Agentic AI For Marketers
Notes de l’épisode
We map the shift from chat-based AI to real agentic systems that can run workflows, manage memory, and publish results without constant human babysitting. We break down how to design AI agents like jobs so they stay grounded, cost-controlled, and useful for marketing, SEO, and software work.
• tiering AI use from assistance to automation to full agents with memory and tools
• writing a clear job description with input, process, and output formats
• building an SEO research agent that generates briefs and scores novelty
• grounding agents with state, scripts, and tight context management to cut errors and token waste
• why models ignore guardrails and how system design fixes repeat failures
• plan mode tradeoffs and where to focus review time: planning, code, or tests
• orchestration patterns like dispatchers, specialist sub-agents, and clean bridges between systems
• security and scalability realities for enterprise-ready software built with agents
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