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News & Blogs

Agent production failure forensics debugAI Agents

Apr 25, 2026

Four forensics when a production AI agent fails

A founder messaged us at 11pm on a Friday: the AI agent his team had launched on Monday was down. Customers were complaining, the team was panicking, the on-call engineer had no idea where to start. Here is the forensics order Sapota walks through when an agent fails in production, and the four most common culprits.

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Late interaction token mesh networkRAG Systems

Apr 22, 2026

When recall plateaus: the late-interaction technique most teams skip

A team had been swapping embedding models for two months trying to push retrieval recall past 60%. Each new model gave a couple of points then plateaued. The bottleneck was not the model. It was the architecture: a single embedding per chunk cannot match what token-level interaction can. Here is when ColBERT and ColPali earn their keep.

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Mobile stack decision frameworkMobile

Apr 22, 2026

Mobile stack decision: FlutterFlow vs React Native vs Flutter

A founder asked us last month which mobile framework was 'the best'. The answer is none of them. Each fits a specific set of constraints, and picking the wrong one usually costs 2 to 4 months of rework eighteen months in. Here is the decision framework Sapota walks every founder through, and why we train our mobile engineers across all three stacks.

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Agent latency code optimizationAI Agents

Apr 21, 2026

Cutting agent latency from 30s to 8s without model swap

A founder's chat product had a problem: users were abandoning the conversation before the AI agent finished responding. The p95 latency was 31 seconds. The team's instinct was to switch to a smaller model. The actual fix was four changes that did not touch the model at all. Here is the latency stack most teams overlook.

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