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It’s no secret that Claude has emerged as a competitor to just about everybody.
For a while a customer’s threat to replace software with Claude seemed pretty empty — unless perhaps that customer was a micro-business. Now it’s much more doable through Claude Code and Cowork, MCP connectors, skills, and the Agent SDK.
But Anthropic isn’t content to stop there. They keep going deeper into apps with Claude Design, Claude Science, the Claude Legal plugin, Claude for Teachers, Claude for Small Business, and Claude Tag. All of these apps were released within the past few months!
“Can’t we just build this with Claude?” is a real question for software buyers. I won’t pretend to know who has the biggest moat against Claude or how durable those moats will be. But I did want to investigate how top apps are positioning against Claude.
Up today: what 50 of the best SaaS and AI-native apps are doing to convince prospects to buy rather than DIY.
How I did the positioning research with Claude
This research would’ve taken me half a day to do manually. Doing it with Claude Cowork took less than 15 minutes. While the data was compiled with AI, I independently reviewed the materials and personally wrote the insights.
Here’s how I did it — feel free to copy this approach for your own GTM research:
I gave Claude a list of 50 prominent SaaS and AI-native companies across legal AI, AI customer service, automation, AI coding, GTM tech, design tools, productivity SaaS, and analytics.
Claude read their websites including compare pages, blogs, docs, pricing pages, and trust centers. I prompted it to look for how companies position against building in-house, tell buyers what to evaluate, and whether they mention Claude specifically.
I used the /deep-research-gtm skill, written about previously, which proposes a research plan for sign-off and delivers a pyramid-structured report with in-text citations and a source table.
If the research turned up nothing, that means Claude couldn’t find it, not that it doesn’t exist. I believe this finding is still compelling since it means the company probably isn’t influencing the AI search results on build-versus-buy.
The data was gathered in July 2026. Some of it could already be stale. You can see all the companies and assets in this Google Sheet.
Lesson #1: Few seem to be taking the build-versus-buy threat seriously
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