Odd Lots

Jared Sleeper On Which Software Companies Will Survive The Saaspocalypse

February 19, 2026

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  • The current market panic in software, dubbed the "SaaSpocalypse," is driven by terminal value concerns regarding AI's long-term impact, even though current financial performance metrics for many software companies remain relatively stable. 
  • Software company value historically relies on more than just code generation, encompassing network effects, integration ecosystems, and herd familiarity, which complicates the immediate threat posed by cheaper code creation via AI. 
  • The future of software pricing may shift from per-seat models to results-based pricing, where vendors charge based on the value delivered (e.g., closed tickets), potentially leading to significantly higher total revenue capture if they successfully build AI-native agents. 

Segments

Software Stock Sell-Off
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(00:01:06)
  • Key Takeaway: The software sector is experiencing a sharp downturn, leading to widespread use of the term ‘SaaSpocalypse’.
  • Summary: Hosts discuss the decline in software ETFs and specific stocks like Salesforce and Atlassian, linking the sell-off to fears that AI code generation devalues software companies.
Guest Introduction and Background
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(00:04:17)
  • Key Takeaway: Jared Sleeper brings a unique perspective having invested across the entire software lifecycle, from early-stage startups to public companies.
  • Summary: The hosts introduce Jared Sleeper of Avenir and ask him to describe the current mood in the software investment community.
Why Software Was Historically Integral
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(00:07:05)
  • Key Takeaway: Software value historically derived from the high cost of building/maintaining code and the necessary ecosystem of integrations and user training.
  • Summary: Sleeper explains why companies historically outsourced software development, noting that the price charged was often less than the cost of one employee.
AI’s Impact on Code vs. Context
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(00:10:15)
  • Key Takeaway: AI is solving the code writing challenge, but the deeper challenge in integrations remains the human problem of understanding undocumented legacy system context.
  • Summary: The discussion covers whether AI agents can solve integration expertise, concluding that human knowledge about prior systems is often the bottleneck.
What Buyers Pay For Beyond Code
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(00:12:18)
  • Key Takeaway: Software buyers purchase support, herd familiarity (standardization), and brand trust, not just the raw code.
  • Summary: Sleeper details the components of software value, using Zoom and Excel as examples of products whose value extends beyond pure functionality.
Terminal Value Concerns Driving Sell-Off
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(00:14:28)
  • Key Takeaway: The market is pricing in a ‘cliff’ scenario where knowledge work fundamentally changes in 3-5 years, severely impacting long-term (terminal) value.
  • Summary: Sleeper outlines the two arguments against software valuations: cheaper building costs and the risk of radical changes to knowledge work.
Software Performance vs. Market Fear
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(00:16:33)
  • Key Takeaway: Despite the market panic, median software company financial performance (growth and retention) has remained relatively consistent over the last year.
  • Summary: Sleeper reviews data showing that growth rates stabilized around 18% after the pandemic peak, contradicting the immediate panic.
The Bull Case: Results-Based Pricing
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(00:28:01)
  • Key Takeaway: The major upside for software is shifting from selling tools (per-seat) to selling outcomes, allowing for massive increases in total revenue captured.
  • Summary: Sleeper explains how replacing human labor with AI agents allows vendors to charge significantly more by capturing a share of the labor cost savings.
Model Makers vs. Application Vendors
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(00:31:35)
  • Key Takeaway: Foundation model makers (like OpenAI) risk being commoditized if they don’t race toward the application layer to control user interaction.
  • Summary: The hosts discuss the risk that core model providers will compete with the application vendors who resell their intelligence.
Enterprise Caution vs. Startup Speed
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(00:34:34)
  • Key Takeaway: Enterprises are cautious about security and compliance when deploying AI agents, giving faster, less regulated startups a temporary advantage.
  • Summary: The discussion touches on the risks enterprises face when giving AI agents access to their systems, contrasting this with startup willingness to ‘play fast and loose’.
SBC and Lack of Financial Floor
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(00:35:42)
  • Key Takeaway: The prevalence of non-GAAP reporting masks weak GAAP profitability, meaning there is no valuation floor provided by dividends or buybacks.
  • Summary: Sleeper addresses the SBC debate and notes that without material GAAP earnings, software stocks lack the traditional support mechanisms seen in other sectors.
Predicted Layoffs and Talent War
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(00:38:45)
  • Key Takeaway: Layoffs are expected across the SaaS space as management seeks to cut costs and retain top talent against aggressive AI compensation packages.
  • Summary: Sleeper predicts management will eventually reduce headcount to show financial discipline and prevent their best employees from being poached by AI-native firms.