Agentic FinOps: Using Specs to Control the Cost of AI AutonomyReducing token waste by providing agents with a deterministic roadmap.
Lower your AI costs with spec-driven development. Discover how structured specifications prevent expensive recursive loops and optimize token usage in 2026.
CQRS in AI systems: why separating reads from writes is the mental model prompt engineers have been missingHow a battle-tested software architecture pattern maps surprisingly cleanly onto inference pipelines, prompt design, and AI system boundaries
Explore how CQRS analogies apply to AI engineering — separating retrieval from mutation logic to build more reliable, observable AI systems.
Deterministic AI vs Autonomous Agents: Choosing the Right Level of IntelligenceWhy not every problem needs an AI agent that thinks for itself
Not all AI systems need autonomy. Learn the practical differences between deterministic AI workflows and non-deterministic AI agents, with real-world examples to help you choose the right approach.
Recursive Reasoning: How Meta-Prompting Solves Complex Multi-Step TasksUsing 'Critic' and 'Architect' loops to eliminate hallucination in autonomous agents.
Discover how recursive meta-prompting enables complex reasoning. Learn to implement self-reflection loops that help AI agents verify and refine their own logic.