Becoming AI Native with Amir MXT

What does it mean to be truly AI (artificial intelligence) native? Amir MXT, co-founder of Humblytics, an AI native analytics and conversion optimisation platform, has built a career answering this question. 

Amir is no stranger to building businesses. His entrepreneurial track record includes two successful exits: SwiftPad, an ePrescribing and pharmacy OS whose IP was acquired by MedAvail in 2017, and Blackcreek, a design agency he co-founded and exited in 2020. He also held senior roles at IBM [IBM] Garage, where he built AI products for insurance and fintech companies, and served as Director of UX at Prospr by Sun Life, where he led the launch of a financial planning startup aimed at millennials. After adopting what he calls the “slo-mad” lifestyle – he currently splits his time between Bangkok and Toronto – he focuses on helping companies adopt AI tools at Humblytics.

In the latest episode of OPTO Sessions, Amir describes the work he does at Humblytics, plus the importance of accountability in an AI-driven world and how management can effectively scale AI adoption. 

Shifting Focus

During his time in the healthcare space, Amir came to realise that there was “a huge gap in being able to have deep industry expertise in healthcare and technology.” That experience eventually drove him to consulting. Teaching founders how to leverage the latest tools remains a central part of his workday. 

However, with the advent of AI, the work landscape is shifting. “At that time, our biggest leverage in building a great business was both industry expertise and human capital. That has changed.”

Now, when working with clients, he wants to use AI to expand options, not replace expertise. “I just want to show what is in the world of possibilities. And you as the expert, whether you’re a go-to-market expert, a paid media expert, can use these tools however you see fit to enhance and augment what you already do.”

The value of such experimentation is rapidly becoming clear, as AI tools offer a chance to scale both output and revenue, Amir says. “As the models get better or improve, you should almost see a correlation of the output of your company and the enterprise value as well – like a 10x value of that.”

Being the Human in the Loop

Keeping pace with the development of AI tools has required a shift in focus, Amir explains. First, with the debut of large language models (LLMs) like ChatGPT, “it started with having the right prompting techniques. Then it was around giving the right amount of context… And then giving the constraints that are required, the guardrails, the output, and access to tools.”

Both LLMs and AI agents – models capable of performing tasks autonomously – may be surprisingly capable, but going in blindly is not going to cut it, Amir admits. “If you’re automating this whole thing without really having full understanding of it and no visibility, I highly doubt it’ll be very successful.”

Accountability, a keyword in AI ethics, describes the importance of having a human involved in any AI process. Amir fully subscribes to this approach. “I would definitely always be involved in every single process because again, it comes down to accountability,” he says. “I’m responsible for the output here. I’m not going to have an agent fully go in and do everything end to end without me being involved.”

Deep experience in a given field and a rich understanding of AI tools are likely to be hand-in-hand for the high-value professionals of the future, Amir predicts. “I actually think we’re going to pay a premium for a lot of the expertise in this space.”

This union of expertise and AI proficiency is what Humblytics helps clients achieve. “We’re giving you the tools you need to get the work done, to save time you don’t need to be wasting. But we still are looking to your expertise and your industry knowledge to... stamp your name on it to say, I’m accountable for this, for this output and this outcome here.”

That way, the focus is not just on saving time, but also on improving outcomes. 

“It’s cool that I can create an email campaign or an ad campaign on Obsidian and use Claude Code and save all this time. But is it actually working? Is it saving me time? Yes. But is it making me more money?”

Building Sandboxes

The success of AI adoption on a company scale, Amir says, comes down to two factors: “company culture and enablement”. Rather than worrying about token usages or LLM licenses, management should be focused on examining where in their organization AI tools can be effectively tested. The question is, “are we giving people the right tools and resources to be able to learn how to actually use this? Are we enabling them to learn, and [providing] the sandbox… to actually play around with this?”

Red tape is another potential obstacle. Amir provides the example of a recent client. Even though he was able to build their website with AI tools, saving both time and money, the approval process proved to be the bottleneck. While oversight remains an essential step, Amir recommends that administrators “take away the friction to be able to enable your team members… to actually use these tools without having to go through the red tape.”

He also cautions against immediately rolling out AI tools company-wide. Instead, “find a very specific team. [Conduct] AI fluency benchmarks, where we look at the team that is going to be the most open to trying something new like this. Build a mandate around what AI will look like, assess… how they currently use AI, the problems they have and how they want AI to solve for it. And then just enable them to understand what is in the world of possibilities.”

Ultimately, a lot of Amir’s work comes down to showing teams what is possible with AI tools. His approach remains to “build something together and then give them the environment to go and build something afterwards. Success is… for them to be able to do something without my direct involvement.”

For companies that successfully pull off this approach, the sky’s the limit: “I truly think you can build $5m, $10m, $20m, even $50m-100m dollar companies being fully AI native with as few people as possible using these existing tools.”