Unlocking Perception into LLM-Primarily based Purposes by @ttunguz

Massive-language fashions have remodeled how thousands and thousands work together with merchandise : from buyer assist to code era to authorized doc evaluation.

These new engagement fashions invite customers by means of a meaningfully completely different product journey. Each software now speaks English. Understanding person conduct is crucial to constructing nice merchandise.

How ought to a product supervisor gauge the shopper expertise? A number of new challenges come up :

  • First, the fashions are non-deterministic which suggests generally the identical query phrased a bit differently produces unexpected results.
  • Second, customers can enter something they like which may result in mannequin drift & sudden outputs probably together with would possibly embody PII (personally identifiable info) or different delicate content material.
  • Third, how ought to a PM take into consideration the person journey by means of a dialog? What’s a profitable interplay? It’s not simple clicking by means of 5 screens. is a product analytics platform for LLM-powered functions. provides product builders an understanding of how customers have interaction with their merchandise and visibility into product efficiency, to allow them to construct higher experiences. detects the subjects of conversations ingested for analytics, after which charges the person satisfaction for every matter. Product builders can perceive how customers navigate their product and determine stronger or weaker product efficiency areas.

Within the video, a PM navigates by means of the UI to find the preferred themes, delve by means of particular person transcripts. Context additionally permits blocking & filtering of specific subjects, tracks specific key phrases , & manages PII. is built-in with Langchain to simplify deployment.

After we met Henry & Alex, the co-founders of Context, we met a workforce who had labored on a few of the largest merchandise globally, including managing conversations & safety on YouTube & engaged on a few of Google’s most significant APIs. Their backgrounds, working to unravel comparable issues, map nicely to serving to PMs perceive the person journey by means of new LLM-enabled merchandise.

We’re thrilled to co-lead’s seed with Google Ventures. As LLMs & chat grow to be a predominant new UX, instrumenting the person expertise will grow to be important to transport nice merchandise.

Should you’re constructing an LLM-enabled product & seeking to perceive person conduct & enhance these journeys, try

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