On one project, client priorities were shifting often and frustration was building. The issue seemed to come less from the engineers or the client and more from how the team's working styles collided with last-minute change.
Strong engineers are only part of what a project needs. The people also have to work well together.
Friction between working styles affects delivery more than most project plans acknowledge. A meeting that drags on without a decision slows engineering. A requirement change that arrives too late can create rework. A team can have the right skills and still lose time because people process change, ambiguity, and problem-solving differently.
At Six Feet Up, we use tools like the Predictive Index, the Kolbe A™ Index, and the 6 Types of Working Genius to understand how people work. We use that information when building project teams, and AI helps us apply it while the work is underway.
A project may need someone who digs deeply into details, someone comfortable working through ambiguity, someone who generates ideas quickly, or someone who is especially good at challenging an approach before the team commits to it.
Putting those strengths together gives a project a better starting point. From there, the team still has to communicate well, absorb change, solve problems, and make decisions efficiently.
That is where knowing how each person's strengths fit together becomes useful.
Each assessment has its own language, and across multiple people and projects, that’s a lot to track. I keep each project team's profiles, including my own, together in Claude Cowork and handle them as sensitive information under Six Feet Up's established data-handling practices.
Having the team profiles in one place makes it easy to spot where working styles may be creating friction, so I can adjust my approach before it slows the team down.
When I looked across the team’s Kolbe profiles, I noticed that everyone scored low in Quick Start, which reflects how someone instinctively deals with risk and uncertainty. Lower Quick Start scores tend to favor minimizing chaos over experimenting on the fly.
For this team, a last-minute pivot felt like more than a minor disruption. It went against how they work best, and they needed more runway when priorities changed. This was a working hypothesis, not a definitive answer, but it gave me something specific to test.
So I started sharing potential shifts earlier, even before every detail was finalized. Engineers had more time to think through dependencies, risks, and downstream impacts before a change became urgent. The client still had the flexibility to change direction, but the team was better prepared to respond.
Working Genius helped in a similar way. The model identifies six types of work and shows where each person has Working Geniuses, Working Competencies, and Working Frustrations. Geniuses tend to energize people, Competencies tend to be work they can do well but that takes more effort, and Frustrations tend to drain them.
On this team, some people were strongest at generating ideas (Invention), while others were better at evaluating concrete options (Discernment).
Instead of asking everyone to brainstorm from a blank page, I asked the idea generators to propose a few options first. Then the rest of the team could challenge, refine, and improve them.
The conversations moved faster, and the team reached stronger decisions with less time spent circling the problem.
Those hours add up. Every hour saved in meetings or rework can go back into architecture, implementation, testing, and review.
Software teams spend a lot of time improving architecture, automation, CI/CD, test coverage, and developer tooling.
How the team works deserves the same attention.
The way a discussion is structured affects how quickly a decision gets made. Team dynamics affect how much time is spent solving problems versus navigating friction around the work.
AI gives us a practical way to use more of what we already know about how people work, without adding another layer of process. The profiles already existed. The technical expertise was already on the team. AI made the context easier to use when it mattered.
For the client, that means fewer avoidable delays, smoother changes, and more engineering time spent moving the project forward. It starts with putting the right people on the right team, then creating the conditions for them to do their best work together.
Read more about Six Feet Up’s Flex6 Process and EQ+IQ™ Team Fit, which considers technical skills, industry experience, personality traits, and individual interests when assembling project teams.
Six Feet Up, Inc.
11208 Windermere Blvd.
Fishers, IN 46037 - USA
Phone: +1 (317) 861-5948
Email: info@sixfeetup.com
