AI agents are expected to replace many jobs in the near future, according to forecasts from McKinsey and Goldman Sachs. However, these agents are not as all-powerful as they may appear. In reality, they function more like specialized assistants—similar to travel agents—who perform specific tasks well when given clear, detailed instructions.

Large Language Models (LLMs) generate responses by predicting the next set of words based on the input prompt, training data, and context. The quality and accuracy of their output largely depend on how precise and well-structured the prompt is. Well-crafted instructions help reduce errors and improve the reliability of AI-generated content.

For those interested in building AI agents, a straightforward yet effective strategy is to teach the model to ask for help when it encounters missing information. For instance, if the AI doesn’t have access to live weather data, it can prompt the user to search online and provide the necessary details. This collaborative approach allows AI to extend its capabilities by working alongside humans.

With a growing number of tools and resources available, developing AI agents is increasingly accessible. With the right knowledge and support, creating these systems is well within reach.

For a more in-depth understanding and additional resources, you can read the full article here: https://slobodan.me/posts/ai-agents/.