Explores fine-grained security for AI agents in analytics, covering dynamic access control, identity propagation, and governance at machine speed.
Explains the need for machine-readable metric contracts to standardize business meaning before AI agents access data platforms.
Explores context engineering for AI agents, comparing personal vs. shared context to prevent failures in human and organizational AI use.
Explores semantic layers in data platforms, their role in ensuring metric trustworthiness, and their critical importance for AI agent accuracy.
Deep dive into designing custom AI agent harnesses, covering architecture layers like loops, tools, context, and control for production systems.
How to use AI coding agents like Claude Code and Codex for deterministic data engineering, ensuring reproducibility and trust.
Guide to setting up Microsoft Entra Agent ID for AI agent identity governance, including blueprint creation, authentication, and hardening.
Explores agentic autonomy levels in AI engineering, proposing a two-axis framework of agency and orchestration for multi-agent systems.
Experiment using AI agents to interact with web apps, find defects, and report via GitHub issues and PRs for automated interactive review.
Announcement of the release of 'Build a Reasoning Model (From Scratch)', a book on implementing modern reasoning techniques for AI.
Applying zero trust security principles to AI agents in cloud environments, addressing challenges and compliance requirements.
Analysis of merge queue limitations under AI agent workloads, challenging Hashimoto's critique with a defense of serialization as coordination.
Explores Agentic AI testing in 2026, where AI acts as independent agents to automate and enhance QA processes, and what it means for QA engineers.
Architecture of an open-source World Cup 2026 fan intelligence platform using AI agents, Drasi, AKS, and Azure services.
A curated roundup of tech links covering AI, .NET, web development, DevOps, and industry news for June 26, 2026.
Explores the Dremio Agentic Lakehouse concept: data built for AI agents and platform management automated by agents, with architecture patterns and production considerations.
A practical guide to using Xcode 27 agents for SwiftUI development, from planning to testing a pinned notes feature.
How to improve AI agent feedback loops using custom linters to enforce coding standards automatically.
Explores the concept of AI agent identity, comparing it to human and workload identities, and proposes using workload identity like SPIFFE for runtime verification.
Explores how AI is transforming the software development lifecycle, focusing on agent harnesses and context engineering.
