AI-Driven Marketer podcast
Browse the complete archive of practical conversations and experiments for marketers building with AI.
Episode archive
Page 14 of 18
CustomGPTs and niche-trained language models can extend a marketer's expertise, but neither replaces the judgment required to diagnose problems, ask questions, and make decisions.
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Craig Nelson and I discuss a practical roadmap for AI-driven sales teams, from call preparation and follow-up to proving time savings and institutionalizing repeatable workflows.
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I tested Grok2's access to live X conversations for market research, from finding B2B trends and complaints to shaping content ideas and checking sentiment in a faster research loop.
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AI gets more reliable when you stop asking it to remember everything and instead load the right context, sources, instructions, and examples into its working memory.
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SearchGPT signals a shift from ranking for clicks to being selected inside answers. Test the search behavior now and publish evidence AI systems and humans can trust.
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A practical look at combining a CRM journey builder with OpenAI to turn podcast source material into consistent newsletter drafts and automated campaigns that can be reviewed and improved.
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Audra Carpenter and I discuss connecting AI to marketing automation, using existing podcast content, clearer prompts, and review checkpoints to create repeatable workflows.
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Noz Urbina and I unpack generative AI's creative power, hallucinations, context, knowledge graphs, and the process that helps marketers use new tools responsibly.
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Dan explains the move from solo consulting and podcasting toward an AI agency built around practical content systems, client bottlenecks, and original points of view.
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Lee-Ann Scott shares a podcast-in-a-box workflow that uses custom GPTs, automated outreach, AI clipping, and fewer handoffs while protecting time for strategic thinking.
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The future of AI marketing is uncertain, but the next step is clear: master transferable fundamentals, test real workflows, and learn early enough to lead the people around you.
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An AI strategy connects a business objective to a measured workflow, a responsible owner, and adoption support so experiments can become useful operating systems.
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