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
Deep dive into NVIDIA OpenShell's policy-based security model for autonomous AI agents — network guardrails, filesystem isolation, privacy controls, and production deployment patterns.
Complete tutorial on the OpenAI Agents SDK covering agent creation, tool definitions, handoff patterns between specialist agents, and input/output guardrails for safe AI systems.
Deep dive into Salesforce Agentforce architecture, Atlas reasoning engine, partner ecosystem, and how CRM-native agents compare to custom-built agentic systems.
Learn how to scale agentic AI systems to handle 10,000 concurrent users with connection pooling, async processing, horizontal scaling, and k6 load testing strategies.
Master advanced RAG patterns for AI agents including hybrid vector-keyword search, cross-encoder re-ranking, and agentic retrieval where agents autonomously decide retrieval strategy.
Deep analysis of the $9 billion agentic AI market in 2026 covering CAGR projections at 45.5%, key players, market segments, geographic distribution, and growth drivers.
Set up production observability for AI agents with distributed tracing across agent calls, structured logging, metrics dashboards, and alert patterns using OpenTelemetry.
Discover how AI agents handle inbound calls and chats at $0.40/interaction vs $7-12 human cost. Architecture patterns, Gartner's $80B savings forecast, and production deployment guide.
Explore how development tools are becoming fully agentic with Claude Code CLI, Codex, Cursor, and Windsurf shifting from autocomplete to autonomous multi-step coding workflows.
