Explores inference efficiency in AI, focusing on preserving attention by reducing unnecessary reasoning steps and improving tooling design.
Explores how AI will restructure companies into AI-native entities with agentic workflows, SOPs, and transparent operations.
Explores how hypermedia and HATEOAS in REST APIs may become crucial for AI agents, with insights from industry experts on fixing broken web APIs.
Explore building a second brain with LLMs and AI agents, focusing on durable context systems for knowledge work.
Learn how to integrate OpenTelemetry with Microsoft Agent Framework apps for enhanced observability, including key trends, challenges, and code examples.
Daily tech news roundup covering AI, .NET, Windows development, cloud, and DevOps updates.
A tutorial on building a vendor-neutral evaluation harness for AI agents, covering outcome, trajectory, and control checks before production deployment.
Explores the emergent failure mode where multiple autonomous AI agents compete for shared resources, causing system-wide issues.
Explains AgentOps as the new Day-2 operations discipline for managing AI agents in production, covering lifecycle, observability, governance, and incident response.
A tutorial on designing reliable AI agent tools with clear naming, schemas, error handling, and evaluation.
Implementation guide for human review systems in AI agent workflows, focusing on enforcement points and audit trails.
Explains why judging AI coding agents requires knowing the task's value, not just the cost.
A model for matching AI agent autonomy to access, risk, and reversibility in enterprise workflows, addressing the blast-radius problem beyond RBAC.
Explains middleware in Microsoft Agent Framework for capping token usage, covering cost control, security, performance, and custom logic.
Explains why prompt libraries are insufficient for agentic AI and how to translate prompt intent into enforceable execution policies.
Explores the critical security boundaries for AI agents in enterprise environments, defining what actions agents must never be allowed to perform autonomously.
A 101 guide to WebMCP in Chrome, explaining how it enables structured AI-agent interactions with web apps via the Model Context Protocol.
A curated reading list covering AI agents, open source toolkits, cloud management, and developer productivity in 2026.
Analysis of AI-assisted apps flooding the App Store, causing discoverability chaos and record new releases.
Explores Microsoft Agent Framework's integration with OpenTelemetry for monitoring and debugging AI agents.
