What GitHub data reveals as the top priorities for modern engineering teams.
Published via GitHub Executive Insights
The developer tech stack is shifting, which means that the notion of who a developer is and what they do is evolving, too. With powerful AI models rapidly changing the development landscape, the most nimble business and engineering leaders are embracing generative AI to keep pace.
Our latest white paper, Engineering Leadership in the Age of AI: Insights from GitHub, distills findings from our 2024 Octoverse report—which explores all public data from GitHub’s global base of developers—to give leaders like you the knowledge to navigate these changes and leverage them for strategic advantage.
You’ll also find critical insights into the latest trends in AI, the rise of Python, and the growth in global developer activity, enabling you to make strategic investments in the technology and talent that will help you win.
What’s inside the white paper:
This asset was designed to be your comprehensive guide to understanding the current landscape, making informed decisions, and giving your teams what they need to excel in the age of AI.
Key takeaways for business and engineering leaders:
Generative AI has moved from a curiosity and area of experimentation to a core reality in today’s software development lifecycle. With the emergence of more powerful AI models and agentic AI, the scope of what these technologies can help engineering teams achieve is only expanding.
Read the white paper to learn what this shift means for organizations, along with strategic insights on how to guide your teams in the months, quarters, and years ahead.
Want to learn more about the strategic role of AI and other innovations at GitHub? Explore Executive Insights for more thought leadership on the future of technology and business.
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4