Ukrainian product company MacPaw has completed an internal two-week experiment to introduce artificial intelligence into the daily work of teams. As a result, employees created hundreds of projects, some of which the company plans to integrate into ongoing processes.
Ukrainian product company MacPaw has completed an internal two-week experiment to introduce artificial intelligence into the daily work of teams. As a result, employees created hundreds of projects, some of which the company plans to integrate into ongoing processes.
According to DOU, MacPaw held an Agent Practice Sprint from March 2 to 13. The initiative involved 402 employees, who launched 355 projects, and managed to implement 247 solutions. For this purpose, the company created a separate internal platform where participants registered ideas, recorded progress, and could seek help from mentors.
Teams from different areas took part in the sprint. The projects were divided into two large tracks — Product and Business Operations, and some employees simultaneously supported the stable operation of products and user service. For the experiment, MacPaw opened access to Claude, Google Gems, n8n, Google Cloud, GitHub, Cursor and other tools, and also expanded API limits so that teams could not just test basic scenarios, but build full-fledged solutions.
Among the tools created are systems for checking code with multiple AI agents, services for prototyping functions directly from Jira, automatic updating of test cases after code changes, as well as solutions for cybersecurity, user analysis and brand mention monitoring. Separately, the company has developed internal tools for analytics in Slack, working with the code base, financial assessment of new ideas, reporting automation, as well as support for legal, marketing and HR processes.
MacPaw says they see this sprint not as a one-time event, but as a foundation for further implementation of AI into operations. The next step is to assess how much time the new tools actually saved teams and determine which ones are worth scaling across the company. MacPaw is also preparing regular meetings to share best practices for working with AI.
Against the backdrop of a market where most companies are still limited to point AI experiments, the MacPaw case shows a different approach: not individual tests by enthusiasts, but an attempt to massively rebuild the routine of teams around automation. That is why this experiment is interesting not only as an internal initiative, but also as a signal about how Ukrainian product companies can translate AI from the category of a fashionable tool into a working infrastructure.
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