Announcing AI Builders
A field journal for ops and tech pros building real-world AI systems
tl;dr:
I’ve started something new! It’s a blog about the ins and outs of building production systems with AI.
My belief is there is far too much hype about AI and far too little serious and practical content. So I’m hoping to remedy that by sharing what I’m learning.
Come along for the ride and check it out here if you’re in a hurry, or read on for the full story.
Why I’m focused on AI
You might have noticed a slight fixation on AI in my content this year.
I’m certainly not alone in that, but the pivot towards AI (at least for me) isn’t an attempt to jump on a bandwagon or get some extra clicks.
Automation has been a through-line in my career for nearly 15 years. Ever since I got my first Marketo instance, I’ve been giddy about the raw power it gave a humble English major like me.
The design and mechanics of automated systems seem to fit my brain naturally and intuitively, in a way that few other topics do. And every time I’ve felt truly in a flow state—seeing the landscape with elevated clarity—it’s been during major systems work.
Fast forward to today, and LLMs have utterly transformed the scope of what’s possible for automated systems.
I’m by no means an AI hype-maximalist (you can see my reservations on display in this piece, the first thing I published on AI). And if anything, my concerns about AI have only grown over the past two years: concern about whether it weakens us psychologically, whether it will be a cause of social disintegration, even whether it will lead to catastrophe.
At the same time, I can’t deny the sheer childlike, magical joy I feel working with AI systems. Not lazily outsourcing my thinking or serious effort to LLMs—but dialoguing with them, exploring ideas with them, occasionally wanting to throw something at them, and experiencing their oddly-endearing quirks of personality.
Even though I know at heart that they are “merely” highly-sophisticated text-prediction machines, I continue to marvel that such a technology exists and that I’m alive to see it. It’s the kind of feeling that a person from the 15th century might have if we suddenly placed them in an airplane, looking out over the cloud canopy.
All this is to say: I feel convinced that building agentic AI systems is going to occupy much of the next act of my career. It’s work I feel very well-suited for and work I feel overwhelmingly drawn to do.
Why I want to write about AI
The first reason is that AI is so new and unfamiliar, so working with it inevitably leads to a series of novel revelations and new insights. And I enjoy sharing things I’m learning about—it helps me crystallize and clarify my own understanding.
At the same time, I feel the state of knowledge about AI is very dire right now. There is water, water, everywhere, and not a drop to drink.
Most AI content I come across falls into one of three buckets:
Deeply technical newsletters for AI PhDs—fascinating, but often a degree or two removed from the problems I face.
AI news round-ups—helpful for staying current, but not much use when architecting real systems.
AI hype-posting—those viral org charts of 27 agents saving 1,000 hours a week…with no receipts.
It’s this last category of content that I actually feel is very toxic and harmful to our profession. It inflates expectations about what AI can do and delegitimizes AI when those expectations go unfulfilled.
I’ve always taken my craft as a technologist seriously, and any kind of snake-oil peddling only cheapens that craft.
I’m also seeing very little content aimed at me —a technical systems/operations person tasked with helping lead “AI transformation” and building robust systems for internal users.
No one seems to be talking about the hard, gritty, and often frustrating work of designing, testing, and scaling internal AI applications—the kind that actually work day-to-day, not just in demos.
There’s clearly a gap, and I’d like to help fill it.
I don’t have any aspirations to be an AI “influencer” or “creator.” I just want to share and learn from other people who are figuring this stuff out. If that’s you too, then I hope this becomes a space where we can learn together.
Why I’m creating a new blog to do it
I briefly considered just evolving my content strategy for RevOps FM. But while RevOps certainly overlaps with AI, it doesn’t really make sense to focus solely on one topic.
I could also rebrand RevOps FM, but I don’t think it would be right. I feel a modest but sincere satisfaction in the body of knowledge I’ve helped create / curate with the RevOps FM podcast and articles. It’s become one of the most recognized podcasts in its niche, and I want it to continue to be a resource for that community.
Therefore: a new publication is the way to go.
AI Builders will be that new publication. It’s meant as a field journal for ops and tech pros building real-world AI systems for internal use (as opposed to AI PhDs building LLMs or AI product developers creating commercial products).
I believe we are an under-served audience. Hopefully we can remedy that.
At the same time, I wanted a space where I could safely make no particular promises about content frequency or length or level of polish.
One of the challenges I’ve had with RevOps FM is the amount of time it takes to create quality content. I burned myself out last year publishing weekly episodes, and feel persistent guilt about the content I’d like to write but don’t have time to.
So I’d like a space that’s appropriate for short, informal, practical and tactical content that I can write quickly. If I can write a post in 20 minutes about something I just learned, and it means I actually post it, then I’m doing more good than waiting until I have 10-15 hours to cover a topic definitively.
I’m thinking of the content on AI Builders as akin to informal notes from the field—dog-eared and smudged, but hopefully valuable.
How to subscribe to AI Builders
I very briefly considered the idea of importing my entire RevOps FM subscriber list to the new blog. I have over 2,200 subscribers here, earned through a lot of hard work over 2 years.
However I quickly knew that wouldn’t be right. You signed up for RevOps content, and I value the gift of your attention too much to abuse it.
This being said, I hope you’ll subscribe to AI Builders as well if I’ve earned your trust and if you share my interest in the topic.
You can also be a contributor
I don’t mean to be a one-man band on this and would very much welcome contributions from other people doing this work.
I don’t have formal contributor guidelines set up yet, but if you are a practitioner who is building production-grade AI systems (not just demos) for internal use and has insights to share, just reply to this note.
What’s next for RevOps FM?
It’s not going anywhere—the show goes on. But it will likely stay at the more relaxed frequency you’ve seen this year. I’ll continue to add to this space when there are new topics that seem important to cover.
Thank you!
Just a note to say thank you for all the support, encouragement, and appreciation I’ve received over the past few years. It means a lot to me, and I likely wouldn’t feel as motivated to share things if it wasn’t for that.
👉 Subscribe at aibuilders.blog, or drop me a note if you’re building in the trenches too.