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
Longer autonomy, standardized tools, agent ecosystems — where enterprise Claude agents are heading and the concrete moves that prepare your team now.
Task success, eval scores, cost per outcome, escalation rate — the signals that prove a Claude agent works and the dashboards that catch regressions.
A realistic walkthrough of building a Claude triage agent — from a messy business problem to a shipped, monitored outcome, with the real decisions.
The real failure scenarios for Claude agents, how to bound blast radius, and the guardrail and kill-switch patterns that contain the damage.
The hiring and skills shift behind shipping Claude agents — what AI engineers must learn, what transfers, and how teams reorganize to deliver.
How to scale agentic AI across an organization in 2026 — shared skills, a platform layer, and the patterns that prevent agent sprawl and chaos.
An honest 2026 decision guide for Claude agents — where agentic AI shines, where it backfires, and the cheaper alternatives leaders keep ignoring.
The governance, trust, and safety controls leadership needs before scaling Claude agents in 2026 — permissions, evals, audit trails, and human oversight.
Change management for agentic AI in 2026 — the habits, norms, and trust-building that make Claude agents stick instead of stalling after the pilot.
