← Saturday, October 31 deck

10Opinion1 source posting

Theo Says High Effort on Opus 5.5 Beats Extra High Almost All of the Time

Julius convinced me to move from extra high to high on Opus 5.5 a week or two ago. He was right. This is better almost all of the time.

Context

Why it matters

A widely followed developer saying a lower effort setting works better could help users get good results from Claude Opus 5.5 while spending less time and money.

Theo runs the t3.gg developer channel and is a well known voice among web developers. Opus 5.5 is a Claude model from Anthropic. Effort settings let users choose how much reasoning the model does before it answers, and higher effort usually costs more and takes longer.

Sources

Deep dive

Theo posted on Saturday that someone he calls Julius convinced him to move from extra high to high effort on Opus 5.5 a week or two ago. He says Julius was right, and that the high setting is better almost all of the time.

The post is a personal usage tip rather than a product announcement or a benchmark. It does not say which tasks Theo tested, how he judged the results, or whether the change also saved time or tokens.

The post still drew more than 280,000 views and over 300 replies, which shows how many developers are tuning effort settings to get the most from Anthropic's models. Effort settings trade speed and cost against how long a model thinks, and users often assume the highest setting gives the best answers.

Theo's report suggests that more reasoning is not always better for everyday work. It is one developer's experience, and results may differ by task, so readers should treat it as an opinion to test rather than a settled finding.

What to expect next

Watch whether Anthropic publishes guidance on when to use each effort setting for Opus 5.5, or changes the defaults. Other developers may share their own comparisons, which would show whether Theo's finding holds across coding and writing tasks. Also watch for benchmark results that compare effort levels on cost, speed and quality, and whether other labs see the same pattern with their own reasoning settings.