AI Agents Podcast

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In this episode of the AI Agents Podcast, host Demetri Panici sits down with Brendan Norman, co-founder and CEO of Classify, to explore how contextual intelligence is becoming a foundational layer for AI agents. Brendan breaks down how Classify helps machines understand content at a deeper, more human-like level—and why that matters for everything from advertising to autonomous agents.
They also dive into how AI is reshaping small teams, why agents still struggle with consistency, and what’s really happening behind the scenes as infrastructure evolves. If you want to understand the next layer of AI beyond models—the systems that make them actually useful—this episode is worth watching.
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⏰ TIMESTAMPS:
00:00 – Why understanding AI is constantly evolving
02:28 – Brendan’s background and building Classify
05:05 – Agents vs bots and how AI systems interact
08:12 – The missing layer: contextual intelligence
13:16 – Do AI models actually understand language?
19:19 – AI workflows, Claude, and productivity tools
24:11 – Building faster with AI as a small team
30:18 – Opportunities for startups in the AI era
36:38 – Explaining AI in a rapidly changing market
49:08 – Are we approaching the AI singularity?
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Every major tech shift follows the same pattern: one side says it’ll change the world overnight, the other says it’ll destroy everything. AI is no different—and both sides are usually wrong.
In this episode of the AI Agents Podcast, Rade Kovacevic (CEO of Polar Grid) breaks down what actually happens during massive market cycles, why AI progress feels chaotic, and where real value is being built right now.
We dive into the future of real-time AI, why latency is the hidden bottleneck, and how technologies like voice agents, edge computing, and AI infrastructure will shape the next wave of products.
If you want a grounded, no-hype perspective on AI’s future—this episode is for you.
Timestamps:
00:00 – Why viral AI takes are always extreme
02:00 – Rade’s background & building companies early
05:30 – The real problem with AI today: latency
09:30 – Why AI feels slow (and why it matters)
13:30 – Voice agents & real-time interaction challenges
18:00 – Where AI is going next (voice → video → gaming)
24:30 – AI hype vs reality in every market cycle
29:00 – Will AI replace jobs or just change them?
38:00 – How companies are hiring in the AI era
47:00 – The future of AI agents & human productivity
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Most people are still intimidated by advanced AI tools—but they don’t need to be. In this episode, we break down how AI-powered workflow builders are making automation accessible for everyday users and small businesses.
Demetri Panici and Aytekin Tank explore the current landscape of AI agents and workflow automation, comparing tools like Zapier, n8n, Pipedream, MuleRun, and Jotform’s upcoming AI-powered workflows.
They walk through real demos using the same prompt across platforms—automating weekly employee updates—to show how each tool performs, where they shine, and where they fall short. From no-code simplicity to more advanced agent-based systems, this episode highlights the trade-offs between usability, flexibility, and power.
If you’ve ever wanted to automate repetitive work but didn’t know where to start, this episode gives you a clear, practical look at what’s possible today—and what’s coming next.

⏰ TIMESTAMPS:00:00 – Why people are still scared of AI tools
00:49 – What are AI workflow builders?
05:13 – Jotform AI workflow demo
09:18 – MuleRun & building full tools with AI
14:52 – Pipedream demo (email automation)
18:28 – Zapier AI workflow builder
21:24 – n8n: powerful but intimidating
23:41 – AI agents (Perplexity & Claude demos)
29:00 – Real-world automation examples
33:43 – Where Jotform fits + future of AI workflows
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In this episode of the AI Agents Podcast, host Demetri Panici sits down with Tina Kung, Co-Founder and CTO of Nue (nue.io), to discuss why preventing AI hallucinations becomes critical when AI moves beyond insights and starts executing real financial transactions.
Tina explains how transactional intelligence is changing how companies manage revenue, why data accuracy is essential for AI systems operating in finance, and how AI agents can move from summarization to actually taking action — generating quotes, creating invoices, and executing complex revenue workflows automatically.
They also dive into evolving AI-native revenue models, how modern AI companies structure pricing, how engineering teams are already transforming their workflows with AI agents, and what the future of AI-driven operations looks like across sales, finance, and product teams.
If you're interested in AI agents that don’t just analyze data but actually act on it — this episode is worth watching.
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⏰ TIMESTAMPS:
00:00 — Preventing AI hallucinations in financial transactions
00:54 — Introducing Tina Kung and Nue (nue.io)
03:02 — Transactional intelligence vs traditional AI insights
07:03 — AI that takes action: quotes, invoices, and automation
09:13 — AI companies and hybrid revenue models
16:27 — New pricing models emerging in the AI era
23:02 — Building practical AI without hallucinations
29:13 — How AI is changing engineering teams
33:03 — Hiring shifts in the AI-first world
36:47 — Tina’s personal AI productivity stack
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In this episode of the AI Agents Podcast, host Demetri Panici sits down with Jotform Founder & CEO Aytekin Tank to discuss the newly emerging ChatGPT App Store and why it could become one of the biggest shifts in software distribution.
Aytekin explains how MCP (Model Context Protocol), originally introduced by Anthropic, helped shape the idea of connected AI apps — and how OpenAI’s ChatGPT App Store is bringing that vision to life. Instead of switching between dozens of SaaS tools, users can now interact with apps directly inside ChatGPT using natural language.
They also explore real-world examples including Jotform, Canva, Adobe Photoshop, Apple Music, and TripAdvisor integrations — showing how AI agents can connect tools, automate workflows, and reduce the need for traditional interfaces.
The conversation also covers why chat interfaces may replace traditional SaaS dashboards, how AI memory improves personalization, and why companies that build AI integrations now could benefit from massive distribution.
In this episode, we're seeing how AI agents and app stores are converging — and why the next generation of software may live entirely inside AI.
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⏰ TIMESTAMPS:
00:00 – MCP, Anthropic, and the rise of AI app ecosystems
01:07 – Introduction to the ChatGPT App Store
03:22 – Why AI apps feel like the early Apple App Store
05:28 – Jotform inside ChatGPT: building forms with AI
10:36 – Moving from traditional UI to chat interfaces
16:46 – Why AI apps are more powerful with context & memory
24:15 – Canva, Photoshop, and AI creative workflows
29:30 – TripAdvisor and AI travel planning apps
32:45 – Why ChatGPT apps are still early but growing fast
35:21 – The future of SaaS: apps inside AI agents
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