Why I picked this
The SaaS is dead, the SaaS is going to rebound argument well encapsulated in a revops reddit thread
ai-coding-toolsback-to-basics-gtmautomation-stacks
“RevOps teams are vibe coding replacements for $18/month tools with uncapped Claude budgets, completely ignoring the time cost and quality degradation”
Key takeaways
- RevOps teams are misallocating resources by building AI-powered replacements for cheap SaaS tools, ignoring total cost of ownership including AI API costs, engineering time, and quality degradation
- The 'uncapped Claude budget' approach represents a new form of technical debt where teams optimize for visible SaaS line items while creating hidden costs in maintenance, bugs, and user friction
- This represents a broader pattern of AI tool misuse: teams are treating coding assistants as cost-saving measures rather than productivity multipliers, leading to false economies that burn more value than they save
Why this matters for operators: RevOps leaders evaluating build-vs-buy decisions in AI era; CFOs tracking hidden AI costs
I cover AI×GTM intelligence like this every Wednesday.
Get STEEPWORKS WeeklyMore picks
AI DevelopmentLenny's Podcast
Humans will keep inventing new reasons why we must stay in the loop with agents
- Human resistance to full AI autonomy is not purely technical—it's psychological and organizational; companies will rationalize keeping humans in decision loops even when agents are capable
- The 'human-in-the-loop' requirement may become a self-perpetuating narrative rather than a genuine necessity, driven by organizational risk aversion and change resistance
- Product leaders at scale (Notion) are observing this pattern, suggesting it's a widespread phenomenon across enterprise AI adoption, not isolated to specific use cases
ai-agent-adoptionhuman-in-the-loopai-governance
GTM Ops**RevOps Impact (Jeff Ignacio)
Comp plans for consumption pricing
- Consumption pricing fundamentally breaks traditional SaaS comp models—requires rethinking sales incentive structures around usage vs. contract value
- Four distinct contract structures exist (pay-as-you-go, uncommitted, committed, hybrid), each requiring different compensation mechanics and sales behaviors
- Enterprise consumption-based deals create tension: customers want flexibility, sales teams need predictability for quota attainment—comp design must bridge this gap
revenue-platform-consolidationconsumption-pricing-modelssales-comp-design
AI×GTMGTM OS: The Future GTM Operator
3 revenue motions your AI is only half wired into
- Model parity has arrived: OpenAI/Claude now trade evenly on core tasks, making 'better AI' a non-differentiator—the edge shifts to integration depth into existing revenue motions
- Waste is quantified: teams paying $17K-$37K/month for AI seats that never touch pipeline generation; real cost is opportunity cost of unused capacity, not subscription fees
- Lean teams have a structural advantage: cannot out-buy larger competitors on model access, but can out-embed them by wiring AI 1 revenue motion deep (pipeline → content → deals) with proprietary deal context competitors haven't seen
ai-sdr-adoptionrevenue-platform-consolidationback-to-basics-gtm
This analysis was produced using the STEEPWORKS system — the same agents, skills, and knowledge architecture available in the GrowthOS package.