Halliday: AirOps Built Nights and Weekends for Nearly Two Years Pre-Funding
“We actually incorporated the company during the pandemic, and I was building with my co-founder for a full Almost two years before we raised any money, and this was nights and weekends, tugging ideas, playing with things”
Halliday: Sam Altman Convinced Him to Explore LLMs Pre-ChatGPT
“So I was Talking to Sam Altman before ChatGPT was a thing. And I said, like, hey, what's got you excited at the moment? Or some like vague question like that. And he, he's like, the AI stuff's getting really good. And I had no frame of reference for LLMs.”
Halliday: Building for high-taste users is the best way to achieve excellence
“One piece of advice is like build against the high taste user and they will like keep rejecting you till you pass that very, very kind of established extra criteria for a problem. And it's the best way in the early days. To get really good at something in my v…”
AirOps mentioned its investors in cold outbound to book early calls
“What worked for us at the very, very beginning was, this is a bit of a cheat code for us, was we mentioned our investors in the outbound to get people on the phone.”
Halliday: 70% of AirOps usage is content creation and refreshes
“About 70% of what people use air ops for is a combination of content creation and refresh sort of operations.”
Halliday: AirOps has a 40-person team supporting brand content workflows
“We have a team of about 40 people who just work with brands all day long to sort of do those use cases, albeit generation eight of those, given how much the market has changed.”
Halliday: Effective AEO requires structuring content to spoon-feed answers directly to LLMs
“There's best practices around structuring that content to make sure you're basically spoon feeding those answers to the models and preparing them for citation. Cause ultimately you want to be quoted a nice big paragraph in a chat GPT response saying on the pro…”
Halliday: AirOps Ingests 1.2B Answer Engine Responses Every 60 Days
“We collect almost 1.2 billion answers every 60 days from these answer engines, and we analyze them.”
Halliday: AirOps founders reached $1.3M ARR doing all selling themselves
“My co-founder and I got us to about 1.3 million in ARR selling ourselves.”
AirOps grew from $1M to $13M ARR in under two years
“We got to a million in Q one of 20, 24, and then we hit 10 in 20, 25. That was kind of a big ramp for us. We actually hit 13 in Q four of 20, 25.”
Halliday: Startups should hire two initial salespeople, never just one
“So first two in, there's some competition between them, right? So that's good. You don't want just one because you have no point of reference.”
Halliday: AirOps enterprise deal ACVs range from $60K to $250K
“Enterprise sales. So ACVs are like 60 to two 50, right? It's big. It's like a big range.”
AirOps converted all but two enterprise pilots to annual contracts last year
“We actually, last year, I think we had all but two pilots convert to annual, which in the world of AI is actually insane.”
Halliday: Enterprise AI software buyers now run sophisticated RFPs and bake-offs
“In our space, for example, a year ago, people had no idea how to evaluate A tool like ours, to be honest. And now we get people showing up with really sophisticated RFPs and different evaluation questions, and they want to try the product. They want to do bake…”
Cabane: Modular multi-agent prompts outperform monolithic prompts for content creation
“That is a much better way To create content, then have a huge prompt that tries to do everything, because it tends to fail when you do that. And so we try to break it down, we store the data in Airtable, and then we feedback the data from Airtable into the fin…”