Your Guide to the AI Revolution

Karpathy's 2016 CS231n lessons still shape AI strategy: representation learning, end-to-end systems, and data-centric iteration.

Apple's M5 Pro and Max chips are tempting, but upgrading hardware before rebuilding your agent platform's control plane just accelerates a brittle system. Here's why we're choosing kernel-first.

Learn how to set up OpenClaw Gmail automation with AgentSkills, Google authorization, and safer permissions for reading, drafting, and sending email.

Your GitHub runner holds the keys to your cloud accounts. Learn what a runner compromise means, why vibe coders are especially vulnerable, and how to lock down your deployment pipeline today.

Learn how MCP Tasks decouple long-running agent work from blocking tool calls with polling, subscriptions, state management, and production safeguards.

Simon Willison's datasette-llm releases introduce purpose-driven model selection — a design pattern that gives enterprises better cost control, governance, and vendor flexibility.

The M5 may improve local AI inference, but for agent platforms the smarter move is stabilizing the kernel first, then scaling hardware in phases.

OpenClaw v2026.3.24 replaces the old package-hunting workflow with built-in registry search, bundle support for Claude/Cursor/Codex, and modular provider plugins.

Agent-to-agent attacks let one compromised AI tool influence others in your workflow. Learn the risks, warning signs, and practical defenses.

Most AI programs stall because organizations are unprepared, not because models are weak. Here's how CTOs can build team AI literacy, redesign workflows, and create structures that deliver real value.

Sam Altman's AI-as-utility pitch could reshape enterprise AI buying, vendor lock-in, and infrastructure planning. Here's what executives should do now.

Apple's M5 Pro and M5 Max improve local AI throughput, but better silicon only helps agent platforms with dependable scheduling, observability, and control-plane authority already in place.