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A tool to help you manage technical debt

Hacker News

A tool to help you manage technical debt

Caribou helps software teams manage long-term technical migrations in their projects. For example migrating from one networking library to another or migrating a codebase from one architecture pattern to another. These changes usually happen over a span of a few months and without any tooling, they can be difficult to manage. It’s difficult to understand how much progress has been made, what is still left to do and who are the engineers helping move the migration forward. Caribou was built to solve these problems. So how does it work? In simple terms, Caribou is a Github application which, after being configured, monitors all the changes in your repository and displays a dashboard with the progress of specific migrations along with who is contributing to these migrations. Caribou allows you to define all sorts of migrations using an easy-to-use rules engine; for example changing the project architecture, replacing a library or changing some coding conventions. You can get inspired by our examples in the docs section. Currently, Caribou is still in Beta. We believe the product can provide a lot of value as it currently stands, but there is more functionality that we’re looking to add in the coming months such as Slack integration and Pull Request comments so that engineers can get valuable feedback in their PRs. You can checkout Caribou here: https://www.hellocaribou.com

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Product HuntOn track for Day 1 leaderboard · Strong signals: slack, using, coding · Missing: mac, agents, macos
73%73% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
51%51% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: lua, ide, io · Missing: https docs, excited, just released
49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: month · Missing: mobile apps, ios, personal
36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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