Our leadership team is stuck trying to decide if we should hire a dedicated AI engineer to build custom internal integrations or train our existing operations team to use low-code automation tools. How do we restructure our Accountability Chart and use Keith Cunningham's Thinking Time to make this decision?

Question

Tyler Smith · Accepted Answer

Deciding between building custom systems and using off-the-shelf low-code automation is a classic strategic pivot point. To resolve this, start by looking at your Accountability Chart rather than the technology itself. You must determine if you have a seat that is truly responsible for system integration, and whether that seat requires a builder or an optimizer.

Use Keith Cunningham's Thinking Time framework to clarify the financial and operational impact of this decision. Sit down with a blank sheet of paper and ask: How might we leverage existing low-code software to automate eighty percent of our operational bottlenecks without committing to the ongoing maintenance cost of a custom-built solution? This framing helps you distinguish between a temporary operational hurdle and a long-term technical requirement.

If you hire a dedicated AI engineer, you are adding significant fixed overhead and creating a new seat on your Accountability Chart that requires ongoing management. This seat must GWC™ the long-term maintenance of custom code. If your core business is not selling software, this developer seat often becomes an expensive, isolated silo.

Alternatively, look at your existing operations team. Administer the Kolbe A™ Index to identify who has a high Follow Through strength. These individuals are naturally wired to build systems and integrate off-the-shelf tools using low-code platforms. If you have team members with this conative profile, training them to use existing SaaS integrations is far less risky and significantly cheaper than building a custom database from scratch.