LLM Search API: How to Ground AI Agents in Real-Time Web Data
LLM search APIs fix knowledge cutoffs by grounding AI agents in real-time web data. Learn how to add retrieval, citations, and freshness to your agent.
LLM search APIs fix knowledge cutoffs by grounding AI agents in real-time web data. Learn how to add retrieval, citations, and freshness to your agent.
RAG demo best practices that win enterprise deals: learn scoped corpus design, source citations, and retrieval pipeline tips from a real podcast search teardown.
AI agent guardrails that hold under real load need layered defense-in-depth—input filters, output validators, and execution controls working together.
Claude Code hooks enforce hard guardrails your AI agent can't argue around. Learn exit codes, lifecycle events, and shell handlers that keep agentic workflows safe.
Model context protocol demystified: learn the host-client-server architecture, secure your MCP integrations, and connect internal systems to Claude Code.
AI agent PRD templates need eval criteria, guardrails, and escalation paths. Get the section-by-section framework that keeps agents safe and shippable.
Claude Code cost optimization tactics that cut token spend 50–80%: prompt caching, model routing, and context hygiene with real benchmark data.
AI agent evaluation explained for PMs: measure trajectory, tool use, and task completion—not just accuracy—before your agent ships to production.
Prompt engineering is product management. Learn how PMs can own system prompts with versioning, evals, and governance to prevent drift and compliance risk.
Claude Code for product managers means prototyping, data analysis, and shipping internal tools—no engineering tickets, no SQL, no coding skills required.
Claude Code skills let you package reusable workflows into installable units. Learn how they work, when to build one, and how they differ from MCP servers.
Enterprise agentic AI deployment fails without solid infrastructure and governance. Learn the IAM, observability, and oversight foundations that actually matter.