Should I hire a fractional AI CTO?

Should I hire a fractional AI CTO? I was asked a version of this in an interview recently: fractional AI CTO versus full-time CTO, which should you hire? At the end the interviewer asked me to turn it into one simple question a founder could ask themselves to decide whether it’s time to bring in outside AI leadership. Here’s my answer. Can I see user outcomes increasing with my new features added, or am I still on a flat line, or even seeing a drop in retention of my product after shipping a significant portion of my application to production? That’s the entire question.

Below are the rest of my answers, organized around what people actually search for when they’re thinking about hiring a fractional AI CTO.

Should I hire a fractional AI CTO? The short answer

What are the signs you need a fractional AI CTO?

For instance, you have a prototype in production that, for some reason, feels cumbersome and overcomplicated. You try to code several versions. You notice quality issues. In production it fails, or it goes out of control. Or you might have an application, a good idea, a good concept, a good design, but this design doesn’t actually serve the user well. It becomes an ongoing issue.

You might have a product that feels like it’s working correctly with a small user group, or prototype-like, but it cannot scale to the full users or the full demand from the users. It cannot scale to the volume of the data. It cannot scale to the latency, cost, security measures, gaps, and so on. Maintenance over time is also becoming a factor. You need to actually engineer a system that is maintained well over time.

Sometimes the CTO doesn’t have enough expertise in that, or they focus more on building internal processes inside the engineering team than on these kinds of roles, addressing agentic and harness maintenance over time. That’s a different profile. And there are always new information gaps. You have a new model, a new harness technique, a new approach, and it’s hard to keep up. So it helps to work with someone who’s deeply connected and researching those things.

What’s the first signal to look at?

I think the user frustration, the outcomes they’re not getting. There might be feedback that the product feels fragile in production, or design inconsistency, or backend architecture inconsistency, or some inconsistency in user experience, when people notice that the AI product kind of feels AI-generated or sloppy. Any feedback like that should be a good signal that you actually need to hire a fractional AI CTO to instrument the process.

Is a drop in retention a sign you need a fractional AI CTO?

I think another signal is user retention. If you see a drop in user retention, or someone buys the subscription and cancels it after using it for one month, or cancels it immediately, that probably indicates the product seems useful as a package but doesn’t work internally. It has some obviously over-promised, under-delivered aspects in the production pipeline or in the features.

Those things are important, and so is the security aspect. You never know if you need a penetration testing team to test your product with adversarial practices for AI agents, or if you can use a fractional AI CTO to inspect your pipeline and see whether there are common practices and gaps for those use cases.

Fractional AI CTO vs full-time CTO: what’s the difference?

It’s like the comparison between a technical CTO and a research CTO, or a chief scientist. You don’t actually compete. You have different sub-roles, and you need someone with deep expertise in agents, not only someone managing the technical stuff. And it’s fine to have a CTO, or not to have a CTO at all on the project. More on how I do the role on the fractional AI CTO page.

Do I need a fractional AI CTO if I already have a CTO?

One concern is how to present this to the current CTO: that we’re going to hire some replacement of you to cover your functionality, because it seems like you’re not super confident in AI. I don’t like this claim at all. I think this role is a little bit different. A fractional CTO helps fill competence gaps that you usually don’t have, especially in AI and in building AI projects.

But if you have a CTO, there is a conflict: we have a fractional CTO, and a CTO who is making the final call on technical decisions. And usually it’s a battle. That’s a typical concern.

How do I tell my CTO we’re hiring a fractional AI CTO?

Frame it as: it’s not a competition. We’re not going to replace you with a new guy. We’re just hiring an AI partner to help you fill a gap where we need more production-ready experience and production-ready outcomes for the customer.

For instance, you don’t have the expertise and time to build, and sometimes you have a very narrow focus on a particular problem, solution, or design. If you can bring some fresh expertise on board, that can help you expedite and actually get outcomes that you don’t have. And it’s a good validation point for your system: some assurance that you’ve got the right direction for the product release.

How do you keep it from becoming a power struggle?

I think by understanding that it’s a collaboration. Usually it’s temporary cooperation, and there is no conflict in roles. It’s just additional expertise to help and grow and address certain points that need to be addressed as fast as possible: scale the company and the solution faster, bring more customers, satisfy the market, bring customer outcomes. It’s not about competing for the status quo and the role.

The guardrail is time boxes. It’s not a competition. It’s not a power struggle. It’s collaboration to deliver things to production as fast as possible.

Build vs buy: why bring in outside AI expertise?

There’s usually also a bias. It’s always a question of build versus buy. People want to build cool things in-house instead of buying them outside. But buying them outside could be much faster. I agree that it comes with a price, but sometimes it doesn’t matter. The price is a secondary factor. You need to have something in production, reliable and fast. I made a similar build-versus-buy point in how much it costs to build an AI agent.

Is a fractional AI CTO becoming standard?

I believe it’s going to be standard practice in a couple of years, or even in the next 18 months, for any VC-backed company to also have a fractional or full-time AI CTO working on their project, to fully capitalize on all the capabilities of AI and make sure you don’t produce a half-baked product.

Because with AI, the quality of products should actually go up. The speed is increased, but the quality gate also increased, because you see a flood of projects that are not fully functional. They can prove the intent, but they cannot deliver the satisfaction, the value for the customer. That’s the whole deal for the software industry.

How do I justify a fractional AI CTO to the board?

This is one of the open questions founders have. How do you present it to the board? Is it industry standard to have a fractional AI CTO? How do you sometimes justify the expense? These are typical concerns I hear.

Themes

So, should I hire a fractional AI CTO?

Ask yourself the question. Can I see user outcomes increasing with my new features added, or am I still on a flat line, or even seeing a drop in retention after shipping a significant portion of my application to production? If it’s the flat line or the drop, that’s the signal. How I run the engagement is on the fractional AI CTO page, and pricing is on the rates page.