Building Data Centaurs in Investment Technology: A Guide for Investment Tech Leaders
The rapid surge of AI has a direct impact on career and leadership decisions in IT. The ideal is to create a culture optimized for data centaurs: developers with human minds up top and all the horsepower of AI supporting them so that they can go farther and build better.
How to measure the right things
Many technology leaders approach automation and productivity in terms of systems thinking or trying to cut costs. The problem is that it means looking at all the people in your organization as a cost or liability. Everyone is someone with potential to be eliminated — a better path involves focusing on enabling top outcomes.
Developer productivity then becomes a suitable yardstick. For example:
- DORA metrics, developed by the DevOps Research and Assessment group, focus on software delivery performance in areas such as deployment frequency, time required for changes, change failure rate, and time to resolve incidents.i
- The SPACE framework (Satisfaction, Performance, Activity, Communication/Collaboration, and Efficiency/Flow) measures performance outcomes, the activities developers engage in (like code reviews or contributions), team collaboration effectiveness, and the efficiency of workflow, but also adds developer satisfaction.ii If you’ve hired people who want to achieve, their satisfaction is a good indicator of productivity.
In the age of AI coding tools, another way to look at the people in your organization is to look at them as huge sources of context, such as the culture of your organization, written and unwritten rules, and implied goals. AI models function with “context windows” that help them process a request. So do people! But any AI model will struggle with over-large context windows or with not having enough context for a task. People are excellent at retaining large amounts of context and dealing with it over time.
We’d all love to hire the top talent in any field — but the path to having a team of excellent people is usually by hiring less-than-perfect people earlier and growing them over time. These factors help you get more return on your investment in those people.
The data centaur vision
If you're going to add automation to your team, think of a centaur. You need to direct people’s brains, judgment, and knowledge of context and history to lead to outcomes. Give them more horsepower so they can go faster, be stronger, and lift more for your organization.
If you give people command of more data, the ability to process more of this data, to clean and contextualize it, and to turn it into solutions and help find those hidden patterns, you develop a team with superpowers.
But, if you look at them as cogs or units you can automate and eliminate, you end up with people who are interchangeable by design. It forces you to invest only in your systems with disposable people. That’s a reverse centaur,iii where the machine is the head, and human effort must carry all that horse weight around.
The technologist and writer Cory Doctorow has an excellent example of a freelancer who is hired to use AI tools to ”write” 64 pages of content and fact-check it himself. It sounds like a great cost-saver, but it turns into a bad outcome for the publisher when AI hallucinations crop up throughout the guide. The system is architected to produce a bad outcome, and the human is there to take the blame for it.
You've just created the person in charge of getting fired for a generative AI hallucination or a mistake. You haven't really prevented the mistake. You've created blame, but it doesn’t help achieve your goals.
Empowering individual developers
Take a software development task, for example, creating a feature that allows users to custom-theme your website for their company colors and logos.
The reverse centaur developer thinks, "I just have to add this generated code. My job is to check that there aren't any security holes at the end. I'm only responsible as the person who gets blamed if there are big bugs or problems." That's not a fulfilling job.
The centaur developer thinks, "I want to generate a set of requirements that look reasonable and complete before I approve them. Then I can break those out into individual development tasks with tests." They pump requirements through agentic workflows, using them for tasks like a first draft code review. The tools help them move faster and concentrate on tough problems.
The difference is participation. Developers understand where the edges are, and where the priorities lie. They become committed. Without that ownership, they say “yay” or “nay” to what the AI did and send it out the door. You end up falling short of requirements that no one understands and safeguards that no one cares enough about.
Orchestrating centaur teams
You can shout at people to use more AI tools, but they need more reasons than being told. Otherwise, you're just leading horses to water. It's hard to force them to drink it.
To organize development, people need to know what they own and when they need to check in with each other. If they don't understand the RACI matrix, they don't know what they are responsible for or accountable for.
But if you have people motivated and eager to accomplish their goals, their motivations will drive them to take up better tools and to accomplish more.
The data show how this trend is playing out:
- A GitHub survey found 92% of U.S.-based developers are already using AI coding tools both in and outside of work.iv
- JPMorgan software engineers reportedly increased their productivity 10% to 20% using an internal coding assistant.v
Building a centaur culture
Centaurs create a lot of value. But you also want to have a herd that plays well together.
To cultivate a centaur-like culture, you first need to make sure it's demonstrated from the top down. Different organizations have different approaches. If you have an organization driven by a list of mandates to execute, you can still have your centaurs. But it’s important that each team member gets clear messages: “Here are your goals, I need Alice to achieve this and Bob to achieve that, and here are the people who can assist you or not.”
Starting the transformation
If you want to create your own centaur culture, you can do it by starting with the outcome you're looking for:
1. Define your desired outcome
If you're looking at a future where there are lots of unpredictable challenges, and the landscape changes under you all the time, and you need people who can quickly cope and adapt to challenging and changing circumstances, try to build centaurs and superheroes who have superpowers so they can quickly respond to things.
2. Create capacity for agility
If you want people to have the capacity to respond to changing requests, to pivot on a dime, and be agile, make sure they can create capacity when needed. Give your centaurs the choice to automate based on what they see as being the biggest blockers in their workflow.
3. Set clear frameworks
Set up a simple and unambiguous framework. “Here are your goals. Where you can stand out, be rewarded, and recognized. Here's where you're just expected to do X, Y, and Z. Here are things that we absolutely don't want you to do.”
4. Provide challenges
When you give people interesting challenges, they tend to rise to them. But if their job doesn’t involve judgment and decision-making, you are likely to have problems in the future. You’ll leave your developers believing you just haven't figured out a way to automate them yet.
Riding forward together
AI gives developers a way to be more than cogs in a machine, but it's up to leaders to help make that happen. You're looking for ways to get even more return on your investment in those people so that they can accomplish their goals better and faster.
The way is to give them more horsepower. Build centaurs who have the agency to tackle challenges and come together as a herd to deliver on your technology strategy.
Authored By
Matt Katz
As Arcesium's Field CTO, Matt leads Arcesium's Forward Deployed Software Engineering and Client Success teams. His work to empower clients and simplify technical challenges stems from a 25-year career in financial technology working with clients and software. Outside work, he enjoys books, bikes, and boards.
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[i] DORA. https://dora.dev/
[ii] ACM Queue, 2021. https://queue.acm.org/detail.cfm?id=3454124
[iii] Locus, September 1, 2025. https://locusmag.com/feature/commentary-cory-doctorow-reverse-centaurs/
[iv] GitHub, June 13, 2023. https://github.blog/news-insights/research/survey-reveals-ais-impact-on-the-developer-experience/
[v] Reuters, March 14, 2025. https://www.reuters.com/technology/artificial-intelligence/jpmorgan-engineers-efficiency-jumps-much-20-using-coding-assistant-2025-03-13/
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