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
Learn how agentic AI coordinates warehouse robots, automates inventory tracking, and optimizes order fulfillment across global logistics operations in the US, China, EU, and Japan.
Build an automated PR review system with Claude that delivers actionable feedback within minutes, catching bugs and security issues before human review.
Practical techniques to reduce LLM inference costs by 40-80 percent through prompt caching, semantic caching, and KV cache optimization in production systems.
How do openai o3 thinking llms work: a technical primer on how reasoning models work — from basic chain-of-thought prompting to OpenAI's o3 and DeepSeek R1. Understanding the inference-time compute revolution.
Assessing LLM Performance: Strategies to Evaluate and Improve Your App.
Explore how agentic AI is revolutionizing predictive maintenance in oil and gas, monitoring equipment health, predicting failures, and optimizing maintenance schedules across global energy operations.
Technical guide to web-browsing AI agents with Claude -- tool-based vs Computer Use, Playwright integration, rate limiting, and common pitfalls to avoid.
Compare CallSphere and Bland.ai for AI voice agents. See features, pricing, compliance, and which platform is better for your business.
Data curation is the single biggest factor in LLM performance. Learn how NeMo Curator uses GPU-accelerated deduplication, synthetic data, and classification at scale.
