The #1 Rule for Building AI Agents in 2026 | Yutori, Abhishek Das
In a Nutshell
Current AI web agents fail on multi-step workflows due to compounding errors, even at 90% per-step accuracy, making first-try reliability non-negotiable—Yutori rejects tolerance for retries or non-determinism. Yutori, co-founded by AI researchers like Abhishek Das, builds trustworthy agents for web tasks via rigorous evals, self-correction, backtracking, and proof-of-work transparency (e.g., Scouts product shows agent steps). Success demands 80/20 feature prioritization blending user feedback with intuition, team dogfooding, and obsessive craft to create magical, reliable products.
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There are about 100 different agent products claiming to do anything on the web, but they often fail on the first try. For a 10-step, 20-step, or 50-step workflow, even 90% accuracy per step leads to rapid compounding of the 10% error rate, resulting in very low overall success rates. This is why technology isn't ready for long-horizon workflows. We've started normalizing tolerance for non-determinism and low reliability in products, but this is unacceptable for agentic products. > If it's not good enough to work on the first try, it's not good enough.
Abhishek Das is co-founder and co-CEO of Yutori, building agents that take actions and complete tasks on users' behalf on the web, freeing users to focus on meaningful work. The three co-founders are all AI researchers by background. Investors Faith Lee and Jeff supported them. Abhishek comes from a family of doctors and medical practitioners but is scared of blood, so he pursued engineering instead.
Science and the scientific process appeal to him: hypothesizing, designing experiments to validate/invalidate, drawing conclusions, and iterating. He attended IIT Roorkee for undergrad, meeting some of the smartest people he knows. In first year, he got good grades in electrical engineering (geared toward power systems), but lost interest and rebelled by stopping heavy focus on it, marking a significant life fork.
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