1/ Ethereum has wallets.Language models have tool calling.What happens when tool-calling models get wallets?You get autonomous agents, digital entities that can reason, transact, and operate on our behalf. And they’re already here. ...

This might be the next deepseek moment. A Chinese company just released another open-source model called Kimmy K2 and it is taking the industry by storm. The reason this graph right here, this is the training loss curve, and people are so surprised by how smooth it is.Typically, you get all of these spikes in here which cause issues that you need to correct. But for Kimmy, it was almost flawless. And the especially cool thing, it is based on a trillion tokens.That is a massive model. So they came up with th ...

Context Engineering Overview - Context engineering is defined as the art and science of filling the context window with the right information at each step of an agent's trajectory [2][4] - The industry categorizes context engineering strategies into writing context, selecting context, compressing context, and isolating context [2][12] - Context engineering is critical for building agents because they typically handle longer contexts [10] Context Writing and Selection - Writing context involves saving information outside the context window, such as using scratch pads for note-taking or memory for retaining information across sessions [13][16][17] - Selecting context means pulling relevant context into the context window, including instructions, facts, and tools [12][19][20] - Retrieval-augmented generation (RAG) is used to augment the knowledge base of LLMs, with code agents being a large-scale application [27] Context Compression and Isolation - Compressing context involves retaining only the most relevant tokens, often through summarization or trimming [12][30] - Isolating context involves splitting up context to help an agent perform a task, with multi-agent systems being a primary example [12][35] - Sandboxing can isolate token-heavy objects from the LLM context window [39] Langraph Support for Context Engineering - Langraph, a low-level orchestration framework, supports context engineering through features like state objects for scratchpads and built-in long-term memory [44][45][48] - Langraph facilitates context selection from state or long-term memory and offers utilities for summarizing and trimming message history [50][53] - Langraph supports context isolation through multi-agent implementations and integration with sandboxes [55][56]