Build Vs. Buy

What It Covers

Petra Billet and Theresa Schwartz examine when product teams should build custom solutions versus buying existing tools, exploring how AI and vibe coding capabilities are shifting traditional decision frameworks around data ownership, vendor lock-in, and engineering complexity.

Key Questions Answered

• •Core Value Rule: Teams should buy tools that are not core to customer value delivery rather than spending product, engineering, and design resources on peripheral systems. The exception occurs when engineering teams lack the technical capabilities to maintain critical infrastructure, making purchase faster than hiring specialized talent.
• •Data Ownership Priority: AI capabilities elevate data portability as a primary decision factor when evaluating vendor solutions. Before selecting platforms like Salesforce or HubSpot, teams must verify complete data export capabilities including comments and attachments, or risk losing control of business-critical information that could limit future AI applications and strategic flexibility.
• •Vendor Capability Assessment: Choose vendors who excel beyond internal capabilities in specialized domains like payments, where Stripe dominates because no reasonable timeline allows matching their expertise. Evaluate whether competitors use the same vendor, creating competitive risk, and whether the vendor supports unique business requirements that justify avoiding custom development.
• •Build Complexity Reality Check: Engineering teams often overestimate their ability to replicate SaaS functionality due to hidden business logic complexity. Conduct technical spike tests to validate feasibility and user experience capabilities before committing to custom builds. Even simple-seeming tools like DocuSign contain years of accumulated features serving diverse customer segments.