This blueprint serves as a strategic guide for CEOs striving to navigate the challenges of digital transformation and secure a prosperous future for their enterprises.
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For CIOs dedicated to leading their organizations through this dynamic era, aligning technology initiatives with overall business strategies is key to securing long-term competitive advantage.
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What are the tradeoffs using AI to learn and master a new technology? Does it work well for everyone? When should you turn to humans for instruction instead of AI?
I have used both AI and traditional instruction to learn new technology in the past year, but to better understand differences, I tried each in isolation for learning a new framework.
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While full-scale adoption is still years away, technology leaders should stay informed, develop quantum strategies, and explore partnerships with quantum technology providers. Companies investing in quantum research today will be better positioned to gain competitive advantages in the near future.
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Quantum computing is not just a future technology—it’s a strategic opportunity. Forward-thinking leaders should explore partnerships, monitor advancements, and prepare for a new era of computational power.
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For CIOs, CTOs, and SVPs of Engineering, code reviews are a strategic lever for improving code quality, reducing time-to-market, and fostering an engaged engineering team.
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At its core, the frontend developer toolkit is a comprehensive set of resources designed to accelerate and standardize the app modernization process.
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This green paper explores the strategies and considerations for modernizing these enterprise monoliths, outlines a comprehensive roadmap that addresses both the technical and organizational dimensions of modernization, and provides actionable insights for CIOs navigating this complex journey.
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As we navigate this evolving landscape, let’s lead by example, shaping a future where technology and humanity work hand in hand for the betterment of all.
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The EQengineered team shares their predictions for 2025.
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There is a lot of confusion about how useful Generative AI is in coding. Some say it’s a complete game-changer, and programmers either need to use it or eventually be replaced. Others, particularly senior developers, disagree strongly, only conceding a limited amount of tactical uses for repetitive tasks. Surveys have produced wildly different results for organizations. Some claim small improvements, while others claim extraordinary time savings.
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The evidence that generative AI cannot reason like humans is not at all a bad thing for the potential of software development. We probably do not want coding assistants to be just like human programmers.
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