Principles I work by
There are seven. Each one points to work you can see somewhere else on this site.
I try to leave a system behind after every campaign.
When a campaign ends, what it taught you goes with it unless you've built something to keep it. I judge a quarter by what got added to the system that keeps running.
I show how every number was measured.
That includes the numbers on this site. A big number with a vague method eventually blows up in a QBR, so I'd rather show the math up front.
I write the playbook down before asking for headcount.
Two of us run ten or more concurrent lifecycle programs because the standards, checklists, and prompt libraries are written down where anyone can use them. Once the playbook exists, the headcount ask usually gets smaller.
I put guardrails in before AI touches the work.
Our prompt libraries, QA checklists, and governance were in place before any AI touched production work. AI speeds up whatever process you give it, including a bad one.
If nobody has time to build it, I learn enough to build it myself.
When design and engineering were booked, I taught myself HTML and CSS and shipped the pages. That's also how I ended up building a voice agent, an automation stack, and this site.
I treat the sales handoff like a product, and sellers are the users.
Speed to lead, routing rules, and the one-click outreach library are its features. Sellers use those things when they live where they already work, so that's where I put them.
I take things apart to understand them.
That goes for cars, martech stacks, attribution models, and chicken coops. Once I know what's inside, I can fix it myself when it breaks.