Projects don't just fail because of bad luck; they fail because we can't calculate the ripple effects of change as quickly as ...

This week, an exercise in separating truth from hype. I am old enough to remember when generative AI (genAI) was the best thing since sliced bread — destined to solve any and all problems. But CIO.com ...

Until teams shift from asking “Where can we use AI?” to “Where are we spending time that doesn’t make sense?” projects will ...

Even as we emerge from generative AI’s tire-kicking phase, it’s still true that many (most?) enterprise artificial intelligence and machine learning projects will derail before delivering real value.

MIT’s latest analysis highlights a major gap between AI hype and real-world results. Many companies are investing heavily in ...

In many technical projects, failure is not caused by a lack of talent, but by a lack of structure. Despite the availability ...

The claim that “AI projects are failing” has become a familiar headline—and a valid one. But while the failure rate may be high, it’s not necessarily cause for alarm. In fact, understanding why these ...

SPONSORED CONTENT Most NFT projects that launched between 2021 and 2023 are no longer active. Discord servers empty or ...

Community driven content discussing all aspects of software development from DevOps to design patterns. Agile software development is one of the most proven approaches to building software and ...

Virtually every organization is trying its hand at AI, yet very few are seeing the payoff. Despite massive investment, most organizations aren’t seeing the results they were hoping for. According to ...

American enterprises spent an estimated $40 billion on artificial intelligence systems in 2024, according to MIT research. Yet the same study found that 95% of companies are seeing zero measurable ...