Re:Show HN: TinyFish Web Agent (82% on hard tasks vs. Operat...
by codebyron on Thursday February 12, 2026 @12:44PM
(#46992173)
The 15-point drop from easy to hard is the number that stands out to me.
That suggests the architecture handles state accumulation across steps without compounding errors — which is the thing that kills most agent pipelines. Every other agent here shows exponential degradation as task length increases, which is what you'd expect from a naive screenshot-action loop with no error recovery.
Looking at the cookbook repo — are you doing any kind of structured DOM extraction before passing to the model, or is this pure vision? Curious whether the hard-task performance comes from better perception, better planning, or better recovery when an action doesn't produce the expected state change.
That suggests the architecture handles state accumulation across steps without compounding errors — which is the thing that kills most agent pipelines. Every other agent here shows exponential degradation as task length increases, which is what you'd expect from a naive screenshot-action loop with no error recovery.
Looking at the cookbook repo — are you doing any kind of structured DOM extraction before passing to the model, or is this pure vision? Curious whether the hard-task performance comes from better perception, better planning, or better recovery when an action doesn't produce the expected state change.