3 Takeaways from All Things AI: 80/20 Rule, Non-Deterministic Humans, and Why We're Still Early

Last week, I attended All Things AI in Durham, NC. The event was geared toward technical AI practitioners with workshops on Day 1 and standard conference talks on Day 2. A few takeaways from the conference are below for y'all!

MLH AI Roadshow

On Day 1, I helped Major League Hacking (MLH) run an AI Roadshow. We're hosting about one of these a month right now. Some are standalone events. Others have been at partner conferences. I think you'll see us again at All Things Open in the fall.

At the AI Roadshow, we run ~6 practical, hands-on-keyboard activities. You walk up and use a ready-to-go laptop to learn a new skill or technique with AI. We typically have snacks, drinks, and networking throughout the events. If you want to keep an eye on the next stop, check out our Luma.

The 80/20 Rule in Practice

(Inspired by Justin Jeffress: Vibe Coding in Action)

I enjoyed Justin's whole talk, but he had a specific slide on the 80/20 rule that is still sticking with me. AI feels really good at getting you 80% of the way there on most problems.

What do you do with that remaining 20%, though? Justin's advice was to simply repeat. Send the "remaining" 20% back to your AI tool of choice.

I've been doing this myself for a while with coding agents, but this talk has me thinking again about the effectiveness of simple loops and repetition. I imagine this advice hasn't penetrated to folks who mostly use AI through chat applications. It might also not work as well for outcomes that can't be tested. But the framing really resonated with me.

Humans Are Also Non-Deterministic

(Inspired by Calvin Hendryx-Parker: Orchestrate Agentic AI)

Through my work at MLH, I'm constantly talking to software developers. The last ~18 months have been even more intense, driven by all the AI development.

A common concern I haven't felt ready to address is that AI tools are non-deterministic. I get it. When you're writing code, you're building for specific outcomes. I think devs like the certainty.

Calvin made a small comment during his talk, reminding the audience that humans are also non-deterministic. The observation really hit home. I knew this. I'm sure you know it, too. But it was a good reframe. Process-driven thinking and guardrails feel suddenly important.

We're Still So So Early

(Just a personal reflection)

Like many of you, I've been following AI heavily recently. It's been important for the work I'm doing at MLH. It's so easy to get caught up in the fad-of-the-week on Twitter. But the reality is that most people still aren't leveraging AI tools. Especially not to their maximum capabilities.

Even at a conference for AI practitioners, I met people who hadn't used a coding agent. There were jokes about OpenClaw and Mac Minis, but not everyone was "in the know".

We're still so damn early in this wave of change. No time like the present to roll up your sleeves and give something a try yourself. I still think learning by doing is the right methodology with AI tools.

Happy hacking!