20VC: SaaS is Dead: Why Systems of Record Will Die in an Agentic...
The Twenty Minute VC (20VC)Full Title
20VC: SaaS is Dead: Why Systems of Record Will Die in an Agentic World | What Revenue Multiple Will Software Companies Trade At? | From 7,000 to 3,000: We Need Less People Than Ever with Sebastian Siemiatkowski
Summary
The episode discusses how the increasing capabilities of AI will fundamentally disrupt the software industry, leading to reduced software creation costs and lower switching costs for data.
This disruption will impact SaaS companies and potentially lead to lower valuation multiples, while companies that leverage AI effectively, like Klarna, can achieve greater efficiency and competitive advantage.
Key Points
- AI is drastically reducing the cost of software creation, potentially to zero, enabling anyone to generate software.
- The switching costs of data currently lock customers into existing SaaS vendors, but AI agents will soon make data migration seamless, threatening traditional SaaS models.
- Software companies may see their valuation multiples decrease from historical highs (20-30x price-to-sales) towards those of utilities (1-2x price-to-sales) as their unique value proposition diminishes.
- Traditional systems of record (ERPs, CRMs) are vulnerable as AI agents can increasingly replicate their functionality, but companies like Klarna are reimagining their tech stacks to be AI-native, integrating AI into their core operations.
- Klarna has significantly reduced its workforce by 50% by leveraging AI, demonstrating a model for increased efficiency and productivity.
- The future of customer service is evolving towards a more human-centric, relationship-based approach, with AI handling routine queries and humans focusing on high-value interactions.
- The conversation touches upon the challenges and opportunities of global expansion, particularly in the US market, and the strategic importance of building a strong brand and customer data for fintech companies like Klarna.
- There's a discussion about the potential for AI to displace jobs, but also to create a "golden age of humanity" where people have more leisure time.
- The importance of founder's hands-on experience with AI tools like Cursor is highlighted for investors to properly evaluate AI startups.
- The underlying concept driving AI model size and capability is data compression, where the AI learns patterns and relationships rather than storing raw data explicitly, making large models manageable.
Conclusion
AI is a transformative force that will significantly reduce software development costs and data switching barriers, impacting SaaS valuations.
Companies that embrace AI, integrate it into their core operations, and focus on customer relationships will be best positioned for future success.
The future of work and business is being reshaped by AI, demanding adaptability and a focus on higher-value human skills.
Discussion Topics
- How will AI agents that reduce data switching costs fundamentally alter the competitive landscape for existing SaaS providers?
- As AI democratizes software creation, what new valuation metrics should investors focus on to assess the enduring value of software companies?
- What are the ethical considerations and societal impacts of widespread AI adoption in the workforce, and how can we navigate potential job displacement while fostering human flourishing?
Key Terms
- SaaS
- Software as a Service - A software distribution model where a third-party provider hosts applications and makes them available to customers over the internet.
- AI Agents
- Software programs that can perform tasks and make decisions autonomously, often interacting with their environment or other systems.
- Systems of Record
- Core business systems that store and manage critical organizational data, such as ERP or CRM systems.
- ERP
- Enterprise Resource Planning - Software that organizations use to manage day-to-day business activities such as accounting, procurement, project management, risk management and compliance, and supply chain operations.
- CRM
- Customer Relationship Management - Software solutions designed to help companies manage customer data and interactions, improve customer relationships, and drive sales growth.
- Valuation Multiples
- Financial ratios used to estimate the value of a business, such as price-to-sales or price-to-earnings ratios.
- BNPL
- Buy Now, Pay Later - A type of short-term financing that allows consumers to make purchases and pay for them over time, often in installments.
- IDE
- Integrated Development Environment - A software application that provides comprehensive facilities to computer programmers for software development.
Timeline
Host questions the value of software in a world where AI can generate code cheaply.
Discussion on how AI will lower data switching costs, posing a threat to SaaS.
The impact of AI agents on the threat to ERPs and CRMs is considered.
Analysis of how software company revenue multiples are changing and potentially declining.
Debate on whether large companies will "vibe code" mission-critical systems internally or stick to existing systems of record.
The idea of software becoming like Lego pieces, reusable and efficient, is explored.
