In this episode, we sit down with Daniel Thulfaut, Head of Product at saas.group, one of Europe's most active SaaS acquirers. With 24 companies in the portfolio and more than €100M in ARR, Daniel has a unique perspective on how product organizations are evolving in the age of AI.

We discuss why many product managers have spent the last decade acting as backlog managers rather than true product leaders, and why AI is now forcing a return to the fundamentals of product management: customer understanding, strategic thinking, prioritization, and decision-making.

We also explore why "good enough" products are becoming easier than ever to build, why that raises the bar for SaaS companies, and what legacy SaaS businesses must do to stay competitive against a new generation of AI-native startups.

Topics we cover include:

• Why the traditional product manager role is changing rapidly • The difference between backlog management and real product leadership • Why AI makes customer discovery more important, not less • Why legacy SaaS companies struggle to realize the promised 10x AI productivity gains • The rise of the "product engineer" and what it means for teams • How feature flags, experimentation, and faster feedback loops change product development • Why shipping more features is not the same as creating more value • What CEOs and CPOs should do right now to prepare their product organizations for the future • Why understanding customer problems remains the most valuable skill in product management

One of the most interesting takeaways from the conversation is that AI is not replacing product thinking. If anything, it's making it more valuable. When building becomes easier, deciding what to build becomes the real competitive advantage.

If you're a founder, CEO, CPO, product leader, or anyone trying to navigate the future of SaaS, this episode is packed with practical insights and plenty of food for thought.

In this episode we sit down with Artti Aurasmaa, CEO of Staria, to discuss how the CFO role is evolving from financial reporting to strategic leadership.

Artti has spent more than 25 years helping companies scale internationally and today leads Staria, a €60M+ business serving growth companies across 50 countries. In this conversation, he shares why the future CFO must become a business partner, data steward, and forecasting expert rather than simply the person closing the books.

We discuss why forecasting accuracy may be the most important KPI for a modern CFO, how AI is changing finance teams, why strong data foundations matter more than the latest AI tools, and what separates companies that scale successfully from those that struggle.

You will also hear Artti's perspective on international expansion, the increasing complexity of global business, and why the best CFOs are moving from the back office to the front row.

Topics covered:

• Why the CFO role is becoming increasingly strategic
• The shift from historical reporting to future forecasting
• Why forecasting accuracy is a critical KPI
• How AI is changing the finance function
• Building the data foundation before deploying AI
• The future structure of finance teams
• International expansion and global compliance
• Why CFOs need stronger technical and data capabilities
• The rise of the "rockstar CFO"
• What growth companies need to scale successfully

Whether you're a CFO, founder, CEO, finance leader, or SaaS operator, this episode offers a practical look at how the finance function is changing and what it takes to stay ahead.

In this episode, we’re joined by George Storm, CRO at N.rich, for a conversation about why traditional B2B SaaS forecasting is no longer good enough in today’s market. George shares how N.rich, the European ABM platform, helps sales-led companies influence complex buying committees, warm up priority accounts, and progress accounts before sales ever reaches out.

We spoke with George about why forecasting can’t be treated as a static quarterly exercise anymore, why revenue leaders need to account for macro signals like layoffs, budget freezes, acquisitions, interest rates, and market turbulence, and how to move from fixed-number forecasting to ranges, probabilities, and continuous forecast loops. He explains why CROs should think in “regimes” like calm, turbulent, and stormy markets, and how that changes the way you model win rates, sales cycles, ACV, and pipeline coverage.

Here are some of the key questions we address:

• Why is traditional SaaS forecasting broken?
• Why should forecasts be modeled as ranges instead of fixed numbers?
• How do macro signals like layoffs, acquisitions, and budget freezes impact pipeline confidence?
• Why can historical win rates be misleading in today’s market?
• What does it mean to forecast in calm, turbulent, or stormy weather?
• How can CROs build a continuous forecasting loop instead of relying on quarterly updates?
• What should revenue leaders monitor weekly to avoid surprise misses?

🎧 Tune in to hear how George thinks CROs can build more realistic, adaptive forecasting models in a market where hope is definitely not a strategy.