Exploring AI Benchmarks: ideas worth trying

[leahdig]

I wanted to start a broader ideas worth trying thread around AI Benchmarks.

A useful angle is prompt design, but it also connects with limitations. Different tools and workflows can produce very different results even when the goal is similar.

It would be interesting to compare practical examples, experiments, setups, or lessons that show where AI Benchmarks is genuinely useful and where it still needs improvement.

 

[adam_2iyv]

I think benchmarks and ideas is the key part of this topic. A practical approach is to define the outcome you want, test it with a small example, and then check quality, speed and reliability separately. That way you can improve the workflow without losing track of what caused the improvement.

 

[alicethelab]

The point about benchmarks and ideas is interesting. In practice I would keep the first test simple, record what worked, and only add extra complexity if it solves a specific limitation. It is usually easier to troubleshoot when each change is tested on its own.