17 verified briefings on Cto. Each story includes a plain-English summary, why it matters, and the concrete action engineering teams should take.
A new survey of 520 tech leaders reveals they are not worried about being locked into a specific AI model. The real concern is the surrounding infrastructure and tooling, which is much harder to change once implemented.
A top CTO argues that hiring for personality and problem-solving ability creates stronger, more resilient engineering teams than focusing only on technical skills. This approach is crucial for navigating crises and integrating AI.
Salesforce claims its AI platform is a $1.2 billion business, but a new report finds customers are struggling to get real value. Many cite poor data readiness and immature AI agents as major roadblocks to adoption.
New research shows most UK tech leaders now view network outages as a critical business problem, not just an IT issue. Growing complexity in vendors and platforms is making it harder for technology to drive business transformation.
Companies rushing to adopt AI are finding their biggest hurdle isn't the new technology, but their old, legacy systems. This technical debt prevents the data access and speed that modern AI models require to be effective.
Autonomous databases promise to manage themselves, but they won't eliminate the need for human experts. Percona's co-founder explains that while automation is transforming data management, human oversight and strategic input remain essential for success.
A new analysis argues that AI models are just complex code. This means prompt engineering can't make them smarter, only better at accessing what they already know—a key limit for developers building reliable applications.
Enterprise software vendors agree that AI agents require deep context to be useful, but they are divided on how to provide it. The key debate is whether companies should integrate AI into existing systems or undertake a risky strategy of rebuilding their entire infrastructure from scratch.
Many companies struggle to get value from their AI investments. The issue often isn't the technology, but a leadership gap in connecting AI initiatives to clear, measurable business goals and a company-wide data strategy.
The rise of AI is forcing a strategic shift in workload placement. Companies are moving beyond simple cloud-first approaches to consider a mix of public cloud, private infrastructure, and hybrid models, driven by nuanced factors like cost, performance, and data governance.
Uber exhausted its annual AI budget in just four months, prompting the company to implement spending caps for employees using AI tools. This move highlights the escalating and often unpredictable costs of adopting generative AI technologies at a large scale for any business.
LinkedIn is building a unified platform to manage its AI agents for engineering tasks like coding and UI testing. This approach moves beyond scattered AI tools, creating a scalable system for complex, multi-agent workflows.
Top AI talent is increasingly choosing employers based on factors beyond salary. They prioritize access to powerful computing resources, the freedom to experiment, and the ability to make a significant impact. Companies that focus only on platforms and governance risk losing their most valuable AI experts.
A new IBM report finds two-thirds of IT leaders are accountable for AI they don't fully control. This growing "accountability gap" stems from uncontrolled AI agent deployment by employees, creating major governance and security blind spots.
A new survey from CIO.com shows AI remains the top priority for CIOs, but the focus has shifted. CEOs now expect technology leaders to move beyond experimentation and use AI to drive revenue, improve business resilience, and deliver tangible value across the organization, redefining the CIO's role.
Many CIOs find they can't leave their roles because they haven't prepared a successor. Their top deputies are often skilled architects but lack leadership training, a phenomenon known as the "Architect's Trap." This oversight in succession planning creates a critical leadership gap in many organizations.
Tech leaders often treat board meetings as one-way presentations, focusing too heavily on technical details. An REI CIO's experience shows the pitfall of this approach, highlighting that boards expect a strategic dialogue, not just a detailed report on roadmaps, to guide the company's direction effectively.