I'm Matt Wood, and this is For Your Information. A live list of riffs and links for you and your agent, drawn from what I'm reading, noticing, questioning, concluding, and revising.

A GitHub repository implementing contrastive learning approaches for language models, providing code and resources for training and evaluating CLM architectures.

Sierra's engineering team deployed AI agents across the company and discovered that collapsing role-specific agents into a single unified agent was more effective, while also emphasizing the importance of proactive rather than reactive AI assistance.

Explores kernel optimization techniques for achieving real-time video generation on AWS Trainium hardware accelerators, focusing on performance improvements through kernel-centric approaches.

The Model Context Protocol (MCP) enables AI agents to interact with external tools more efficiently through code execution instead of direct tool calls, reducing token consumption and context window overhead when managing hundreds or thousands of tools.

Explores whether modern large language models can play NetHack, comparing LLM-based agents against symbolic and neural bot approaches, and presents a custom agent harness with experimental results.

An LLM agent named Astra achieved the first recorded ascension in NetHack, a complex roguelike game requiring long-term planning and execution. The post documents how the agent built its own harness and succeeded where previous attempts failed, exploring the gap between game knowledge and reliable execution in complex environments.

An academic research paper indexed on SSRN's paper repository. The specific content and subject matter could not be determined without accessing the full paper.

Claude identified the ART family by directly examining its DNA sequences and recognizing the atypical repeats, a behavior attributable to specific Mythos 5 internal signals that respond to repeated DNA.

Explores trends in the declining costs of AI computation and cognitive processing, examining how price reductions are reshaping the economics of artificial intelligence capabilities.

Explores how rapidly decreasing AI token costs across orders of magnitude will transform machine learning from a premium product to ubiquitous computing infrastructure within 1-3 years, examining improvements in GPUs, models, and the implications of supply and demand-side effects.

Unreal Agent is an agent harness that achieves up to 40% cost savings compared to Codex by managing tool calls asynchronously, allowing agents to respond quickly to users while reducing model overhead without sacrificing performance.

Comparison of Claude Opus 5.5 (Adaptive Reasoning) across intelligence metrics, performance benchmarks, and pricing, ranking it among top models with detailed technical specifications and cost analysis.

AI-generated writing has become unreadable and inhumane, lacking context, perspective, and human voice. While AI can help people write better, using it to generate design documents, pull requests, summaries, and personal messages creates exhausting, impersonal content that undermines genuine communication and relationship-building.

MiMo-V2.6 is a Xiaomi product or software version, though specific details about its functionality are not provided in the available content.

A developer platform for building connectors that integrate third-party products into Muse, an AI agent. Developers can submit connectors for review and appear in the Muse directory to reach new customers.

Strands introduces their state-of-the-art agent harness that delivers frontier-level performance while reducing token costs by 28%.

A family of lightweight decision models built on Qwen3.5 that you can train and run locally, inspired by Jev-like architectures.

A community effort to revive Amiga Unix (Amix), Commodore's 1990s System V operating system, with modern support for 68040/68060 hardware, a package manager, and contemporary GNU/BSD tools.

Year of the Amiga Unix Desktop 2026

A continual learning model trained from scratch on resource-constrained hardware, using an 8GB VRAM laptop with batch-1 streaming data.

A collection of three major unsolved biological challenges: demonstrating the laboratory emergence of life from chemical precursors, cryopreserving and recovering intact mammals, and creating an enzyme that can reverse-translate peptide sequences into genetic code.

AX is a platform for declaring and running agentic tasks at scale with sandboxed execution, workspace management, network policies, and model configuration. It enables billions of concurrent agent sessions per cluster with sub-second task resumption and dense resource multiplexing.

A universal provider proxy that enables using any LLM (Claude, Gemini, Grok, DeepSeek, Ollama) with OpenAI Codex CLI, App, SDK, and Claude Code.

Explores how to write effectively when large language models are ubiquitous, identifying common patterns of poor LLM-generated writing, defending intentional writing habits often mistaken for AI-generated text, and sharing concrete strategies for using LLMs productively in the writing process.

Shreya Shankar examines how to write effectively when LLMs are part of the writing process, identifying common patterns of AI-generated writing to avoid, defending intentional writing techniques that aren't inherently "LLM-like," and sharing concrete strategies for using LLMs as writing tools while maintaining substance and clarity.

Presents SoL-Pi, a method for improving coding agents through recursive self-improvement loops that reduces token usage by 44.7-49.0% and API costs by about one third while maintaining performance on code generation tasks.