When faced with a complex multi-step task, breaking it into sequential prompts can simplify the problem for the model.

Tasks often vary by type (e.

When different parts of a task can be done simultaneously, parallelization speeds up processing.

Complex tasks with unpredictable subtasks require dynamic breakdown.

Ensuring answer quality can be hard in one pass.

Some tasks have no fixed steps and require continuous control.

LLMs may make logical mistakes without self-review.

LLMs lack direct access to real-time data or calculations.

Certain problems benefit from alternating reasoning and action.

Large tasks often need an explicit roadmap.

Some problems can be handled by one versatile agent.

When workflows are large or specialized, multiple agents collaborate.

Writing boilerplate app code is tedious for developers.

Complex software tasks span many files and edits, which is error-prone.

Some tasks require controlling software or machines directly.

Sales teams need to engage prospects efficiently.

Handling high support volumes is expensive.

Keeping up with competitors manually is slow.

Personalizing content at scale is challenging.

Retailers must predict which trends will be popular.

Creating personalized trip itineraries is time-consuming.

HR departments receive many routine inquiries about benefits and policies that tie up resources.

Financial advisors need fast insights in client meetings.

Delivery companies must plan routes that change in real time.