Software Winners & Losers in the Age of AI (w/Alex Rubalcava & Paul Bricault) | #626
Alex Rubalcava and Paul Bricault discuss the current state of software companies amid AI disruption, their venture fund Amplify LA's pre-seed investment strategy, and how AI is transforming enterprise software through increased productivity and workflow automation. They share specific examples of portfolio companies leveraging AI and discuss which types of software businesses are most vulnerable to displacement.
Summary
This episode features Alex Rubalcava (formerly of Stage Venture Capital) and Paul Bricault from Amplify LA discussing the impact of AI on software companies and their pre-seed investment approach. They begin by addressing concerns about public software companies, with Rubalcava arguing that mission-critical software touching money, regulation, or physical assets will survive, while 'nice-to-have' products face displacement risk. The guests explain Amplify LA's focus on pre-seed enterprise software investments, typically $2-3 million rounds, with about 50% in Southern California. They emphasize investing in companies with defensible moats like proprietary data, regulatory barriers, or physical constraints that make them harder to disrupt. The conversation covers numerous AI adoption examples from their portfolio, including Placer's AI front-end for foot traffic data that saved a multimillion-dollar real estate deal, and Trace's use of AI agents to replace 39 out of 40 SDRs and CSRs while growing revenue 50%. They discuss concerning job displacement effects, particularly for entry-level positions in data analysis, customer service, and basic content creation. The guests share investment stories including pivots (like a hologram company becoming a 3D file conversion service) and outline their approach to taking profits from successful investments through secondary sales when companies hit 10x returns. They conclude by discussing QSBS tax benefits for early-stage investors and the importance of building networks for pre-seed sourcing, as AI tools don't work well for finding companies that haven't been announced yet.
Key Insights
- Rubalcava argues that software companies serving as systems of record or touching money, regulation, and physical assets will survive AI disruption better than 'nice-to-have' products
- Portfolio companies are reporting 4-5x increases in engineering productivity and code output within 100 days of adopting advanced AI tools
- One portfolio company reduced staff from 40 SDRs/CSRs to 2 while growing revenue 50% by implementing AI agents for sales and customer service
- Placer's AI front-end enabled a customer to create a presentation in 90 minutes that would have taken three weeks, saving a multimillion-dollar real estate transaction
- Pre-seed round sizes have doubled from $1-2 million to $2-3 million over the past two years, with some extreme outliers reaching $100 million for foundational model companies
- The guests observe a decoupling of revenue growth from expense growth, with many portfolio companies growing revenue multiples without increasing headcount
- Entry-level jobs in data analytics, customer service, content creation, and basic legal work are disappearing rapidly, creating challenges for college graduates
- AI tools are shifting the balance from outbound sales effectiveness to inbound marketing effectiveness as automated outreach floods the market
- The firm focuses on investments with proprietary data advantages, regulatory constraints, or physical world integration as defensive moats against AI disruption
- Companies that adopted AI tools show significantly higher revenue growth according to recent data from fintech company Ramp
- The programming language for most software has effectively become English as AI enables natural language interfaces and workflow customization
- Pre-seed investing remains more defensible against AI tools compared to later-stage investing because early companies often aren't publicly known or trackable by AI systems
Topics
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