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  • Startup Life: Unscripted #44 with Anton Eremin, Founding Forward Deployed Engineer at Athena Intelligence

Startup Life: Unscripted #44 with Anton Eremin, Founding Forward Deployed Engineer at Athena Intelligence

Anton shares insights from his journey from quantum physics to leading AI startups, focusing on the importance of adaptability and problem-solving.

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Startup Life: Unscripted is a TNG Media newsletter, as part of The Nudge Group, where we feature candid conversations with startup operators about their career journeys and experiences. If you received this email as a forward, you can read all our past interviews and subscribe right here.

Welcome back to Startup Life: Unscripted! In this week’s edition, we’re excited to introduce Anton Eremin, the Founding Forward Deployed Engineer at Athena Intelligence, the developer of Olympus, an AI-native analytics platform.

Anton has a unique background, making the leap from quantum physics to driving innovations in AI and data science. In our conversation, he shares his fascinating transition from studying quantum physics in Russia to working in tech startups.

Key interview takeaways:

🔍 Problem-Solving Mindset: Anton discusses how his background in quantum physics helps him tackle challenges in tech.

🚀 Startup Journey: He talks about moving from academia to startups, emphasising the importance of adaptability and customer focus.

💡 Innovation in AI: Anton explains how Athena Intelligence stays at the forefront of AI and data science.

📈 Growth and Scalability: He offers insights into managing growth, scoping product values, and staying agile.

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Anton, you've transitioned from quantum physics to leading tech innovations. What was that like, and what drew you to the startup world initially?

I grew up in Russia, where technical education is deeply rooted in maths and physics. Prestigious universities often focus on niche specialties like Quantum Electronics or Superconductor Materials.

My major was intense with lab work. After two years of "universal" maths and physics, the curriculum progressed towards domain-specific subjects where I quickly learned that hardware wasn't for me, and robust science felt too narrow.

Many alumni from my university became renowned startup founders or tech leaders, which piqued my interest in tech. I also had a fleeting interest in consulting, so the business aspect of tech felt natural. In the mid-2010s, with the rise of the UX movement, I started as a UX designer and later transitioned to PM roles.

That’s quite a journey! Do you think those early experiences with such a rigorous education shaped the way you approach problems in the tech world today?

The exposure to both foundational STEM curriculum and customer-centric roles gave me an outlook on product development that I still find valuable today.

I didn't feel completely isolated from the R&D and academia side of tech progress — for instance, skimming through AI papers and reminiscing about the university days when I had to multiply matrices by hand is always fun.

Yet, being focused on solving customer needs for most of my early tech days made me very aware of the fact that product adoption rarely has much to do with technical excellence (past a certain threshold anyway).

Applying state-of-the-art algorithms and technologies to the problem at hand is exciting, but until there's a clear signal from a customer, I'm not putting extra engineering cycles into this problem. Building something people want means not overbuilding anything you don't know people want.

From Yandex to launching in new markets, and now at Athena, you've been through some intense growth phases. Could you share a couple of standout moments or lessons that you learnt along the way?

Intense growth phases mean more demand than the team is used to, leading to fewer time resources and more priorities. It's the most demanding period because you have to meet expectations quickly while focusing on about 30% of the issues and opportunities.

Most of the pressure comes from yourself and your team. A crucial lesson is to scope down the core value of the product and be ruthless in communication and setting expectations. 90% of problems aren't problems if you set expectations right.

Starting something new always comes with its set of challenges. What were some of the hurdles you faced in the early days at Athena, and how did you tackle them?

Returning to a small founding team after leading a 300-person team required a mindset shift. Planning execution and squeezing 20% more output from most projects isn't beneficial.

It's better to get multiple things done quickly rather than perfecting one thing. You're more nimble and flexible, focusing on brokering possibilities and identifying strong product signals.

One valuable lesson was spending hours on something only to realise it wasn't what the customer wanted. This taught me to prioritise agility until we gain clarity.

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How did you adapt your leadership style when moving from a large team to a smaller, more agile team? Was there a particular moment when you realised you needed to shift gears?

I was fairly happy to step down into a hands-on mode. When you're working in a small, early-stage team, there's nobody to delegate to and no upside in crafting a mid-term vision and roadmap.

I had that realisation pretty early on when a few capability items I was very excited about were abandoned because we didn't get a strong signal from the market on any of them.

Also, in a small team, your leadership applies mostly to yourself, to hold the execution, communication, morale, and informedness bar as high as you can.

In a field as fast-evolving as AI and data science, how do you keep your team and products at the cutting edge? What's your strategy for staying informed and innovative?

The Athena team consists of information junkies. Brendon, our founder and CEO, shares dozens of links daily. The field moves fast, and we embrace new developments quickly. Our team's passion for AI and what we're building helps. We often find time to hack new things, leading to new features or capabilities within days.

I’m curious, what does a typical day look like for you at Athena?

We're a small, nimble team, so we keep communication and focus tight. My responsibility is customers, particularly their workflows.

Bridging the gap between customer needs and our product capabilities involves mapping problems to solutions, guiding users, and communicating insights to the engineering team.

This requires constant decision-making, from helping customers to determining what should be built and if it's good enough, often with only 60-80% of the information.

Running a startup can be all-consuming. How do you keep a healthy work-life balance, and what advice would you give to other founders who are struggling in this area?

I'm not great at this, but living in New York for the past three years taught me the importance of sports. My teammates work out almost daily, and I try to keep up.

I enjoy Japanese jiu-jitsu, volleyball, and hot yoga, which are more time-consuming than the gym, but I make do. Working out 3-4 times a week is beneficial and keeps my mind off unnecessary thoughts. Waking up at 6 am also helps maintain energy.

You've compared AI development to levels of autonomous driving. Where do you see AI heading in the next few years, especially in terms of its impact on startups and new businesses?

I like comparing AI development to levels of autonomous driving. Currently, the industry focuses on tools that make information workers more efficient.

For example, a founder can send 30 well-crafted emails a day using AI-assisted tools, and an analyst can process much more information with agents like Athena. However, humans still have the final say.

The next wave involves autonomous agents that can be overruled at any time. These agents will start small but will improve as models and tools advance. In 6-12 months, some tasks will be automated, though humans will still need to review and correct them.

This period will require skills in planning, defining outcomes, and managing multiple tasks. For startups, this means matching the throughput of larger companies, but it requires intentional task definition and delegation.

Let's wrap up on that point. What advice would you give to startups looking to stay ahead of the curve with these upcoming AI advancements?

The amount of short-term and mid-term potential the AI brings to any niche of knowledge work is very high. The actual production adoption is still very low. Don't shy away from trying new things often.

Don't give in to scepticism and annoyance with the hype, stay sober, but curious and eager to give things a chance. If your domain is threatened by AI, embrace it and become one of the players who's changing the industry.

If you can benefit from AI adoption within your company, become a design partner for an AI startup — there's much more new AI startups than uncovered use cases.

From the Startup Life team

And that's a wrap! We hope you've enjoyed this edition as much as we loved putting it together. Stay curious, keep learning, and above all, enjoy the rollercoaster ride that is Startup Life. Catch you in the next one! 👋 Not subscribed yet? Do it here and don't miss out! Subscribe Now.

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