From Niche to Norm: What AI Tools Have Top Engineers Incorporated into Their Stack?

It’s no secret that AI tools are reshaping how developers work. From automating boilerplate code to boosting daily productivity, artificial intelligence has evolved from a sidekick to a co-pilot — and in many cases, the pilot itself. The adoption of these tools is rapidly becoming the norm, with usage rates ranging from 70% to 82% across countries such as the U.S., Brazil, India, and Germany, according to GitHub. And for good reason.

McKinsey reports that 65% of companies that have adopted AI have seen increased revenue in at least one business function, while 44% say it has reduced costs in those areas.

We asked a segment of our engineering community at BEON.tech — a network of thousands of top-tier Latin American developers — a simple yet revealing question: “Which coding assistant are you currently using?” The results shed light on which tools are gaining traction and which are quietly falling behind.

To complement the insights from this survey, we also hosted an internal webinar led by Damian Wasserman, co-founder of BEON.tech, where he explored how developers across the region are integrating AI into their daily workflows.

Throughout this post, we’ll bring in some of Damian’s key takeaways — and we’ll take things a step further by examining how these changes reflect the broader shift toward AI-first engineering.

Cursor Takes the Lead

With 29% of the votes, Cursor is the clear frontrunner among BEON.tech developers. Its seamless integration with code editors and focus on speed and accuracy make it a favorite for devs looking to speed up iteration without compromising code quality.

Cursor’s growing traction is consistent with wider industry trends. Damian highlighted Cursor’s ability to reduce friction in complex tasks, especially when switching between logic-heavy files. He also praised its collaboration features for distributed teams, aligning perfectly with modern, AI-first engineering workflows.

ChatGPT and GitHub Copilot: Still Strong Contenders

ChatGPT earned 19%, showing its value as a flexible, general-purpose AI assistant. From debugging to architectural decisions, developers trust it for more than just autocomplete.

GitHub Copilot, once the AI darling of coders, now trails slightly at 17%. It’s still a solid choice — especially for GitHub-heavy workflows — but the competition is heating up.

According to Damian, GitHub Copilot remains popular in enterprise environments because of its seamless integration with CI/CD pipelines and GitHub repos. However, its limited customizability compared to tools like Claude or Cursor may be pushing devs to explore new alternatives.

Claude Enters the Chat

Claude also secured 17% of responses, marking its place as a rising star in the AI coding space. Lightweight, conversational, and context-aware, Claude is carving out a niche with devs who value a more collaborative interaction.

Its extended context windows and structured prompts make it ideal for pair programming — particularly when dealing with legacy codebases or massive monorepos.

Gemini and Claude Code: Niche but Growing

Gemini, Google’s entry in the race, pulled in 8%, while Claude Code landed at 6%. Though not yet mainstream, they’re attracting early adopters exploring alternatives outside the dominant players.

As Damian noted, Gemini is often preferred by Android developers within the Google ecosystem. Meanwhile, Claude Code’s coding-first UX and advanced summarization capabilities are quickly earning it a loyal following.

The Curious Cases: Tabnine and Windsurf

Tabnine and Windsurf each earned 2%, signaling low but present engagement. Whether these tools evolve or fade will depend on future innovation — or acquisition.

Damian touched on the ongoing consolidation of the AI tooling space. Windsurf, for example, recently caught attention after being acquired by Cognition (creators of Devin), but still hasn’t built meaningful traction.

One Lonely Dev

Just 1% of devs reported not using any AI assistant. That’s a powerful message on its own: in mid-2025, going AI-free is almost unheard of.

The AI Adoption Dilemma: What Does This Say About the Modern Tech Stack?

AI coding assistants are no longer optional. They’re becoming core to the daily workflows of top-tier engineers. Whether it’s refactoring, documentation, or pair programming, these tools are embedded in the way developers think, code, and collaborate.

Damian emphasized that this isn’t just about tooling — it’s about a cultural shift. Teams are adopting “AI-first workflows,” where code reviews, estimations, and testing are supported or initiated by assistants. This redefines what productivity means for devs.

He also underscored the rise of role-specific assistants (like Claude for architecture insights or Cursor for debugging) and how engineers are now stacking assistants — using multiple tools simultaneously to cover their entire dev flow.

From Engineering Managers to Hands-On Leads

Another shift Damian noted is how engineering management roles are evolving:

This reflects a growing industry preference for “doers” — highly-skilled, versatile individuals who can ship product and guide AI-driven workflows.

If your team is navigating how to integrate these new technologies, check out our breakdown of AI business solutions for tech leaders or explore how to effectively collaborate with a generalist software engineer in this new landscape.

Ready to integrate top-tier AI-powered talent into your team?

At BEON.tech, our Latin American devs are not just keeping up with the future — they’re building it, one AI-assisted commit at a time.

Schedule a call with our team and find the right developer to help you scale with confidence.