Wiring MCP Tools into Claude Skills: Auth & Errors
Connect MCP servers to Claude Skills the right way: authentication, tool schemas, structured error handling, and idempotency for safe retries.
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
Connect MCP servers to Claude Skills the right way: authentication, tool schemas, structured error handling, and idempotency for safe retries.
Reusable code-level patterns for Claude Agent Skills: router descriptions, script-offload, reference-doc tiers, and clean context contracts.
A hands-on walkthrough for building, testing, and shipping a Claude Agent Skill — folder layout, SKILL.md, bundled scripts, and debugging triggers.
Inside Claude Agent Skills: progressive disclosure, the metadata index, and how Skills differ from prompts, Projects, MCP, and subagents.
In-Context Learning (ICL): How Modern LLMs Learn Without Retraining
How agentic AI systems monitor customer health scores, predict churn, automate outreach, and drive retention across global SaaS and enterprise organizations.
How agentic AI systems manage data center cooling, power distribution, workload placement, and PUE optimization across global cloud infrastructure in the US, EU, Singapore, and Middle East.
KPMG projects agentic AI will drive $3 trillion in corporate productivity gains. With 44% of finance teams adopting AI agents in 2026, the shift from automation to autonomy is accelerating faster than anyone predicted.
How agentic AI systems automate lab experiments, analyze research data, conduct literature reviews, and generate hypotheses to accelerate discovery in research labs worldwide.