by Tyler Kelley
Eight weeks ago, I started talking to my computer the way I’d talk to a new employee. Not typing commands. Not writing code. Just explaining what I needed, the same way I’d explain it to someone sitting across from me at the office. The computer started remembering.
That sounds like science fiction, but it’s the most mundane kind of automation. I wanted a system that could recall every detail about my clients’ brands, their voice, their positioning, the specific phrases that land with their audiences. The kind of institutional knowledge that usually lives in one person’s head and walks out the door when they leave.
So I built one. Not by hiring a developer or buying enterprise software. I built it by having a conversation.
The system I use now holds 248 curated quotes from books I’ve read, a hundred and ten of my LinkedIn posts with performance data, and detailed brand profiles for every active client. When I sit down to develop strategy, it already knows the context. It remembers what worked last month. It can pull a quote from a branding book I read two years ago and connect it to a client’s messaging challenge, because I taught it to.
The conventional wisdom about AI in small business goes like this: it’s coming, it’s important, and you should probably hire someone who understands it. Every conference, every webinar, every breathless LinkedIn post says the same thing. AI is a technical problem that requires technical people.
Except it isn’t. Not anymore.
The tools available right now, not next year, not in some beta program, let a business owner build custom automation by describing what they want in plain English. No code. No IT department. No six-figure implementation budget. The barrier to entry has dropped so far that the main obstacle is no longer skill. It’s belief.
Here’s what actually happened when I stopped thinking about AI as a technology project and started treating it like a conversation. I identified the task I was doing most repetitively. Pulling together client context before writing sessions. I described that task to an AI tool the way I’d describe it to a sharp intern. Then I asked it to remember what I told it.
That’s it. That was the whole implementation plan.
The system grew from there. I started adding book quotes I wanted to reference in my work, not dumping them in, but curating them with notes about why each one mattered and when it should come up. The AI became a librarian for my own thinking. When I write about organizational dynamics, it knows which Drucker passage I’d reach for. When a client needs messaging about resilience, it pulls a quote I’d marked three months earlier.
A McKinsey study from last year found that sixty-five percent of companies had adopted AI in at least one business function, up from thirty-three percent the year before. But the same study found that most of that adoption was concentrated in large enterprises with dedicated AI teams. Small businesses, the ones with the most to gain from automation, were being left behind. Not because the tools didn’t exist, but because nobody was explaining these tools in language that made sense.
The email system I built works the same way. Incoming messages get categorized, summarized, and routed without me touching them. Priority items come first. Follow-up reminders generate automatically. Before this, I spent forty-five minutes every morning sorting through an inbox that looked like everyone else’s. Urgent mixed with trivial, important buried under noise. Now that time is close to zero.
I didn’t write a line of code for any of it. I described what I wanted, tested it, adjusted, and described some more. The process felt less like programming and more like training a new team member who happens to have perfect memory and no limit on patience.
Everyone’s asking how fast AI can do the work. The better question is whether you’ve ever sat down and defined what the work actually is. Most business owners haven’t, because the work has always been whatever showed up that morning. AI doesn’t fix chaos. But it does make you describe the chaos precisely enough to find the pattern inside it.
Tyler Kelley is the Co-founder and Chief Strategist of SLAM Agency, helping organizations use AI to build visibility, strengthen relationships, and equip teams to deliver results that matter in an AI-driven future.