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Developer First Engineering Metrics

Hacker News

Developer First Engineering Metrics

Engineering metrics for developers are becoming more popular and they going in a negative direction and I want to fix this with my developer first engineering metrics. Solutions like GitPrime (now Pluralsight Flow), GitHub Insights (formerly Gitlaytics) and other similar solutions are giving non-technical people a false sense that you can easily roll up metrics to quantify developer productivity. In the "The Space of Developer Productivity" [1] that was posted on HackerNews this week, it goes into great detail to explain that there are a lot of variables at play. In the business world, business intelligence is widely accepted and business leaders do not assume business insights will come easily. People are actually hired to generate business intelligence reports and I'm hoping this type of attitude is adopted for developer insights as well. There are a lot of variables at play, and it should be expected that leaders will need to work for meaningful developer insights. Right now, I'm still early in my research, but I believe impact based metrics is something developers and leaders can get behind. Rather than repeat what I've written before in another thread, you can learn more about my thoughts on impact based metrics at https://news.ycombinator.com/reply?id=26457072&goto=item%3Fid%3D26452550%2326457072 Like the saying goes, a single line change can take more work than a hundred, and that is ultimately what I want GitSense (my solution) to be able to show. If you want to play around with GitSense, you can do so at https://public-001.gitsense.com/insights/github/repos and if you want to install it, you can find the instructions at https://gitsense.com [1] https://news.ycombinator.com/item?id=26452550

Visit product View on Hacker NewsMar 19, 2021

Actual performance

6points

4comments

Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntOn track for Day 1 leaderboard · Strong signals: new, single, plain · Missing: mac, agents, macos

53%53% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

50%50% 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

26%26% 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.

Incorrect prediction on native model

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