Overthinking Hurts AI (Sometimes) · Automate What Academy

Aug 15 • 🤖 AI

Overthinking Hurts AI (Sometimes)

Turns out, giving AI models more time to “think” doesn’t actually make them smarter, in fact, it can make them worse.

Anthropic just dropped some eye-opening research showing that large language models perform worse on certain tasks when allowed to reason longer, a phenomenon they call “inverse scaling.”

This is huge because most of the AI industry assumes that throwing more compute at a problem (especially during test-time) will improve accuracy and reasoning. But this research shows that more isn’t always better, sometimes, it just reinforces bad patterns or leads models off track.

One practical takeaway: If you're building automations or tools that rely on complex AI reasoning (and using tools like Claude or GPT), don’t just assume longer processing = better performance. Test across different reasoning lengths and keep things concise when possible, especially for simple tasks.

I’m really curious… have any of you noticed “overthinking AI” behaviors in your projects? Maybe a time where more time or context actually made things worse?

Read the full article here: https://links.tldrnewsletter.com/lwwuXT

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