/blog · playbook notes

Notes from the workshop floor.

Slow, careful posts on what we've learned shipping AI-native apps.

From Frontier Models to Reliable AI Systems: The New Priorities in Agents, Security, and Inference

The latest AI advances are shifting attention away from isolated chatbot demos and toward complete systems. Frontier models still matter, but practical progress increasingly depends on coding agents, memory, evaluation, privacy, security controls, and affordable inference hardware.

Sep 2, 2026Read

5 min

From Local Models to Computer-Using Agents: The New AI Systems Stack

AI is moving beyond chat interfaces. The most important developments now concern systems that can operate software, use websites, run locally, interpret visual context, and connect model capabilities to enterprise workflows.

Sep 1, 2026Read

5 min

From Multiplayer Coding Agents to Local AI Infrastructure

AI is moving beyond chat and autocomplete into persistent, tool-using systems that can coordinate work, operate software, and run closer to the user. The most important developments are not only larger models. They include shared coding environments, structured browser access, governed execution, local inference, regional infrastructure, and domain-specific AI.

Aug 31, 2026Read

5 min

Building Reliable AI Agents: Evaluation, Context, Security, and Affordable Infrastructure

AI development is entering a more practical phase. The difficult questions are no longer limited to model size or benchmark scores. Teams now need to understand whether agents can complete real workflows, how much context they require, what tools they are allowed to use, and whether developers can run the necessary infrastructure affordably.

Aug 30, 2026Read

5 min

From MCP and Agent Swarms to Local Models: The New Enterprise AI Stack

AI is moving beyond standalone chat interfaces and into the systems where software is planned, built, tested, deployed, and operated. The latest developments point toward a more connected and competitive stack: Model Context Protocol (MCP) integrations, autonomous coding agents, portable model runtimes, enterprise-grade concurrency, and infrastructure designed for sustained AI workloads.

Aug 29, 2026Read

6 min

From Open Models to Actionable Agents: The Infrastructure Shaping Enterprise AI

AI development is shifting from isolated chat interfaces toward complete systems. The important advances are no longer limited to larger models. Developers also need long-context inference, tool connectivity, retrieval, browsing, low-latency voice, hardware portability, and strong controls around sensitive data.

Aug 28, 2026Read

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