10x Engineer, 10x Employee, 10x Person

Traditional business application software from 2000-2022 (e.g. software sold into HR, Sales, Marketing, etc.) has been primarily workflow automation tools — Salesforce started with SFA (Salesforce Automation), ServiceNow started with IT Workflow Automation, and Workday is HR workflow automation. 

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The core value proposition was coordinating large groups of people around a process.

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When you wanted to do complex data analysis — crunch lots of numbers, combine data from different data sources, etc. — you would push that data into a data warehouse (Teradata in the 2000s, later replaced by Snowflake) and layer it with a BI solution (like Tableau or, more recently, Sigma/Looker).

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SaaS apps that lived in the world of Security and Infrastructure were more likely data/infra apps from the beginning — companies like Rubrik, Crowdstrike, and Datadog fit this mold.

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The type of engineers and cultures you attract to build workflow apps versus data apps is materially different.

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AI requires a higher percentage of SaaS apps to become data apps. 

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99% of apps will die in this process because they have to build a fundamentally different engineering culture. Only 1% will survive.

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Rippit realized this three years ago and embarked on this journey — partly through our instinct of how SaaS needed to transform, and partly through a little bit of luck. 

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This also transforms my role, and I’m going through my own journey of survival. As a non-engineer, being the founder of a workflow app is significantly less technical and more S&M-oriented than being the founder of a data app. 

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My Monday morning meeting used to be the Go-To-Market kickoff and now it’s the Engineering kickoff. I’m working very hard to become as effective as I can at lower levels of product decisions — my ceiling here directly affects Rippit’s ceiling.

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.

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Think of the model as the brain and the tools as the arms, hands, legs, and feet.

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Claude Code has many coding-specific tools. 

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What you need for your task will require specific tools, environments, and optimizations too.

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Designing the best tools and environments is going to be the name of the game.

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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.

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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.

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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.

Pick things that compound over time.

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Wake up looking forward to the present.

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Talk about ideas and projects of the future. 

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Reminisce less. The good old days are ahead of you, not behind you.

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What ages like wine?

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To each their own.

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One hack is to have extremely low expectations to start. 

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The other hack is to reset your mindset today — no matter your age — and start over. 

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There's no better time to start the ascent than today.

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This applies to companies too — is tomorrow potentially better than today?

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Just Rip It.