/blog · playbook notes

Notes from the workshop floor.

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

Agentic Workflows and the Strategic Evolution of AI Infrastructure

The landscape of artificial intelligence is shifting from passive assistants to autonomous agents. This transition—the "agentic shift"—is fundamentally changing how software is built, secured, and deployed, while simultaneously redefining the physical infrastructure required to power these systems.

Jun 22, 2026Read

3 min

The Shift to Agentic Systems: From Nvidia AI Factories to GLM 5.2

The artificial intelligence landscape is undergoing a fundamental pivot. The "Chatbot Era"—defined by manual prompting and single-turn interactions—is giving way to the "Agentic Era." This new phase is characterized by autonomous loops where AI systems can plan, build, and judge their own outputs, moving the value proposition from clever prompt engineering to sophisticated orchestration and persistent context.

Jun 21, 2026Read

3 min

From GLM-5.2 Coding Leaps to the Mythos Security Breach: The State of Specialized AI

The landscape of artificial intelligence is shifting rapidly from general-purpose chatbots to specialized agents capable of high-level execution. Recent developments indicate a convergence of advanced coding proficiency, autonomous enterprise utility, and a critical need for localized infrastructure and enhanced security.

Jun 21, 2026Read

3 min

The Shift to Agentic Orchestration: Verifiable Loops and Enterprise Autonomy

The landscape of artificial intelligence is undergoing a fundamental transformation. We have moved beyond the era of static, conversational chatbots toward a paradigm defined by Agentic Orchestration. Developers and enterprise architects are no longer just prompting models; they are engineering persistent "loops" that function as autonomous operators within complex digital environments.

Jun 20, 2026Read

4 min

From Manual Prompting to Markdown Programming: How Autonomous Agents and Local Hardware Are Redefining the Developer Stack

The developer landscape is undergoing a silent but fundamental paradigm shift. The days of raw, conversational prompt engineering are rapidly maturing into the era of Loop Engineering and Markdown Programming. Rather than manually guiding large language models (LLMs) through chat interfaces, modern practitioners are deploying deterministic, automated execution loops. They use version-controlled structured directories to run agents programmatically, bringing predictable, production-grade automati

Jun 20, 2026Read

4 min

Navigating the Great API Bifurcation: From Long-Running Reasoning Models to Local-First AI DevTools

The modern software engineering stack is undergoing a massive architectural shift. As AI moves beyond simple conversational text boxes and integrates deeply into developer environments and autonomous workflows, engineers are confronting a new set of challenges: managing high-compute reasoning times, standardizing memory structures, and keeping cloud costs under control.

Jun 19, 2026Read

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