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
The April 5 to May 5 2026 vertical voice AI cycle reset the buyer playbook for SMB and mid-market. Pricing patterns, integration depth, vendor selection, and the build-vs-buy line.
Version your prompts in git, run a 50-case eval suite on every PR, block merges below threshold, and ship a new agent prompt with confidence — full GitHub Actions tutorial.
AI SDK 5 ships fully typed chat for React, Svelte, Vue, and Angular plus first-class agent loop primitives. Here are the patterns that matter for shipping in 2026.
Neo4j's agent-memory project ships short-term, long-term, and reasoning memory in one graph. Microsoft Agent Framework and LangChain both wire it in. Here is the production pattern.
An agentic-AI perspective on Anthropic Skills system, covering orchestration patterns, tool use, and how agent tooling fits production agent stacks.
A practical engineering deep dive into Claude Sonnet 4.6 migration, covering architecture, tradeoffs, and what production teams need to know about model upgrade.
AgentStack scaffolds CrewAI, LangGraph, and AutoGen projects with a single CLI. The trade-offs of meta-tooling versus framework-native templates for serious teams.
Long-running agents accumulate noisy state. Five consolidation patterns — summarization, salience scoring, decay, dedup, and refactor — and when each one fits.
Prompt injection is still the top open agent security risk in 2026. The five defense patterns that work, and the two that do not — with real attack-and-defend examples.
