About Mug

My AI pill took time to digest.

I didn't want AI writing for me, and I didn't want it doing my work.

But for as long as I can remember, when I found myself in the middle of monotonous, un-creative, "just gotta get this done" work, I'd feel this brain tickle — "there has to be a way to automate this".

A decade ago, I stumbled into low-code software. Tools like Airtable and Zapier let me automate away busywork and build systems around how I wanted to work.

Then AI hit. And I didn't get it — copy-pasting in and out of a chatbot?

Then coding models got good. Suddenly anybody could build software from scratch to do anything (including me).

I dove in. I spent months talking to Claude more than friends and family (still true, sadly).

I studied the online AI hype cycles. Turns out, lots of people were drinking the kool-aid. But with each week's fresh round of "This changes everything" hysteria, I had a realization — none of this was trickling down to real businesses.

Real businesses stand to gain the most from AI. They have lots of real people, doing lots of real, operationally-complex work, every day. They don't need (or want) to "change everything". Their software and processes work. But they know AI is coming for us all, whether we like it or not. It's "AI or die" for every business.

They also know that integrating AI into their business is going to be slow, painful, and expensive. Most of them never even got around to integrating automation tools like Zapier, Make, and n8n for the same reasons.

Around the time I had my realization about this "real business" AI gap, the trend of "headless" software was emerging — the idea that people no longer need to click through an app, they just tell AI what they want, then the software and AI work together to make it happen behind the scenes.

This got me thinking — real businesses need AI, but they also want minimal change. They only want AI and automation in the right places, and their team doesn't want another app to learn. The headless concept actually made a lot of sense for this...

So I started sketching out how I'd do it:

1. Sync data from any API into AI-native SQLite
2. Code automations in TypeScript to run on schedule or automatically as data changes
3. Deploy custom agents with SOUL, skills, tools, & persistent memory, running models from any provider — Anthropic, OpenAI, Google, xAI, Meta, DeepSeek, etc.
4. Send headless web interfaces via email, SMS, & Slack when humans need to be in the loop: forms, portals, dashboards, etc
5. Wrap it all in a CLI kit so Claude Code, Codex, & Cursor can drive it

A vibe coder could build everything a business needs to enable AI-native workflows, without changing that company's tech stack at all.

Fast forward months of building, and Mug was born.

Now I'm on a mission to roll out AI automation to as many "real businesses" as I can.

If you've read this far into my missive, I sincerely appreciate it.

If you have any thoughts, questions, or suggestions for Mug, please email me, message me on LinkedIn, or open an issue on GitHub. I read and respond to everything personally, ship updates daily, and am happy to do demos.

—