Your Developers Got Faster With Agents. Your Team Didn't.
Faster developers don’t automatically make a faster team. We built Tiller to give people and coding agents a shared plan, clear checks, and a human at every merge. Now it’s open source.
Faster developers don’t automatically make a faster team. We built Tiller to give people and coding agents a shared plan, clear checks, and a human at every merge. Now it’s open source.
An AI workflow can save time and still need a person to check it. Letting go of those checks takes evidence about the agent's mistakes, what they'd cost, and the work people are still quietly doing.
The TLDR: faster coding only shortens a project when coding is what's holding it up. Once work is delivered faster than people can review, test, accept, or make
Your first AI pilot probably won't need every data problem fixed. Work out which ones would get in its way, and how you'll know when you've done enough.
Your business has changed before, and it has had to keep working through every change. Start there when deciding what to do with AI.
The machines automated everything in the job description. Four things survived, and they were never in the job description to begin with.
Every shadow spreadsheet marks a spot where the sanctioned systems stopped serving the business. Before you replace them, read them. They're the most accurate requirements documents you own.
You inherited 4 ERPs along with the trucks and the buildings, and the board wants one view of the platform by the first quarterly meeting. Consolidated reporting doesn't require consolidated systems; a shared data layer above them delivers visibility in weeks, not years. Consolidate later, or never.
If your teams build software with AI agents, you're already running a production system. The question is: did anyone actually design it?
A test verifies that your code does what the test says. An eval verifies that your system does what the user actually needs.
Turning intent into syntax was the expensive part of software, and the entire industry is shaped around that assumption. Agentic AI is collapsing the translation layer, and engineers are migrating up a level, from writing the code to deciding, describing, and judging what it should do.
Integration debt is the cost accumulated between systems when decisions are made without enough information, made rapidly when pacing is more important, or when constraints force your hand. It isn’t in itself a bad thing, but it is limiting. Here's how to measure it and begin paying it down.