So we came back to HubSpot’s My First Million Podcast with Sam Parr and Shaan Puri to do a deep dive on AI and SaaS. It was a fun one because we approached it more from a content creator and end-user perspective vs. a software builder perspective.
The Top 10 AI in B2B Takeaways:
1. AI Clones Can Outperform Their Human Creators. Our SaaStr AI Can Outperform Jason Lemkin.
The Breakthrough Discovery: Lemkin’s AI version, trained on 20 million words of his content (equivalent to 200 books), consistently outperformed him in business conversations and advice.
Why This Matters:
- The AI remembers everything across 12 years of content while humans forget
- It can connect insights from different time periods that humans can’t recall
- Perfect memory combined with weighted content creates superhuman advisory capabilities
- Users asked deeper, more vulnerable questions than they would to humans
Business Implications: This suggests AI advisors could replace human consultants in many knowledge-work scenarios, offering 24/7 availability with perfect recall of all relevant information.
2. People Confess More to AI Than Humans
The Psychology Revelation: Users shared their deepest business fears and personal struggles with the AI that they wouldn’t tell human advisors.
Real Examples from SaaStr’s own AI:
- “I’ve partnered with Sam on this podcast, but I’m not sure he’s committed as me”
- “I don’t know if my board’s going to fire me”
- “I’m only growing 18%, I have 11 months of runway”
Why This Happens:
- Reduced judgment anxiety
- Perceived anonymity and safety
- 24/7 availability for vulnerable moments
- No social consequences or relationship complications
Impact: This creates unprecedented opportunities for AI therapy, coaching, and advisory services where emotional safety is paramount.
3. Traditional B2B Software Workflows and Interfaces Are Dying
The Death of Interfaces: Lemkin predicts we’ll spend 24 hours a day in ChatGPT-like interfaces, making traditional B2B app interfaces obsolete.
Current Evidence:
- Going from B2B apps to ChatGPT already feels “dated”
- MCP (Model Context Protocol) allows AI to pull data from any app without logging in
- Companies like Salesforce and Okta are seeing slowed growth (7-10%)
- The average public SaaS company traded at 70X ARR in 2021, now at 5X
The New Reality:
- CRMs become invisible database plumbing
- No need to learn complex interfaces or configurations
- Voice and chat replace point-and-click navigation
- “The kids these days will never use software like we use it”
4. Zero-to-One Million in ARR is Now “Much More Likely” in AI. But Revenue is Also Less Stable.
The Fundamental Shift: Lemkin’s famous framework has been disrupted by AI capabilities.
Old Framework:
- Zero to $1M: Impossible
- $1M to $10M: Unlikely
- $10M to $100M: Inevitable
New AI Reality:
- Zero to $1M: Very likely (can happen in weeks)
- Beyond $100M: Everyone getting disrupted
Why This Changed:
- AI tools enable miraculous product creation speed
- Small teams can now build what previously required massive organizations
- The barriers to initial success have collapsed
- But sustaining growth beyond $100M is harder due to AI-enabled competition
5. AI Is Already Eliminating Many Traditional Roles
Lemkin’s Business Transformation: SaaStr went from many employees to 5 people doing $25M revenue ($5M per person).
Roles Eliminated:
- Ghost writers: AI writes better content summaries in minutes vs. weeks
- Content reviewers: AI reviewed 300 speaker sessions better than human teams
- Designers: AI tools handle most design needs
- BDRs: “There will be no BDRs in a year”
- Sales screening: AI handles initial sales conversations
Future Predictions:
- 50% of sales and marketing teams gone in 2 years
- McKinsey already laid off 10% due to internal AI
- Mass unemployment coming to knowledge work
6. The Great Talent Retention Crisis
OpenAI’s Warning Signal: Only 60% employee retention over two years at OpenAI.
What This Means:
- If OpenAI can’t retain AI talent, traditional companies have it even harder competing for top AI talent
- AI engineers are the new gold rush prospectors
- Companies must treat AI talent “really well” or lose them
- Traditional retention strategies won’t work
Strategic Response: Companies need entirely new compensation and culture strategies to compete for AI talent, or they’ll be left behind.
7. Many of The New Generation Won’t Have Traditional Jobs
Lemkin’s College-Age Children Insights:
One kid:
- 10% of class didn’t want college at all
- Plan to move to Eastern Europe and make money online
- “Worst case, I’ll work for Airbnb remotely”
- Zero interest in traditional employment
Other:
- All want to go to graduate school to defer work reality
- More education-focused but still avoiding traditional work
Cultural Shift: This represents a fundamental change in work expectations and career aspirations, with major implications for traditional business models.
8. Content Creation Without AI is Dead
The New Creative Reality: Lemkin predicts no one will create content without AI going forward.
Current Examples:
- Higgsfield.ai: Creates movies from single screenshots
- Speaker promos: What took designers months now takes 10 seconds
- Video generation: Can create conversations between people who never met
Implication: Traditional creative roles must rapidly evolve to become AI collaborators or become obsolete. We’re already seeing this almost everywhere.
9. The $100 Billion Venture Bet
Investment Strategy Evolution: VCs now expect $100 billion outcomes per fund (vs. $1 billion historically).
Why This Matters:
- Justifies $60-100M seed valuations
- Assumes extremely high loss rates
- Only makes sense if you find the next OpenAI/ChatGPT scale winner
- Traditional venture math is broken
Lemkin’s Personal Strategy: “I’m in it for one” – seeking one $10 billion outcome with 10% ownership to generate $200M+ return.
Market Reality: This creates a bifurcated market where you either win massively or lose everything.
10. The Fog of War Opportunity
The Pattern Recognition: Similar to mobile and crypto transitions, everyone knows AI is huge, but no one knows exactly where the opportunities are.
Historical Context:
- Mobile: Obviously big, but winners like Uber looked nothing like previous web winners
- Crypto: Fringe belief, most missed it entirely
- AI: Consensus it’s huge, but complete uncertainty about execution
Current Challenge:
- Even working AI applications get disrupted quickly
- Models vs. infrastructure vs. applications – unclear where value accumulates
- “You know this is the time when all the money is going to get made… You still have no idea where to put it”
Strategic Approach: The smart money is either going all-in with high conviction or cashing out entirely, avoiding the middle ground of uncertainty.
Conclusion
AI has quickly transformed from tool to the beginning stages of replacement across virtually every knowledge work function.
SaaStr’s own AI demonstrates that we’re not just automating tasks—we’re creating digital entities that can outperform their human creators. The implications stretch from individual career choices to venture capital strategies, suggesting we’re in the early stages of the most significant economic disruption in modern history.
The key insight: those who embrace AI as a collaborative amplifier will thrive, while those who ignore it will become irrelevant faster than most anticipate.
