GitHub and Andela have trained 3,000 engineers on GitHub Copilot through Andela's AI Academy, targeting developers in Africa and Latin America working on active production systems. The program, two years in the making, draws from Andela's 5.5-million-member talent network. It is not a certification exercise. Copilot was embedded directly into IDE environments, pull request reviews, and live refactoring work, evaluated against real production constraints from day one.
The article is worth reading for the specific failure mode it identifies: broad AI tool provisioning without role clarity, defined job profiles, or evolving review standards causes adoption to stall. Andela's counter-model selected developers based on direct relevance of AI to their responsibilities. Senior engineer Daniel Nascimento, 25-plus years of experience in Brazil, describes using Copilot to generate unit test coverage on legacy code before any refactoring, creating safe boundaries in systems where no coverage previously existed. Stephen N'nouka A' Issah, a React developer working across Cameroon and Rwanda, found the tool handled advanced patterns and legacy code at a level he did not expect.
The structural problem the piece addresses is infrastructure inequality: unreliable connectivity, high cloud tool costs, training content designed for well-resourced environments, and contract-based work that leaves no time for reskilling. The productivity numbers are partially cut off in the source, but the documented outcomes include faster system orientation, more confidence on ambiguous work, and reduced setup time. The model Andela built is described as transferable, whether you are integrating AI tools across a team or experimenting independently inside a production codebase.
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