I haven't yet tried to solve truly complex algorithmic problems.
Generally speaking, if the problem is common, the model has likely already been trained to solve it.
If it's truly complex and/or specific to my needs, I can try using a reasoning model to think through a solution before moving on to implementation.
I use the agent to conduct research, find resources to understand the complexity, best practices, feedback, etc., and to write a Markdown analysis file on the topic.
Then I can use this file as a basis to precisely define what I want to do and brainstorm with the agent in thinking mode. The more the task is described and defined, the more accurate the result will be.
Generally speaking, if the problem is common, the model has likely already been trained to solve it.
If it's truly complex and/or specific to my needs, I can try using a reasoning model to think through a solution before moving on to implementation.
I use the agent to conduct research, find resources to understand the complexity, best practices, feedback, etc., and to write a Markdown analysis file on the topic.
Then I can use this file as a basis to precisely define what I want to do and brainstorm with the agent in thinking mode. The more the task is described and defined, the more accurate the result will be.