Agentic AI: The Next Evolution of Automation
summary
An AI agent is an LLM plus explicit tools, short‑ and long‑term memory, and a planning loop using REACT prompting; standards like MCP and Agent2Agent enable tool access and agent‑to‑agent orchestration. Live examples: SEO/marketing agents scrape pages, generate blog posts, create ads and run AB tests end‑to‑end; sales agents use 11Labs voices and CRM data to call customers with natural pauses; DevOps agents triage incidents and sometimes fix them. Beware context‑window bloat, invest in evals, guardrails, and expect high latency.
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chapters (7)
- 0:00Introduction to Agentic AI
- 10:19Core components of AI agents
- 16:21Memory and planning in agents
- 20:37Real-world agent use cases
- 28:24Building and deploying agents
- 34:31Security and operational tips
- 38:43Q&A and closing remarks
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