When teams start using AI, the most common assumption is simple. One strong model should be enough. It feels efficient, easier to manage, and less confusing. If the model is powerful, why not let it handle everything?
Why one AI model is not enough in real work Read More »
AI agents are having a moment. They plan tasks, reason across steps, and respond like a capable assistant. Demos look smooth. Early trials feel impressive. It is easy to think that once an agent is added, the work will take care of itself.
Then reality shows up. Tasks stall. Outputs need fixing. Humans quietly step back in. The agent is still there, but the workflow is doing most of the heavy lifting.
This is not because AI agents are weak. It is because workflows decide whether they succeed or struggle.
Why AI agents fail without strong workflows Read More »
Every week, there’s a new promise that AI will handle entire workflows from automating emails to managing complete projects. The hype sounds great, but a new benchmark from Scale AI and the Center for AI Safety shows a different reality.
In the study, AI agents were tested on real freelance tasks like writing, research, data entry, and design. Out of nearly $144,000 worth of work, the top model earned only about $1,800 completing just 2 to 3 percent of jobs successfully.
This doesn’t mean AI is weak. It means organizations are skipping the most important part of AI success: workflow design.
The truth about AI automation nobody tells you Read More »
