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Steve Brain

CTO/CPO - ex Amazon & Qualtrics

Steve Brain is a highly accomplished technology executive with extensive experience in software engineering and product development across various high-tech industries. With a career that spans over several decades, Steve has been instrumental in building software organizations that deliver substantial customer value. His expertise lies in creating market-leading software services in several domains, including financial services, e-commerce, and B2B SaaS. He has a particular talent for leading teams through complex challenges, transforming existing engineering organizations, and fostering a customer-first approach in every project he undertakes.

Steve’s experience is incredibly diverse, having developed systems ranging from real-time trading applications to large-scale e-commerce infrastructures and even supply chain optimizations. He has successfully launched multiple SaaS products, showcasing his ability to innovate and adapt to the constantly changing landscape of technology. His leadership has not only built successful software but has also created lasting engineering organizations both in the United States and Europe, demonstrating his commitment to long-term strategies in team building and product success.

In addition to his impressive technical skills, what sets Steve apart is his dedication to mentoring and training teams. He has a knack for constructing teams from the ground up, ensuring that the engineers he works with have the skills, tools, and mindset necessary to meet customer needs effectively. With Steve at the helm, organizations experience a unique transformation where the focus not only remains on cutting-edge technologies but also on aligning product goals with real customer value. This dual focus has been a hallmark of his career and is evident in the success of the companies he has worked for.

Highlights

Jul 24 · linkedin

I’m happy to share that I’m starting a new position as Chief Technology Officer at Agolo. CEO, John K. introduced me via a consulting arrangement and I was impressed and decided to join the team full time.

“Any sufficiently advanced technology is indistinguishable from magic” Arthur C Clarke.

Time to make some magic. Gen AI has a lot of promise but the gap between query engineering and real results is too large. Agolo is making Gen AI useful for enterprise clients.

Jul 12 · linkedin

In January I started a career break. It had been years in planning, and aligned with us finishing a house build and wanting time to get things straight. Since January I’ve skied a bunch in British Columbia and also in France, Italy, Switzerland and Norway. Also had plenty of time to relax, ride my bike and reflect. For those really interested, I did make a hiking trail on our property but am still figuring out how to build a mountain bike trail on a steep hillside.

However, there is more to the story than this. I also wanted to explore a startup idea I had. With the shift to 401(k) retirement plans in the 1980’s and the generations of baby boomers and increasingly Gen X retiring now, there are a significant number of Americans balancing investments and spend in their retirement. Consistent sources such as social security, final salary plans and annuities, are replaced with variable income sources based on capital market performance.

But the current tools to manage spend still use similar data models to Quicken. They focus on financial transactions, versus true units of spend. If you shop on Amazon, they want to categorize every transaction the same. In my research I found there are people who still love Quicken, but they are self diagnosed as a little obsessive compulsive. Those individuals are happy to manually categorize and split each transaction into the correct spending class. Those are not the majority of our population - most people wing it.

Building a better product is made easier today with AWS services including Quicksight (for reporting), Plaid for gathering financial transactions and LLMs to analyze and generate personalized recommendations. I was able to prototype quickly and was confident a great product could be built.

Why am I publishing this now? The short answer is I decided to abandon the endeavor. There are two reasons why, different sides of the same coin:

Price - researching the competitive landscape, consumers are willing to pay around $100/year for a solution. The appetite for a better product that costs more might justify 2x this, but it would be hard to justify 10x the price. Cost - the cost of goods sold (COGS) in this product would be impacted by the monies payable to AWS, Plaid and OpenAI. COGS impacts margin, which impacts both bootstrapping and fund raising.

It was a fascinating exercise to think through building a company from scratch. It reinforces my belief that founders need to be risk takers, and I’m probably too rational to believe the impossible. It also explains why only a small percentage of startups succeed.

From my research, I did personally start using copilot.money for my own financial tracking, as the best option I could find.

As for what’s next for me? I’ve got more tech work in my future and recently completed a tech evaluation for a startup (not Copilot or anything in this same immediate space). More to come soon.

Related Questions

How did Steve Brain develop his expertise in engineering leadership and software development?
What are some examples of the SaaS products Steve Brain has successfully launched during his career?
How has Steve Brain's educational background in Computer Systems Engineering contributed to his success as a technology executive?
What strategies did Steve Brain implement to ensure a customer-first approach in the organizations he led?
How did Steve Brain construct and transform engineering organizations in both the US and Europe?
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Location

Bellingham, Washington, United States