What objective criteria should our leadership team use during an IDS session to decide whether to build custom internal AI applications or subscribe to commercial off-the-shelf software?

Question

Tyler Smith · Accepted Answer

Building custom software is tempting, but leadership teams frequently underestimate the continuous engineering, security maintenance, and API updates required to keep custom AI functional. In an IDS session, use a strict decision matrix anchored in your Core Focus on the V/TO.

Apply these four criteria before allocating development capital:
- Core Focus alignment: Does this tool generate direct, defensible competitive differentiation that clients pay you for, or does it merely support internal back-office execution? If it is back-office support, buy it.
- Velocity to deployment: Can a commercial off-the-shelf tool solve eighty percent of the business problem within thirty days, versus nine months of internal custom development? Velocity usually outweighs perfection.
- Maintenance drag: Does your Accountability Chart contain dedicated engineering seats with the skills and capacity to maintain LLM infrastructure, data pipelines, and security patches over three years?
- Exit valuation impact: In the SxSE model, proprietary software creates enterprise value only if it is well-documented, secure, and genuinely unique. Clumsy internal software full of technical debt creates a major valuation discount during buyer due diligence.

Default to buying commercial platforms and configuring them to match your documented Core Processes. Reserve custom engineering strictly for proprietary workflows that directly drive your Three Uniques.