Agentic AI, LLM engineering, and the models behind modern automation — multi-agent systems, LLM evaluation and comparisons, RAG, fine-tuning, AI infrastructure, security, and production AI engineering.
From the blog
Whisper Large v3 Turbo on Apple Neural Engine via WhisperKit hits sub-100ms streaming on iPhone 15 Pro. M5 delivers 4× faster AI inference. Build a fully on-device voice agent for iOS.
Webhook-driven AI integration is the workhorse of B2B automation. The 2026 patterns for reliability, retries, and idempotency at scale.
The actor model is a clean primitive for multi-agent LLM systems. What Ray, Akka, and OpenAI Swarm get right (and wrong) in 2026.
Accuracy alone misses what is actually wrong with your agent. The 2026 metrics teams use to evaluate agentic systems before and after deployment.
Production LLM agents in 2026 separate episodic, semantic, and procedural memory. Here is how to design each store and the tradeoffs that matter.
What enterprise multi-agent systems actually look like in 2026, based on deployment patterns across 200 production teams.
Google's A2A protocol shipped in 2025 to let agents from different vendors talk to each other. Here is what it does, where it differs from MCP, and who is adopting.
Agents that write and run code need real isolation. A 2026 comparison of E2B, Daytona, Modal, and Firecracker-based sandboxes for production agentic workloads.
Versioning agent workflows is the unsexy reliability primitive that decides whether your agent survives its second deploy. A 2026 deep dive.
