AI Hype Meets Hidden Costs: The Risky Reality of Build vs. Buy in GTM

May 3, 2026 · Topline
🎧 PodShort 62 min squeezed to 3 AI SprinklerAS Sales Tech New
Episode artwork
Liz Cristofalo
General Partner at Stage 2 Capital
Topline
62 min squeezed to 3
Full episode from Topline
Quotable Moments

Pitch decks read like really ridiculous right now, where everybody wants to tell the story of like a $10 billion outcome because that's the new milestone that got set. These numbers that I am seeing now are so crazy.

Liz CristofaloGeneral Partner at Stage 2 Capital
00:12

There's like a huge amount of cost buried behind the scenes that we're not really talking about today because it's still like sexy and fun.

Liz CristofaloGeneral Partner at Stage 2 Capital
00:32

Somebody is bothering to prepare that and put it in front of you, like take time to read it and write notes.

Liz CristofaloGeneral Partner at Stage 2 Capital
02:56
Key Insights
  • Pitch decks for generative AI startups are increasingly absurd, with everyone wanting to tell a story of a $10 billion outcome, even for highly niche or small markets, making the current environment ridiculous.
  • Teams building their own internal tools with AI carries major hidden risks, as companies are not considering the long-term maintenance, edge cases, security, and compliance aspects beyond the initial build.
  • Many companies are acquiring others not for their customer base or ARR, but primarily for their AI talent, highlighting the high cost and strategic importance of acquiring skilled AI engineers.
  • Despite the ease of building tools with AI, there's a significant hidden cost in terms of time and maintenance that many companies aren't fully considering, leading to a false sense of efficiency.
  • The focus on large TAMs and $10 billion outcomes in pitch decks has become unrealistic, with valuations for entire markets like legal services being smaller than the combined valuation of just a few AI companies.
  • Salesforce's acquisition of Slack, and Slack's prior acquisition of Troops.ai, shows that even large tech companies struggle to integrate and leverage acquired technology quickly, leading to long delays in product realization.
  • The shift towards AI-powered internal tools means companies must define clear policies on where AI should and shouldn't be used, especially to prevent the erosion of critical thinking skills among employees.
  • Qualities of a successful founder remain consistent: grit, genuine connection to the problem being solved, and the ability to attract and build a great technical team, rather than relying solely on AI to build solutions.
Metrics Mentioned
  • 10 billion dollar (outcome for generative AI startups in pitch decks)
  • 170 percent (global organization for NetSuite's BDR team)
  • 30-40 million (revenue for a PE-owned business that collapsed engineering, design, and product into one team)
  • 50 dollar (a month for software subscriptions)
  • 200 dollar (a month for cloud subscriptions)
  • 250 billion dollars (raised by startups in venture funding in Q1 this year)
  • 50 percent (of the venture capital raised in all of 2025)
  • 75 percent (of the venture capital raised in all of 2025)
  • 125 percent (of the venture capital raised in all of 2025)
  • 100 million (in revenue for businesses in Pavilion Gold)
  • 3.1 billion (valuation for Clay, a company mentioned in the podcast)
  • 10 million (revenue when a company starts)
  • 50 million (revenue for a company to hit the next tier of growth)
  • 100 million (revenue for a company to hit the next tier of growth)
  • 1 billion (revenue for a company to hit the next tier of growth)
  • 27 percent (chance to get from $10M to $50M ARR)
  • 29 percent (chance to get from $10M to $50M ARR)
  • 30 percent (chance to get from $10M to $50M ARR)
  • 31 percent (chance to get from $10M to $50M ARR)
  • 15 percent (chance to get from $10M to $100M ARR)
  • 0.25 percent (chance to get from $0 to $10M ARR when starting a company)

RevBots.ai View:

  • AI Sprinkler stage companies often overlook long-term costs of DIY AI tools.
  • ARM stage companies focus on AI orchestration, avoiding the pitfalls of fragmented AI adoption.
  • SaaS Hoarder companies risk acquiring AI talent without integrating it into a cohesive strategy.
  • Tab Hopper companies face existential threats as AI rewrites traditional SaaS playbooks.
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