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​Podcast, YouTube, Blog​

Dear founder,

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When Peter Jackson was brainstorming the Lord of the Rings movie universe, two amazing Tolkien-savvy illustrators sat in on the meetings: John Howe and Alan Lee.

Jackson would explain a scene, what was where, and they would sketch as he talked.

When he was done explaining, the two artist would hand over their quick sketches, allowing the director to see what he had just envisioned.

Until now, you needed extraordinarily gifted experts with years of experience to do this kind of work effectively.

But someone out there is currently working on a generative AI tool that takes and visualizes ideas as they’re spoken, in real-time, at scale. And if no one is working on that just yet, maybe you should. Because in the months to come, professionals in all kinds of industries will expect this tool to exist for their own use cases.
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🎧 Listen to this on my podcast.​

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The Evolution of AI Tools: From Specific to Omnipresent

The expectations around AI-powered software have shifted dramatically. I’ve witnessed this transformation firsthand while building Podscan, and it’s fascinating to see how our relationship with AI tools has evolved.

Remember when AI was this mysterious thing that only existed in specialized, expensive tools? Back then, AI meant machine translation, predictive analytics, or neural networks churning through massive datasets. It was specific, limited, and usually hidden behind complex interfaces. The tools were compartmentalized: you had one for translation, another for data analysis, and yet another for predictions.

But look at what’s happening now. I opened Ahrefs the other day – my go-to SEO tool – and noticed something telling: their AI content helper has claimed the prime spot in the navigation, pushing traditional features like Site Explorer and Keyword Explorer toward the back. This isn’t just a UI decision; it reflects a fundamental shift in how we expect software to work.

Through my work on Podscan, I’ve discovered something particularly interesting about AI’s capabilities. While we often worry about AI hallucination in creative tasks, I’ve found AI to be remarkably reliable in analytical work. When I use AI for question-answering and data extraction, it’s impressively accurate. The key insight? AI excels at reducing complexity but struggles with expanding it. It’s like the difference between summarizing a book and writing one from scratch.

This observation leads me to envision three distinct ways AI is reshaping software tools:

AI as Your Guide

Imagine a sales pipeline tool that doesn’t just show you how to use features, but actually guides your strategy. It might suggest, “Hey, you should get Customer Success to reach out to this specific customer for a testimonial that would perfectly fit your current sales conversation.” The AI becomes less about interface navigation and more about achieving your actual business goals.

AI as Your Validator

This is where my experience with Podscan has been particularly enlightening. AI shines when it comes to verification and validation. While we often hear about AI hallucination, that’s mainly a concern with creative tasks. For analytical work – fact-checking, data verification, consistency checks – AI is remarkably reliable. It’s like having a meticulous assistant who never gets tired of double-checking your work.

AI as Your Opportunity Scout

Here’s where things get really interesting. AI can act as a constant background presence, scanning your business data for opportunities you might miss. Think of it as an AI agent that works while you sleep. For developers, this could mean an AI system that continuously analyzes your codebase, not just finding bugs but actively fixing them through simulation and testing.

The implications go far beyond tech. Imagine an AI that notices you haven’t spoken to a key customer in four weeks, remembers they usually attend an upcoming conference, and suggests scheduling a meeting. Or one that recalls a customer mentioned launching an article in April and reminds you to follow up in March.

What fascinates me most is how AI is evolving from being a mere text or image generator to becoming an ambient intelligence that enhances every aspect of our work. In my experience building and using AI tools, I’ve seen that the real power isn’t in flashy features but in this quiet, persistent assistance that makes everything we do a little bit better.

The future of AI in software isn’t just about chatbots or generating content. It’s about having an intelligent presence that helps you source opportunities, guides you through processes, and validates your work. It’s becoming the background rhythm of modern software, orchestrating improvements in ways we’re only beginning to understand.

As someone building in this space, I can tell you: we’re just scratching the surface of what’s possible when AI becomes less of a feature and more of a foundation.

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If you want to track brand mentions, search millions of transcripts, and keep an eye on chart placements for podcasts, please check out podscan.fm — and tell your friends!

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