BUILD AI TOOLS, NOT SAAS

Leverage AI-first development: Build bespoke, efficient internal tools faster and maintain them with evolving documentation and shared best practices

Dec 17, 2025 6m 19s

Maciej Korolik

Expert Insights

Maciej Korolik makes a powerful case for building bespoke AI-powered internal tools rather than relying on generic SaaS products. He proposes this shift as a new default in software development practices.

Maciej highlights the increasing ease of building tailored systems that fit a particular organization's needs, providing an exact solution rather than a close approximation.

Maciej's approach brings to light:

The benefits of bespoke AI-first development, emphasizing on quick implementation and full control over feature addition.
The advantages of personalized internal tools over off-the-shelf SaaS solutions, particularly avoiding vendor lock-in and feature load.
The use of AI to assist in the development process, ensuring quicker and more efficient software production.
The importance of extensive and dynamically updated documentation to ensure AI models work efficiently.

So in cursor, we have this folder in the repository with the rules. And each rule is like a set of instructions for AI, but also a set of uh, best practices to use in the project. (...) It is very important that we constantly update and look if the rules are still relevant, based on our experience. And also because the project evolves.

Monterail Team Analysis

Here are the key takeaways for software development teams transitioning to AI-enabled workflows:

Prioritize Bespoke Development: Consider developing in-house AI-enabled tools tailored to your unique needs, instead of relying on generic SaaS solutions. Use AI to drive efficiency and better customization.
Re-think the Build vs. Buy debate: Understand that the economics of software development have changed with AI. Building your own solution might be quicker and more cost-effective than waiting on a SaaS provider.
Emphasize Documentation: Maintain comprehensive and updated documentation for AI models to ensure efficient functioning and evolving with project needs and learnings.
Share Best Practices: Draw inspiration from platforms that share successful rules used in similar projects; it could help inform your own AI-first development strategies.
Regularly Review Rules: Monitor the application of the rules in your project to ensure their relevance and modify and update them based on your project's evolution.
Prepare for Project-Specificity: Design your AI solutions understanding they might not cater to thousands of users, but will precisely meet the needs of your team or organization.
Plan for Quick Implementation: Harness AI's power to execute features and tweaks in your software in a matter of hours, making it a highly responsive tool.
Anticipate the shift: Understand that internal tool development, facilitated by AI-assisted development, is becoming a new norm.