Owen Carter

Whenever I start a session in a large monorepo the agent automatically indexes or pulls in context from unrelated microservices. Suddenly, it starts suggesting patterns or types from a completely different service that shouldn't even be communicating with the current module.

The broader the context window gets, the more "cross-contamination" happens in the suggestions. How do you effectively curate or prune the file context before handing off a task to an agent?

I've been thinking about this a lot lately, especially working on AINA.

Even a few years ago, job hunting meant tailoring your resume manually and preparing for interviews mostly alone (or with a friend, or sometimes a coach if you were ready to invest).

Now AI is everywhere in the process. Candidates use it to rewrite resumes, practice interviews, and figure out why their applications aren't landing. Recruiters use it to screen resumes, write job descriptions, and even run first-round interviews.

Ours was simple. We priced for the Fortune 500 budget. Leads were coming in, interest was real, but deals kept dying. Took us months to understand why.

CFOs treat new marketing experiments like a rounding error on their total spend. If your price tag is bigger than what they mentally allow for "let's try this," the deal dies in finance, not in the sales call.

We launched a second brand at credit card swipe pricing instead. Same service, different lane.

What was your pricing mistake?