Anish Acharya: Is SaaS Dead in a World of AI?

The popular narrative that SaaS is dead due to AI is challenged.

The discussion shifts to what is changing in the SaaS landscape due to AI.

A disagreement arises about the advantages of building tech companies in different locations versus SF.

The conversation touches on the changing definition of "sufficient" for venture outcomes.

The sustainability of traditional enterprise revenue is questioned amidst market sentiment.

The increase in SaaS prices post-ChatGPT release is examined in relation to growth.

The decreasing cost of transitioning between SaaS providers and its impact is discussed.

The question of who wins in the AI era – incumbents or startups – is posed.

The value creation potential of the application layer compared to foundation models is debated.

The shift from a single dominant foundation model provider to a multi-model landscape is analyzed.

The relationship between increasing AI efficiency and human ambition is explored.

The market composition for developer tooling in the AI era is likened to cloud rather than ride-sharing.

The concept of competitive investing and its relevance in the current market is questioned.

The opportunity in the "apps layer" and threats from foundation models themselves providing products is discussed.

The idea that "boring wins" is contrasted with the potential for "weird wins" in AI.

The fundamentally different, human-like nature of AI models compared to previous technologies is highlighted.

The concept of "companionship" as a category for AI innovation is explored.

The idea of a contextual companion for children playing video games is proposed.

The evolving UI paradigm in the world of AI is questioned.

The concern about defensibility, switching, and "steerability" in the AI landscape is raised.

The changing prominence of different forms of defensibility is discussed.

The idea that AI has not significantly altered traditional forms of defensibility is considered.

The importance of margins in the context of AI is debated.

The statement "inference is the new sales and marketing" is discussed.

The increased power and willingness of "power users" to pay for AI products is noted.

The challenge of accurately assessing LTV in a rapidly changing AI landscape is discussed.

The distinction between acquisition-oriented margin spend and durable margin profiles is clarified.

The argument against AI being in a "bubble" is presented.

The concept of "intelligent subsidization" by Big Tech benefiting consumers and startups is discussed.

The transition of spend from SaaS budgets to human labor budgets due to AI productivity gains is debated.

The bundling of traditional enterprise functions and the role of AI in achieving capital improvement is explored.

The highly competitive nature of the customer support software market is highlighted.

The definition of a "market" versus an "industry" is crucial for understanding competition.

The potential for AI native companies and massive productivity increases is discussed.

The difficulty of the "zero to one" phase in startups and the importance of shipping products is emphasized.

The underestimation of market size by investors is a recurring theme.

The guest shares his most memorable first founder meeting.

The concept of "inertia" as a mental model for investing in founders is discussed.

The guest's claim of never having lost a deal is questioned.

The importance of seeing 100% of deals in a sector and winning all pursued deals is stated as an expectation.

The elasticity of investment ownership versus price is discussed.

The concept of "triple, triple, double, double" growth is contrasted with AI-native company growth.

The "area under the curve" investment thesis is explained.

The difficulty of Series A investing due to high valuations and early-stage uncertainty is noted.

Different types of investment risks are categorized and discussed.

The perceived increase in founder "promiscuity" is explored.

The need for founders to have an "irrational direction" or commitment to their problem is highlighted.

The best founders are generally great fundraisers, but their styles can vary.

The value of repeat founders working within their domain of expertise is emphasized.

The most significant change in investing approach is the imperative to use products extensively.

The potential overhype of "agents" in the current AI landscape is discussed.

The need for humans in the loop and clear instructions for AI agents is highlighted.

The idea of owning the full stack versus being a meta-layer in the agentic world is debated.

Ambiguity is identified as a key factor in the effectiveness of agents.

The future of RPA companies like UiPath is questioned in the context of AI.

The open versus closed model debate in AI is introduced.

The potential for AI products to be substituted based on price is discussed.

The impact of improved AI capabilities on user behavior, prioritizing capability over cost, is noted.

The importance of companies having a viable business model from the outset, driven by product costs, is emphasized.

The significant expansion potential of software into discretionary spending areas is discussed.

The role of investors in providing brand capital and creating credibility for early-stage companies is explored.

Alex is highlighted as an exceptional founder with strong go-to-market instincts and product creativity.

The most significant mistake made by the investor was being too casual about product-market fit.

The idea of "area under the curve" companies that take time to develop is contrasted with faster-moving startups.

The Andreessen brand is seen as a tailwind, never a hindrance.

The strengths of Mark, Ben, and DG as investors are discussed.

The hardest decision was transitioning from being a builder to an investor.

The expectation at Andreessen is to see 100% of deals in their sector and win 100% of pursued deals.

Brompton is identified as a special seed manager due to his consistent ability to be right.

The guest has changed his mind on the idea that early leaders in product cycles would not necessarily maintain their dominance.

New AI-native categories are expected to emerge in 2026, with early leaders in existing markets maintaining their position.

Mockbook is described as a fascinating technology with potential for digital twins and scaled human interaction.

The guest is most optimistic about the potential for AI to bring peace and joy to more people.

The importance of founders being intellectually honest about product-market fit is stressed.

The importance of trying all new AI products and models to gain intuition is highlighted for founders and investors.

The podcast begins by addressing the "SaaS is dead" narrative in the context of AI.

The discussion shifts to how AI can be strategically applied in enterprise spend.

The conversation turns to the diminishing switching costs for SaaS due to coding agents.

The resilience and capabilities of incumbent SaaS providers in the AI era are examined.

The potential for disruption and innovation in new AI-native categories is explored.

The investor reflects on past mistakes, particularly regarding product-market fit.

The high standards and expectations at Andreessen Horowitz for deal coverage and win rates are discussed.

A change of mind regarding early leaders maintaining dominance in AI product cycles is revealed.

The guest emphasizes the critical need for founders and investors to actively use and understand new AI products.