What happens when one of tech’s most prolific entrepreneurs gives AI his entire framework for generating startup ideas?

In this episode of AI-Curious, we sit down with Bill Gross, founder of Idealab, to explore how he is using AI to scale a process he has spent decades refining: finding problems, connecting them with emerging technologies, and turning those connections into new companies.

Bill has helped launch more than 175 companies, and his latest experiment takes that idea factory to a new level. After feeding AI thousands of articles and applying his 31-method framework for innovation, the system generated roughly 32,000 company ideas in an hour. He then scaled the process across millions of documents, producing tens of millions of raw ideas that were ultimately narrowed down to about 1.2 million.

We dig into how the system works, what AI is actually good at when it comes to creativity and lateral thinking, and why Bill sees the technology less as a replacement for entrepreneurs and more as a tool for dramatically expanding what they can do.

We also talk about the parts AI cannot automate away: timing, execution, judgment, pricing, strategy, and knowing when the market is actually ready. Bill explains why a good idea is only the starting point, how Idealab.ai is designed to help more people explore entrepreneurship, and why he believes AI could lower the barrier to starting companies around the world.

The conversation also explores idea ownership, open-source entrepreneurship, AI safety, the risks of bad actors using similar systems, job displacement, job creation, and Bill’s vision of a future where AI gives small teams and solo founders more leverage against much larger companies.

Guest
Bill Gross — Founder, Idealab.AI

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Why are so many people getting faster with AI, while their companies still move at the same speed?

In this episode of AI-Curious, we bring you a live panel conversation from HumanX Amsterdam with Andrey Khusid of Miro, Nasrin Mostafazadeh of Verneek, and Imad Riachi of Honu. Together, we explore one of the biggest questions in enterprise AI: what has to change for humans and AI to work as a true team across an entire organization?

We discuss the gap between individual AI productivity and company-wide transformation. Many employees now have their own chatbots, agents, and AI workflows, but that does not automatically mean the business moves faster. The panel looks at why AI adoption often stalls at the organizational level, and why companies may need to redesign workflows, teams, accountability, and decision-making instead of simply giving everyone access to new tools.

Andrey shares how Miro uses AI internally through daily briefs, shared data surfaces, and a digital twin of the company, helping teams operate from the same source of truth. Nasrin explains why enterprise AI should begin with business strategy, not AI strategy, and how Verneek helps retailers and consumer brands use AI to improve merchandising, planning, and operational decisions. Imad brings a neuroscience and systems perspective, warning that we often mistake eloquence for intelligence and that overreliance on fluent AI systems can quietly erode human expertise.

We also explore augmented intelligence, organizational intelligence, AI governance, decision traceability, tacit knowledge, accountability, and why AI should not just make today’s work cheaper, but help companies build a more interesting tomorrow.

Guests
Andrey Khusid — Co-founder and CEO, Miro
Nasrin Mostafazadeh — Co-founder and CEO, Verneek
Imad Riachi — Founder and CEO, Honu

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What if the biggest limitation of AI agents is not intelligence, but context?

In this episode of AI-Curious, we bring you a live panel conversation from HumanX Amsterdam with Bianca Anghelina of Aily Labs and Stefan Ostwald of Parloa. We explore why “context is king” in the age of AI agents, and why even the most powerful models can struggle inside companies if they do not understand how the business actually works.

Bianca and Stefan both work with AI agents inside large enterprises, where success depends on more than model performance. We talk about what context really means in practice: internal business knowledge, company strategy, user history, market conditions, regulations, policies, permissions, governance, and the processes that shape how work actually gets done.

We also discuss why enterprise AI deployment is much harder than simply giving employees a chatbot. The panel gets into APIs, access management, semantic layers, real-time context, cost efficiency, token budgets, and the importance of measuring AI ROI instead of only measuring AI spend. Bianca shares how Aily Labs embeds business context into decision-intelligence systems for Fortune 500 companies, while Stefan explains how Parloa helps enterprises deploy AI agents for customer communication.

Finally, we explore what leaders can do to make AI adoption stick. From giving CEOs a “super agent,” to building safe AI playgrounds, to containerizing agents so they cannot run loose across a company’s systems, this conversation offers a practical look at how large organizations can experiment with AI agents without losing control.

Guests:
Bianca Anghelina — Founder, Aily Labs
Stefan Ostwald — Co-founder, Parloa

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For anyone interested in Jeff’s AI Workshops for their company:

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