The Commission Vault Museum, a tiny new exhibit located within an old vault at McLaren Lodge, offers a unique glimpse into the history of San Francisco’s Recreation and Park Department. Measuring only 6 by 10 feet, the museum features a collection of archival photos, plaques, and historical artifacts ranging from the 1850s to the present. Visitors can explore the evolution of the city's parks, see rare photographs of historical figures and landmarks, and learn about the department's long-standing role in managing the city's green spaces. Due to its intimate size, tours are by appointment only and often require booking months in advance.
In this tutorial, we build a self-organizing memory system for an agent that goes beyond storing raw conversation history and instead structures interactions into persistent, meaningful knowledge units. We design the system so that reasoning and memory management are clearly separated, allowing a dedicated component to extract, compress, and organize information. At the same time, the main agent focuses on responding to the user. We use structured storage with SQLite, scene-based grouping, and summary consolidation, and we show how an agent can maintain useful context over long horizons without relying on opaque vector-only retrieval.
This blog post explains that Large Language Models (LLMs) don't need to understand the Model Context Protocol (MCP) to utilize tools. MCP standardizes tool calling, simplifying agent development for developers while the LLM simply generates tool call suggestions based on provided definitions. The article details tool calling, MCP's function, and how it relates to context engineering.
6502.sh is a 6502 emulator and debugger written in busybox ash compliant shell script, featuring 32k RAM, 16k ROM, an interactive debugger, and STDIO directed to an ACIA compatible serial port.
SmolVLM is a compact, efficient multimodal model designed for tasks involving text and image inputs, producing text outputs. It is capable of answering questions about images, describing visual content, and functioning as a pure language model without visual inputs. Developed for on-device applications, SmolVLM is lightweight yet performs well in multimodal tasks.
