The interesting thing about AI Explored is the exit door. Before Michael Stelzner committed to a new podcast, he decided what would make him close it. Twelve episodes. A target of 1,000 downloads per episode. A small experiment with a stop button. For an audience being told to adopt artificial intelligence immediately, that is a rather useful way to begin.
- A free weekly show about applying AI to marketing and business.
- Expert interviews come with written notes you can use at your desk.
- Start with one troublesome task; keep a human decision in the process.
The experiment with an exit door
Stelzner had reason to hesitate. In his public account of the launch, he described an earlier commitment to Web3 that had gone badly. Emerging trends had begun to look like expensive distractions. Then his COO encouraged him to look again at AI. The show launched in May 2024. By episode four, he says, the team had declared the experiment successful and made it permanent.
“The plan was to only run 12 episodes.”
Michael Stelzner, on the launch
The lesson is transferable, with a qualification. Define a trial, decide what evidence matters, and give yourself permission to stop. Social Media Examiner already had a marketing audience. A new publisher starting from zero cannot assume the same result, or borrow its download target without thinking.
A publisher answers the next question
AI Explored belongs to Social Media Examiner, the media and education business Stelzner founded in 2009. Its audience is specific: marketers, creators, and business owners who want to use AI. These are people who may have a campaign to finish before they have time to understand the technology underneath it.
The product is an interview, distributed weekly across podcast platforms and YouTube, with written episode notes on the publisher’s website. That second format matters. Audio is good company on a walk. A sequence of instructions is easier to inspect beside a laptop. You can move from listening to trying without transcribing an entire conversation.
There are other ways to spend this hour. Paul Roetzer and Mike Kaput’s The Artificial Intelligence Show covers AI news and its business implications. AI Explored’s practical interviews offer a different editorial emphasis: someone describes a job, the tools involved, and the decisions inside the job. Choose according to what you need to do next.
The chocolate test
Consider Angie Carel’s appearance. She describes mapping a process from input to output before building it. One example follows leads about snack foods, candy, and ice cream. An assistant finds them; another qualifies the ones containing chocolate. Further assistants turn the results into blog and social content. Chocolate becomes the filter that keeps a workflow from becoming an indiscriminate content machine.
Carel also describes a business response to cheaper logo ideation. Her VIDA assistant lets clients develop concepts for free; her expertise refines and finishes the work she charges for. The useful question is where the customer still needs judgment after software makes the first attempt inexpensive.
For a reader, the next move can be modest. Draw the starting material on one side of a page and the desired result on the other. Write down the steps between them. Carel recommends familiar tools and a few high-value uses. A complicated chain is harder to troubleshoot when you have not mastered its parts.
Five hours, taken apart
Rick Mulready brings another kind of specificity. His weekly newsletter consumed roughly five hours and drained his energy. His advice begins with recording work over five to seven ordinary business days, including how each task feels. The job you dread may be a better starting point than the task that makes the most impressive demo.
Then take the job apart. Research, selection, outlining, writing, and publishing contain different decisions. Mulready describes a MindPal workflow that researches newsletter material and pauses for him to choose the story. That pause is worth noticing. Faster research still leaves an editorial choice.
- AuditRecord time and energy.
- DeconstructSeparate the decisions.
- TestKeep a review step.
He also recommends documenting the working process and repeating the time audit quarterly. This gives the listener something more useful than a feeling of progress: a way to check whether the experiment changed the week.
Your expertise has to leave your head
Loren Bartley’s interview shifts the problem from time to knowledge. Her Leadership Lexicon gathers beliefs, existing content, and notes so assistants can work with her methods. She recommends focused knowledge files and continued refinement. If the output misses how you would handle a situation, the documentation may be missing something.
Video has a similar appetite for material. Stephanie Nivinskus describes supplying about two hours of varied footage to train her avatar. Her lighting included an Elgato light that cost $100 when she bought it. Those are her reported inputs, rather than a universal production budget. Better source material still takes preparation.
Free listening. A separate commitment.
The podcast is free. Social Media Examiner separately sells education through the AI Business Society and conferences. On October 9, 2026, its membership page advertised $597 annually or $77 monthly. A listener can use the public interviews without making that purchase.
The Society offers live training, recordings, resource kits, and a community. That arrangement puts free discovery beside paid depth. The practical test for a customer is whether structured learning helps finish work that self-directed listening leaves unfinished.
The show keeps following that work. Its October 6, 2026 interview with Jeff Sieh covers reusable design systems and on-brand visuals. The recurring challenge is giving a tool enough context to make something useful. Pick one job, describe it carefully, and inspect what comes back. An experiment earns its next episode.