Ketchup vs Jellyfish: Engineering Intelligence vs Surveillance
Ketchup vs Jellyfish: Narrative vs Metrics
Engineering Management Platforms (EMPs) like Jellyfish, LinearB, and Pluralsight Flow have dominated the market by measuring "Engineering Efficiency."
But developers hate them. Why? Because they feel like surveillance.
| Comparison | Jellyfish / LinearB | Ketchup |
|---|---|---|
| Core Metric | Cycle Time, PR Pickup Time | Momentum, Narrative Impact |
| Interface | Dashboards & Charts | Video Recaps & Written Briefings |
| Developer Sentiment | "Big Brother is watching" | "Wow, my work looks cool" |
| Time to Value | Months (needs historical data) | Seconds (Day 0 Value) |
| Shareability | PDF Reports (Internal only) | Cinematic Video (Viral/Social) |
The Problem with Pure Metrics
Knowing that your "Cycle Time increased by 15%" is useful data, but it doesn't say why. Did you work on a complex legacy refactor? Did you mentor a junior dev?
Charts hide the context.
The Narrative Engine
Ketchup focuses on Contextual Intelligence. When Ketchup sees a drop in velocity, our Deep Dive engine analyzes the code to find the cause:
"Velocity slowed because the team spent 40% of time paying down tech debt in the
authmodule, reducing future risk."
That is a story a CTO can defend. A chart showing a red line is just an excuse to yell at people.
Conclusion
Use Jellyfish if you want to optimize the process. Use Ketchup if you want to understand the people and the product.
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