7 AI Theses That Will Shape Your Software Startup in 2025 - with Christoph Gerber, Talon.One

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About this episode

Christoph Gerber has proven with Talon.One that sustainable software companies can be built even in highly competitive markets. As co-founder of Lieferando and now CEO of Talon.One with over 300 employees, nearly 300 customers including Adidas, H&M, and Sephora, plus €135 million in funding, he shares seven battle-tested theses that will shape software startups in 2025.

Thesis 1: Trust Beats Hype

While the AI world is driven by hype cycles, Gerber focuses on a different currency: trust. "AI accelerates workflows, but it doesn't replace relationship building," explains the Talon.One founder. For software startups, this means: instead of jumping on the latest AI trend, they should consistently work on building trustworthy customer relationships.

Trust takes time – something often forgotten in the fast-paced startup world. But especially in an era where AI tools are available everywhere, the human component becomes the crucial differentiating factor.

Thesis 2: Think Value-Based Pricing

Traditional seat-based pricing has had its day. Gerber advocates for a paradigm shift: "Away from seat-based, toward measurable customer value." The challenge lies in finding the right pricing strategy that reflects the actual value of the software.

For startups, this means fundamentally rethinking their pricing models. Instead of charging based on number of users, they should ask: What concrete, measurable value do we create for our customers? This value-based pricing approach will become standard in 2025.

Thesis 3: Moats Through Deep Integration

Surface-level apps are easily replaceable. Gerber therefore focuses on defensibility through deep integration into customers' core infrastructure: "Real moats aren't created in loose apps, but in core infrastructure." Switching costs become a natural protective barrier.

Startups should ask themselves: Are we just building another app, or are we integrating so deeply into our customers' workflows that switching becomes painful? The answer determines the long-term defensibility of the business model.

Thesis 4: Consciously Choose Buy or Build

The decision between buying and building becomes more strategic than ever in 2025. Gerber's rule of thumb: "Buy software where it brings speed, build mini-apps when internal development is faster." It's about finding the right balance between external efficiency and internal control.

For startups, this means conscious resource allocation. Not everything needs to be developed in-house – but the critical components that create competitive advantage should remain under internal control.

Thesis 5: Go-to-Market Remains the Bottleneck

Despite all AI advances, classic go-to-market challenges don't disappear. "Security, compliance, procurement don't vanish because of AI," warns Gerber. Sales remains crucial, especially in the enterprise space.

Startups must understand that while AI can optimize processes, fundamental sales and compliance requirements persist. Those who cut corners here will later fail against B2B market realities.

Thesis 6: Productivity Before Layoffs

Instead of immediately cutting staff, startups should use AI as a productivity enabler: "More output with existing teams." The right balance between efficiency gains and team stability becomes a success factor.

This mindset not only creates a better work environment but also optimally leverages existing know-how. AI becomes a tool that amplifies existing talent rather than replacing it.

Thesis 7: Performance Under Load Non-Negotiable

Latency and reliability remain non-negotiable even in the AI era. "Scaling as a challenge" becomes a test for many startups. Quality determines long-term success.

Especially when AI features require additional computing power, performance and stability cannot suffer. Customers forgive innovative features, but not poor performance.

Conclusion: Practice Over Theory

Gerber's seven theses show: successful software startups in 2025 combine AI innovation with proven business principles. Trust, thoughtful pricing, deep integration, and solid go-to-market strategies remain the foundation – AI amplifies these factors but doesn't replace them.

For founders, this means: less hype, more substance. The future belongs to those who use AI strategically without forgetting the basics.