The SaaS Moat Was the Cost of Reconstructing Your Own Intent

SF Scott Farrell July 17, 2026 scott@leverageai.com.au LinkedIn

This line cuts deeper than “AI makes software cheaper.”

It says a large part of the SaaS moat was never product superiority. It was the cost of reconstructing your own intent.

That intent is already sitting inside the system—in decisions accumulated over years. Until now, it was legible to users but prohibitively expensive to turn back into software.

Once AI can recover it, feature breadth stops being the same kind of lock-in.

But the escape path has a toll: verification.

Generating the replacement is becoming cheap. Proving that it preserves every edge case, control, permission, integration and exception is now the real work.

So the strategic consequence is not that every company should rebuild its stack.

It is that the build-versus-buy calculation has changed—and many renewal decisions are still being made with the old maths.

The vendors most exposed are not those with weak features. They are those whose strongest moat is the customer’s belief that leaving would require rediscovering the business from scratch.

It may not anymore.

Learn more: https://leverageai.com.au/wp-content/media/articles/article.php?article=105-custom-software-verification

Originally posted on LinkedIn


Discover more from Leverage AI for your business

Subscribe to get the latest posts sent to your email.

Leave a Reply

Your email address will not be published. Required fields are marked *

© 2026 Leverage AI, Scott Farrell. All rights reserved. This content is made available on a limited, revocable, read-only basis only. No licence or right is granted to copy, reproduce, republish, scrape, store, adapt, summarise, index, embed, or use this content to create derivative works, work product, deliverables, methodologies, training materials, prompts, templates, software, services, research, or commercial outputs, whether by humans or machines, without prior written permission. This restriction includes internal business use, client work, consulting, advisory, implementation, and any use in or for artificial intelligence, machine learning, data extraction, retrieval, evaluation, fine-tuning, or knowledge-base construction.