Agents at work
Agents at work
Podcast Description
Your front-row seat to the AI agents revolution! Join us as we explore the cutting-edge world of AI agents through in-depth conversations with the pioneers shaping this technology. From breakthrough architectures to practical deployment strategies, we bring you insights from builders, researchers, and innovators who are turning autonomous AI agents from science fiction into reality.
Podcast Insights
Content Themes
The podcast focuses on the integration of AI agents across various sectors including software development, sales operations, and product management. Each episode covers specific case studies and insights, such as exploring the use of Large Language Models in enhancing developer experiences, the challenges of agent deployment in sales, and innovative monitoring tools for AI systems. Episodes emphasize themes like the transformative impact of AI on coding practices and the emerging need for new performance metrics in AI applications.
Your front-row seat to the AI agents revolution! Join us as we explore the cutting-edge world of AI agents through in-depth conversations with the pioneers shaping this technology. From breakthrough architectures to practical deployment strategies, we bring you insights from builders, researchers, and innovators who are turning autonomous AI agents from science fiction into reality.
In this episode of Agents at Work, Jordi Montes talks with Ben, the builder behind Polsia.
Ben is building an AI “founding team” that can spin up and run online businesses end-to-end.Instead of asking “what can agents do in theory?”,
He runs the growth loop for real: generate an idea, ship a landing page, wire up Stripe, run outreach/ads, respond to customers, ship fixes, and repeat without a human babysitting every step.
They get into:
– The autonomous growth loop: idea → build → launch → traffic → revenue → learn → iterate
– Why the winning move is speed + distribution, and why startups that aren’t “80% autonomous” get outpaced
– What it takes to give agents the full stack (web server, DB, GitHub, email, payments, ad accounts) so experiments run end-to-end
– Ben’s approach to shipping fast without breaking everything (model cross-checking + safer deploy decisions)
– How per-company memory + shared “best practices” turns one agent into a compounding advantage across many businesses
– The real business question: do you sell software, sell tokens, or take a cut of outcomes?
If you care about shipping faster than your competitors, turning experiments into compounding systems, and using agents to run the messy parts of a business (not just generate copycats) this one’s for you.
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