[Editor’s Note: This guest post is by Marcelo Calbucci, a longtime Seattle tech and startup community leader.]
This month, I ran a survey with early-stage founders from Seattle-based Foundations about their use of AI tools and agents. There were some surprises in the data — and not in the direction you’d expect — and trends that are worth talking about.
The sample size represents 22 startups with one-to-five software engineers each, for a total of 42 people. What makes this cohort valuable to understand is that they are AI-native startups, started during a time that AI can code. This gives us a glimpse into the future of tech companies.
The first question I asked on the survey was about the percentage of production code being written by AI. I wrote this question explicitly to exclude unit tests, scripts, documents, and other artifacts that are not related to the core value proposition of a business. If you know one thing about AI coding, it is that it generates large volumes of unit tests, readme files, and scripts. None of that relates to the code that delivers the value to the customer.
Here’s the surprising fact: out of the 22, four startups (18%) said AI is writing 100% of their code. That’s mind-blowing! It doesn’t mean these folks are not reviewing and re-prompting the AI to refine the code. However, it means they aren’t typing code in an IDE. There are 11 startups (50%) where AI is writing 80-99% of the code. Adding the four where AI writes everything, 68% of startups have AI write over 80% of the production code. On the other side of the spectrum, three startups (13.6%) said that AI is writing less than 50% of their code.
Choose your weapons
From the news that Cursor gets in the press, you’d think usage for this cohort is close to 100%. In our sample, out of 42 programmers from 22 unique startups, “only” 23 of them (54.7%) use Cursor. On average, Cursor programmers spent $113.63/person in September. The most popular tool, though, is Claude Code, with 64.3% of programmers using it and spending $167.41/person in September. Claude is the preferred tool for startups, with 16 of the 22 (72.7%) using it.
After Claude and Cursor, there is a big cliff, with OpenAI Codex coming in a distant third place with seven of the startups using it, representing 12 of the 42 programmers. On average, expenses with OpenAI Codex came in at $48.49/person in September. The fourth and fifth places were GitHub Copilot and Gemini CLI by Google. They had 9.52% and 4.76% of programmers using it, respectively.
On average, each software engineer spent $182.55 in the top five AI tools mentioned above, with some startups spending over $400/person.
Founders also mentioned they use a variety of tools to create production code, including Lovable, Devplan, Mentat, Factory.ai, Jetbrains Junie, Warp, and Figma.
Roadblocks
When asked about what’s preventing more use of AI for coding, the number one complaint was the quality of the code. Another hindrance to faster adoption is the learning curve to get the agent to do what you want.
In terms of frustration, this group raises three key issues. First, the quality of the output, requiring considerable rework. Second, a mismatch between expectation and reality based on what everyone is hearing. Lastly, the most common frustration — and I definitely empathize with this one — is managing the context and dealing with large code bases.
What’s next?
In the survey, I asked about their intention to continue using AI tools and agents to assist with product development. The survey asked the founders if they intended to add, remove, increase, or decrease usage of each tool. The biggest winner, by far, was Codex, with nine startups (40.9%) saying they aren’t using it yet, but plan to use it in Q4. Once I normalize the data to account for what the expectations are for Q4, Claude will maintain its leadership, but Codex will match in the number of startups. Cursor and GitHub Copilot will trend slightly lower, each with one startup saying they will stop using it. Finally, the Gemini CLI might see a small increase in adoption, with three startups claiming to give it a try in Q4.
Contrary to the many other aspects of software engineering like choosing a cloud provider, a language, or database, AI tools and agents are not a zero-sum market. On this survey, 68.2% of startups used more than one AI tool to assist in production code development. Based on their stated intention, that number will grow to 86.4% in Q4.