Discussion on why enterprises spend heavily on replicating existing software functionality.
The concept of "Company in the Box" and how AI agents can manage core business operations is presented.
The future of ERP systems is discussed, moving towards broad, integrated solutions.
Klarna's strategy to build an AI-native tech stack as its company's operating system.
Klarna's approach to customer service automation and its impact on headcount.
The effect of announcing AI-driven efficiency on company perception and employee morale.
The shift in customer service focus from cost-saving to human connection and relationship building.
Klarna's innovative "Uber model" for recruiting passionate customers into customer service roles.
The debate on whether AI will lead to widespread job displacement or a new era of human prosperity.
Reflection on Klarna's past strategic decisions and whether they've changed in light of new information.
Klarna's long-term vision of becoming a digital financial system, driven by AI.
A comparison of Klarna's strategic positioning in the fintech space versus competitors like Revolut.
The focus on the US market for Klarna and the competitive landscape of US financial institutions.
Discussion on the advantages and disadvantages of being a public company CEO.
The ease of making strategic decisions and investments due to AI's efficiency gains.
The state of stock-based compensation (SBC) in tech and finance, comparing US and EU practices.
The changing nature of "money printing machines" in tech and finance due to increased competition and AI.
Lessons learned from past investment rounds and the importance of aligning revenue growth with multiple expansion.
The role of a strong board and the impact of investor scrutiny on decision-making.
The influence of Silicon Valley VCs on startup strategy and the importance of founder conviction.
The evolution of Klarna's product offerings beyond Buy Now, Pay Later (BNPL).
Klarna's transition away from high-interest revenue streams towards a healthier financial model.
The operational challenges and considerations for a bank, especially concerning customer relationships and data.
The influence of Stockholm as a hub for AI and tech innovation.
The debate on whether a US presence is essential for building a large startup today.
The state of venture capital in AI and the need for investors to understand the technology.
The role of AI in compressing knowledge and making large language models manageable.
A comparison of OpenAI's ChatGPT and Anthropic's Claude, focusing on their different user experiences and potential business models.
Changes in perspective on software investment due to AI's disruptive potential.
The underinvestment in data centers despite the growing demand for AI inference.
An anecdote about AI generating a complex financial animation, exceeding human capabilities.
Discussion on the massive compression of information in AI models due to repetitive data patterns.
The tension between data compression in enterprise and data regeneration for consumer use cases.
The role of AI in promoting data discipline and reducing redundancy in enterprise systems.
The concept of novelty in data and the debate on whether AI truly generates new information or variations.
Confidential topics discussed by CEOs in private that are not shared publicly.
The idea that AI might be forcing CEOs, even in public companies, to become builders again.
A personal experience of AI exceeding human capabilities in creating a complex financial explanation.
The potential impact of Elon Musk's Grok on the AI landscape and its competition with other models.
The role of AI in combating misinformation and establishing trusted sources of information on platforms like X.
Changes in perspective on the pace of AI adoption, with consumers adopting faster than enterprises.
The personal impact of criticism, particularly when it's perceived as untrue.
Reflecting on what one would do differently if freed from public scrutiny and investor pressure.
The importance of authentic leadership and building personal connection with customers over solely focusing on products.
The immense pressure and psychological impact of high-stakes performance, drawing parallels to professional sports.
The evolution of a founder's vision from early-stage ideas to a fully realized global business.
The motivations behind building a business, including personal aspirations and inspirations from other entrepreneurs.
The common trait of a "broken relationship with their father" among successful unicorn founders and its potential impact.
The realization that money cannot solve all personal problems, despite initial aspirations.
Excitement for future advancements in AI and its potential to improve human lives and realize business visions.
The future of AI enabling faster and higher-quality realization of business visions.
Episode Details
- Podcast
- The Twenty Minute VC (20VC)
- Episode
- 20VC: SaaS is Dead: Why Systems of Record Will Die in an Agentic World | What Revenue Multiple Will Software Companies Trade At? | From 7,000 to 3,000: We Need Less People Than Ever with Sebastian Siemiatkowski
- Official Link
- https://www.thetwentyminutevc.com/
- Published
- February 16, 2026