In-product human-to-human chats.
Customer conversations.
Agent-to-Agent conversations.
Employee-to-Agent conversations.
More conversations recorded.
Synthetic text datasets.
The way Splunk owned system logs.
The way CrowdStrike owned security logs.
There will be an application that owns conversation logs.
We call that a Conversation Data Platform.
Rippit analyzed 20+ Gong calls in one shot, instantly connecting the dots in customer prep to nail high-stakes panel sessions.
I was moderating two panels at our customer conference in San Francisco the other month — one with Checkr and one with SpotOn.
The day before, I was finalizing my questions and deck, and I realized my notes from my prep calls with the customers had some logical gaps.
I went into Rippit, filtered our Gong table to all Checkr calls, and started asking questions using AskRippit. I did the same with SpotOn.
Afterward, I asked the marketing team a simple question: “Where else could I analyze 50 Gong calls in one shot as easily as Rippit?”
If you downloaded the 20 calls out of Gong 1 by 1 and then uploaded it into Claude, you have a chance, but for reasons I’ll share later — you lose accuracy.
That led me to think about how I prepared my deck. I used Gamma instead of Google Slides. I tried Google Slides first, but the AI wasn’t good enough — so I was willing to pay for Gamma. For me, in my role, I’ll pay for whatever helps me deliver the best presentation.
The same goes for conversation analysis for my use cases — I’d rather pay for Rippit than try to hack it in ChatGPT or Claude.
Productivity is the wrong frame. 10x comes from judgement — and judgement is what AI improves most.
The 10x engineer isn't more productive because they squeeze more output in the same time as the 1x engineer. The 10x engineer is more creative and a better problem solver. The person has better judgement.
This is true for every person, in any role.
This is what AI will help people do the most.
AI can improve judgement by giving a person new insights they didn't have before. AI can improve judgement by helping you run experiments and prototypes faster.
Using Rippit is one way to improve judgement — you can get instant insights into a dataset that wasn't possible to analyze before.
Be curious and discover secrets with AI to improve judgement.
Don't focus on incremental improvements. Seek 10x.
Why does Claude Code outperform standard chat? LLM tooling and environments—not just the model—are the keys to great AI outputs.
When you use Claude Code, you see the same model (ex. Opus 4.6) is used across Claude Code, Claude Cowork, and Claude Chat. Then why does it perform differently? The tools and environment.
Think of the model as the brain and the tools as the arms, hands, legs, and feet.
Claude Code has many coding-specific tools.
What you need for your task will require specific tools, environments, and optimizations too.
Designing the best tools and environments is going to be the name of the game.
For example, if you want to build an analytics system, you connect Claude to Snowflake. In that case, Snowflake is the tool. Snowflake is the hard part of the problem and 99% of companies don’t have the engineers to build products as technically difficult as Snowflake.
This has become more obvious since the code behind Claude was leaked the other week and people studied it - but it’s not obvious to the regular person blown away by Claude Code and “Vibe Coding”. When you experience a crazy, mind-blowing output, it's hard to separate the 'AI' from the tools and systems doing the mission-critical heavy lifting.
The world of Tool Design is going to go through a lot of trial, iteration, and realization — we have our differentiated POV but the playbook is being written.
Where conversations become
insights
actionable data
business intelligence
enterprise visibility
insights
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