/blog · playbook notes

Notes from the workshop floor.

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

From Prompt Injection to Production: The New Stack for Enterprise AI Agents

AI systems are moving from chat interfaces into tools that can browse applications, access data, manage credentials, write software, and complete multistep tasks. That shift is creating a new engineering priority: building agents that are not only capable, but controllable, observable, and safe to operate.

Oct 23, 2026Read

5 min

From Chat Interfaces to Governed AI Agents

AI software is moving beyond question-and-answer interactions. The emerging pattern is an execution layer that can create applications, call tools, operate inside persistent environments, and coordinate multi-step workflows.

Oct 21, 2026Read

5 min

From Self-Improving Agent Harnesses to Secure Enterprise Automation

AI systems are moving beyond impressive demonstrations into software development, business operations, and production infrastructure. The important shift is not simply that models are becoming more capable. It is that the surrounding systems—tools, workflows, evaluations, security controls, and data environments—are becoming part of the intelligence stack.

Oct 19, 2026Read

5 min

Persistent AI Agents Are Redefining Inference, Software Engineering, and Security

AI is moving from on-demand assistance toward continuous software labor. Persistent agents can monitor systems, write and test code, operate devices, and continue working after a developer disconnects. That shift expands the opportunity for enterprise AI, but it also changes the infrastructure, security, and governance problems that organizations must solve.

Oct 15, 2026Read

5 min

From Multi-Week AI Agents to Production-Ready Developer Platforms

AI is moving beyond short prompt-and-response interactions. The most important shift is toward systems that operate inside real workflows: coding, advertising, 3D production, enterprise search, and cloud deployment. That shift creates a new engineering agenda centered on reliability, evaluation, security, provenance, and runtime efficiency.

Oct 14, 2026Read

5 min

From Coding Agents to Physical AI: The Infrastructure Behind Reliable Automation

AI development is moving beyond isolated model demonstrations. The emerging focus is infrastructure: coordinating multiple agents, validating generated code, running models locally, securing autonomous systems, and applying AI in high-stakes physical environments.

Oct 13, 2026Read

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