About Kyle
Awfully Helpful is one person: me. I help small businesses get real work out of AI, and I help cities make their websites easier for everyone to use.
Hi, I’m Kyle
I served on active duty in the US Army. Since then I’ve worked in IT, in federal IT and in workplaces with strict rules about data. I like making complicated things easy to understand, and leaving people with something they can actually use.
These days I spend a lot of my time on AI: building helpers, testing tools and finding out what really works. I started Awfully Helpful because I like being useful, and I like plain words.
When I’m not at a keyboard, you’ll find me training for amateur strongman, enjoying a good movie on the home theater, or out on a hike.
Yes, the name is Awfully Helpful. The “awfully” is the good kind.
Things I’ve built
A few real projects, and what the same idea could do for a small business.
A team guide that answers back
At a past job, I pulled scattered documents, how-tos and know-how into one guide that the team keeps up to date. People read it directly, and their AI tools search it and point back to the source.
For a small business: your how-to binder, except you can ask it a question.
AI helpers with one job each
I run my own AI helpers. Each one has one clear job, like a short summary of the day every morning, and a person checks its work.
For a small business: a helper that drafts your weekly update or sorts new requests, while you stay in charge.
Security training for 991 people
At a past job, I ran security training and a practice phishing test for a whole organization. I learned how to teach busy people new habits without a boring lecture.
For a small business: a friendly training session on your AI rules that people actually remember.
A report that sorts what to fix first
An automation that turned the software list from more than 1,300 computers into a short list of what to fix first. A cleaned-up version is free on GitHub: the Fleet CVE Scanner.
For a small business: a long, messy list turned into a clear next step.
Voice notes into summaries
An app I use every day. I talk, and it gives me a searchable transcript and a short summary. Private notes stay on my own computer. See Stellar Notes on GitHub.
For a small business: call and meeting notes, written up for you.
This accessibility check
My city checks run on tools I built: browser probes, a real screen reader, and two AI judges from different vendors. I read every finding myself.
For a small business: AI does the legwork, and a person makes the call.
How I think about AI
Start with what you know, not the chatbot
A chatbot can’t fix an out-of-date how-to or a question nobody owns. So I start with your real information: where it lives, and who keeps it current. Then AI can help, and its answers can point back to a source.
Give an AI one job, then make it dependable
“Help with everything” is hard to test. “Draft a reply to this kind of email” is easy to test. I start small, check the real results, and grow it only when the small version works.
A person stays in charge
AI drafts, sorts and summarizes. You decide. Every plan I write says where a person checks the work.
I also help Minnesota cities
A city website is where people pay a water bill, find a council agenda or apply for a permit. When a page doesn’t work with a keyboard or a screen reader, some people can’t do those things on their own.
Most of those problems are fixable. So I write every finding in plain words, for two people: the person who approves the bill, and the person who fixes the site. I confirm every finding before it goes in the report.
Let’s talk
A stubborn task, a question about AI, or just a good reason to compare notes. I’d love to hear from you.