If every A.I. draft you get back feels polished, generic, and somehow not you, this episode names the actual problem, and it isn't the tool and it isn't your prompts. I'm Makeda Boehm. I've closed nearly $10 million in tech sales, and my entire business, a daily blog, this five-language podcast, my newsletter, runs on A.I. employees that sound like me because of one skill: context training.

Context training: teaching your A.I. everything it needs to know to do the job you're asking of it, aligned to what you actually need, and refined as you go, so the results get better, not just more like you. It works in any domain. I apply it to business: a living foundation that means everything your A.I. does starts from knowing you instead of guessing at you.

In this episode:
- Why two owners with the same A.I. tool get wildly different results
- The "brilliant hire with zero onboarding" test, and why generic output is an onboarding problem
- The four things your A.I. needs to know about your business
- Where context training sits next to context engineering and contextual intelligence
- Garbage in, garbage out: your business context is a dataset, and you own it
- Why blank A.I. gives you the average of the internet, and what accountable output looks like
- The one-hour decision that beats every tool upgrade

Who this is for: the service-based business owner who's collected prompts, switched tools, and still reads drafts that sound like a stranger.

Take the free AI Employee Report: eleven questions, about three minutes, and it names where your business is leaking money, time, or options, plus your first move. Take it at audit.seedandsociety.com/?src=podcast

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