/blog · playbook notes

Notes from the workshop floor.

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

From Local Inference to Autonomous Action: The New AI Systems Stack

AI progress is increasingly defined by complete systems rather than model benchmarks alone. The emerging stack combines capable models, fast inference, developer tools, secure tool access, polished interfaces, and reliable behavior in difficult environments.

Aug 19, 2026Read

5 min

From Local Models to Persistent Agents: The New Architecture of AI Development

AI development is moving beyond standalone chatbots and autocomplete. The emerging stack combines local models, persistent agent runtimes, specialized developer tools, private hardware, and stronger security controls.

Aug 18, 2026Read

5 min

From Cursor and Grok to Governed Coding Agents

AI development is moving beyond chat-based assistance. The emerging model is an operating layer for work: systems that interpret requirements, modify repositories, use software tools, monitor context, and act with limited supervision.

Aug 14, 2026Read

6 min

Agentic Development Enters Its Security-and-Infrastructure Phase

AI development is moving beyond standalone chat interfaces. The newest tools combine collaborative coding agents, local execution, structured document processing, lower-cost models, and faster inference hardware. At the same time, these systems introduce new security and reliability requirements.

Aug 13, 2026Read

5 min

From Grok 4.6 to WebMCP: The Infrastructure Behind Autonomous AI

AI development is shifting from chat interfaces and code completion toward systems that can plan, use tools, modify software, and operate for extended periods. Recent model releases and developer platforms point to a common direction: more capable agents, more local execution, and stronger requirements for evaluation and security.

Aug 12, 2026Read

5 min

From Open-Weight Models to Governed Agents: The New AI Deployment Stack

AI is moving beyond chat interfaces into deployable systems: local inference, multimodal creation, autonomous research, infrastructure automation, and developer tooling. The most important progress is not simply that models are becoming more capable. It is that models are being connected to tools, workflows, hardware, and production controls.

Aug 11, 2026Read

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