Several questions remain around the impact of AI in the software development industry. Software engineering increases in productivity, though, is an observable outcome. The ease of creating code and applications continues to permeate engineering roles and is starting to migrate to citizen developers and business users.
Taking analogies from other roles or industries, it would be unheard of for financial and accounting professionals not to use Excel to accelerate their planning and modeling, or for lawyers not to use word processing software to crank out more and higher-quality agreements in no time. Knowledge workers would get more productive with software, and more so with GenAI-native software.
The productivity gained by software developers when complementing their work with AI tools is relevant and expected to continue to increase.
The industry is communicating a 25% to 30% productivity increase this year. As AI tools and platforms continue to improve (i.e., GitHub Spark announcement and constant improvements at Replit, Cursor, plus other SDLC-related tools, etc.), we expect a significant acceleration in productivity, to the point where a top quartile software architect could manage multiple AI agents creating functionality, reflecting multiples in performance-adjusted output.
Meta has been active in hiring top AI researchers at reported compensation reaching $100 million. Given Meta’s comp for high-performing engineers at $1 million, it does not seem crazy that they can bring forward these talent decisions at exponentially high comp levels, signaling how they view the world in 2-3 years for top-performing technical architects.
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Enterprise digital transformation needs and expectations will continue to increase going forward. It seems the software and services industry capabilities should be able to deliver on these higher expectations.
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