If you were forwarded this newsletter, and you'd like to receive it in the future, subscribe here.​

​Things that Used to be Impossible, but are Now Really Hard​

Kevin Scott, CTO of Microsoft, framed the opportunity in AI this way : work on problems that used to be impossible, but are now really hard.

My immediate reaction : what technical problems are now possible but still hard? What can computers achieve by themselves that two or three years ago would be intractable?

But, this point isn’t purely about technical innovation.

What business problems are newly solvable?

Nearly 10 years ago, I wrote a post about the minimum viable average contract value to justify a sales team. Most companies typically hire account executives & development reps at $15k or greater in contract value because the economics of lower ACVs aren’t viable for most.

Imagine a product offerd at a $10k contract value sold by an AE. The on-target earnings of the salesperson might be $120k. To break even, this team would need to book 12 contracts per year or one per month. But most sales leaders operate their GTM teams with a 4-5x ratio between sales costs & quota. In this case, this team would need to book $480k or 48 contracts per year - 1 per week. For most products, this is extremely difficult, bordering on impossible.

AI-based sales development changes the economics of this calculation. If AI can reduce the overall cost of sales, the minimum viable ACV drops.

Assume an account executive can close two transactions per month without AI but AI improves productivity by 50% (similar to coding productivity gains from copilots.) ACVs remain the same. The team operates at a 3x ratio of on-target earnings (OTE) to quota.

It’s tight, but the economics work for a sales team to engage with a $10k ACV product.

There may be a compounding effect. Assisted sales from freemium/PLG typically convert at 15% compared to unassisted sales at around 2-4%, a 5x+ improvement in yield.

This hypothetical demonstrates a GTM motion that used to be impossible but is now really viable (& hard). Executed properly, this strategy could become a competitive differentiator in a market segment, enough to win disproportionate market share.

AI has the potential to change the unit economics of a business, expanding addressable segments with better efficiency.

​