You standardized your sales tools years ago. Now your competitors are doing the same with AI development—and measuring what you can’t.
The Disaster You Already Prevent in Sales
Your top AE—the one closing $5M deals—didn’t pick Salesforce. Your CRO did. That rep adapted in two weeks and got back to selling.
You did this because the alternative is catastrophic.
Imagine New York runs Salesforce. London runs Hubspot. Remote reps insist on Pipedrive. Enterprise hunters built some Airtable thing they swear works.
You can’t forecast. You can’t identify why London closes 30% faster than New York. When your board asks “what’s our sales cycle?” you can’t answer because everyone tracks differently.
You can’t replicate what works. You can’t scale what’s working. You can’t even see what’s working.
Someone wants to use a legal pad and Rolodex? Tell them 1975 wants its process back.
Sales is a system. You standardize so you can measure. You measure so you can improve. You improve so you can scale. This compounds organizational learning quarter over quarter.
This is obvious in sales. You do it without thinking.
The Disaster You’re Creating in Engineering
AI-augmented development follows identical physics. High-leverage professionals operating AI agents to produce business outcomes. You need to measure output quality, cycle time, and cost efficiency across teams.
Let every developer pick their own AI platform? You just recreated the Hubspot/Salesforce/Airtable nightmare with code instead of deals.
Your competitors standardized six months ago. They’re measuring what works, killing what doesn’t, and iterating weekly. They’re compounding organizational learning while you’re comparing apples to oranges across fifteen different toolchains.
They’re pulling ahead. Permanently.
What This Actually Means
Your best developers will adapt to excellent tools just like your best AEs did. Two weeks, maybe three. The ones who won’t are optimizing for personal comfort over company outcomes.
That’s not senior talent you need to retain. That’s a performance problem wearing a hoodie.
Stop treating tool selection like a perk. It’s a strategic decision that determines whether you can measure, manage, and scale your AI development capability.
Your sales organization figured this out in 2005. Your engineering organization needs to figure it out by Q1.
The companies who move first will be measuring and improving while you’re still debating. That gap doesn’t close. It widens.
Engineering leader who still writes code every day. I work with executives across healthcare, finance, retail, and tech to navigate the shift to AI-native software development. After two decades building and leading engineering teams, I focus on the human side of AI transformation: how leaders adapt, how teams evolve, and how companies avoid the common pitfalls of AI adoption. All opinions expressed here are my own.