
The Official SaaStr Podcast: SaaS | Founders | Investors
1mo ago·43m
SaaStr 856: AI-Native GTM 101: The 5 Decisions Every Founder Has to Get Right with Owner's CRO
Owner.com is approaching $100M ARR selling to independent restaurants and their GTM team is producing numbers that shouldn't be possible. $150K AEs closing $2M+ ARR per year. Outbound BDRs generating $100K in closed-won ARR per BDR per month. 4X the ARR per rep compared to direct competitors.
None of that happens by accident.
In this session, Kyle Norton, CRO at Owner.com, breaks down the exact AI-driven GTM playbook that got them there, including 5 decisions he believes every SaaS company needs to make right now before the gap between AI-native and AI-curious companies becomes impossible to close.
What you'll learn:
1. Centralized vs. decentralized AI: why letting a thousand flowers bloom is probably killing your results
2. Build vs. buy: the 5-question framework (hint: buy your infrastructure, build your intelligence)
3. The AI sophistication ladder — Levels 0 through 4, where most companies are stuck, and exactly how to move up
4. The "5 P" prioritization framework for deciding which AI projects to tackle first
5. Agentic vs. assistive: how to think about human-in-the-loop and why chaining too many generative steps is the #1 cause of AI slop
6. Why your personal compounding AI stack is your most underrated competitive asset
This isn't theory. This is what $100M ARR in a notoriously difficult SMB market actually looks like when you go all-in on applied AI.
None of that happens by accident.
In this session, Kyle Norton, CRO at Owner.com, breaks down the exact AI-driven GTM playbook that got them there, including 5 decisions he believes every SaaS company needs to make right now before the gap between AI-native and AI-curious companies becomes impossible to close.
What you'll learn:
1. Centralized vs. decentralized AI: why letting a thousand flowers bloom is probably killing your results
2. Build vs. buy: the 5-question framework (hint: buy your infrastructure, build your intelligence)
3. The AI sophistication ladder — Levels 0 through 4, where most companies are stuck, and exactly how to move up
4. The "5 P" prioritization framework for deciding which AI projects to tackle first
5. Agentic vs. assistive: how to think about human-in-the-loop and why chaining too many generative steps is the #1 cause of AI slop
6. Why your personal compounding AI stack is your most underrated competitive asset
This isn't theory. This is what $100M ARR in a notoriously difficult SMB market actually looks like when you go all-in on applied AI.
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