks. In this report, we evaluate 18 LLMs, including the state-of-the-art GPT-4.1, Claude 4, Gemini 2.5, and Qwen3 models. Our results reveal that models do not use their context uniformly; instead, their performance grows increasingly unreliable as input length grows.
hypercontext — spatial context awareness
See what your AI knows. Session state as a spatial map.
The Architect of Constraints: Why Context Engineering Is the Human Skill That Matters
“If I had an hour to solve a problem, I’d spend 55 minutes defining the problem and 5 minutes solving it.” — Albert Einstein
Context Constitution
Today we are releasing the Context Constitution: a set of principles governing how AI agents manage context to learn from experience.
Modern GPU Programming For MLSys — Modern GPU Programming For MLSys
Machine learning systems sit at the heart of modern AI workloads. In these systems, performance often comes down to the quality of a small number of GPU kernels. Attention kernels, LLM prefill and decode kernels, low-precision block-scaled GEMMs, fused MoE layers, and other large fused kernels all directly shape end-to-end speed in both training and serving.
Modern GPU Programming For MLSys — Modern GPU Programming For MLSys
Machine learning systems sit at the heart of modern AI workloads. In these systems, performance often comes down to the quality of a small number of GPU kernels. Attention kernels, LLM prefill and decode kernels, low-precision block-scaled GEMMs, fused MoE layers, and other large fused kernels all directly shape end-to-end speed in both training and serving.
Model Leaderboard | Letta
Context-Bench measures an agent's ability to perform context engineering with: