Get your free personalized podcast brief

We scan new podcasts and send you the top 5 insights daily.

The biggest drawback of building a custom CRM or similar internal tool is the opportunity cost. It pulls top engineering talent away from improving the core, revenue-generating product and tasks them with rebuilding infrastructure that already exists as a commercial off-the-shelf solution.

Related Insights

The primary cost of building a new GTM measurement system in-house isn't money, but the "time tax." This represents months of missing data, unseen pipeline opportunities, and delayed revenue that accumulate while an internal team learns through trial and error, versus leveraging a proven framework.

The opportunity cost of building custom internal AI can be massive. By the time a multi-million dollar project is complete, off-the-shelf tools like ChatGPT are often far more capable, dynamic, and cost-effective, rendering the custom solution outdated on arrival.

An established customer base is both an asset and a liability. The endless demands for features and support for the core product can consume over 98% of engineering resources. This "trap" leaves little capacity for the focused work needed to create a competitive AI product, causing companies to fall behind.

Building an in-house version of a tool like Slack is nearly always a mistake, argues Redpoint's Logan Bartlett. Even if the direct engineering cost seems lower than a subscription, the true price is the immense opportunity cost of diverting top talent from the core, revenue-generating product.

Building a custom tool with AI to replace a SaaS subscription seems cost-effective, but building is only 10% of the work. The other 90% is the often-forgotten overhead of maintenance, on-call support, security, and bug fixes that SaaS vendors typically handle.

Saying yes to numerous individual client features creates a 'complexity tax'. This hidden cost manifests as a bloated codebase, increased bugs, and high maintenance overhead, consuming engineering capacity and crippling the ability to innovate on the core product.

The fantasy of replacing a major SaaS platform like Salesforce with a custom-built tool ignores the total cost of ownership. Beyond initial development, the internal team becomes responsible for documentation, feature upgrades, security, support tickets, and user enablement—functions that are bundled with a commercial product.

Building proprietary internal tools is a 'dumb thing to do when you're small, but it's the smartest thing to do as you scale.' Deel's CEO advises waiting until the company is on a clear path with strong, profitable growth. At that point, investing in custom infrastructure like a proprietary ticketing system becomes a strategic advantage that unlocks significant long-term efficiency.

With executive time valued at $1,000-$2,000 per hour, building a custom app that could be bought for $10,000 makes no financial sense. The justification to build must be a critical, strategic need for something unavailable on the market, not a desire to save on subscription fees.

Forgo building custom AI tools for common problems. Instead, purchase 90% of your AI stack from specialized vendors. Reserve your in-house engineering resources for the critical 10% of tasks that are unique to your business and for which no adequate third-party solution exists.

Building Internal Tools Diverts Precious Engineering Resources from Core Product Development | RiffOn