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flavianh

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blog.buildtosell.org 2y ago

Productivity in software development: the lean response to McKinsey

flavianh
1pts0
buildtosell.org 2y ago

Beyond features: crafting apps users love

flavianh
1pts0
buildtosell.org 2y ago

Three common mistakes we make with software bugs

flavianh
2pts0
github.com 2y ago

LLPhant – A Comprehensive PHP Generative AI Framework Using GPT4

flavianh
1pts0
buildtosell.org 2y ago

Three anti-patterns in bug management

flavianh
2pts0
news.ycombinator.com 2y ago

Ask HN: How do you measure eng team productivity?

flavianh
8pts17
buildtosell.org 3y ago

Why agile is not enough to build great products

flavianh
1pts0
buildtosell.org 3y ago

Achieving zero customer-reported bugs in 3 months

flavianh
1pts1
github.com 3y ago

Cadl: A language to describe APIs and generate schemas

flavianh
3pts0
news.ycombinator.com 3y ago

Ask HN: How is your company training you to become a better developer/engineer?

flavianh
97pts149
flowingdata.com 3y ago

Life Satisfaction and Age

flavianh
1pts0
buildtosell.org 3y ago

Three months to change a product concept and increase retention

flavianh
1pts0
julesblom.com 3y ago

Understanding react hooks through a timeline

flavianh
1pts0
buildtosell.org 3y ago

User errors: are we dealing with idiots?

flavianh
1pts0
buildtosell.org 3y ago

User errors – they are not just idiots

flavianh
2pts0
buildtosell.org 3y ago

Startups Need More Than Luck to Succeed

flavianh
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buildtosell.org 3y ago

The Joy of Fixing Bugs

flavianh
2pts0
blog.sicara.com 8y ago

Bokeh vs. Dash, which is the alternative for Shiny in Python?

flavianh
6pts0
blog.sicara.com 8y ago

Top articles in data in October, handpicked with love by data scientists

flavianh
1pts0
blog.sicara.com 8y ago

October articles on deep learning and data processing picked by data scientists

flavianh
5pts0
blog.sicara.com 8y ago

Importing a Jupyter notebook in another to present data analyses

flavianh
4pts0
medium.com 8y ago

Artificial intelligence business tools you can use today (2/3 – continued)

flavianh
4pts0
blog.sicara.com 8y ago

Articles in data published in August, handpicked with love by data scientists

flavianh
4pts0
blog.sicara.com 8y ago

A short tutorial on genetic algorithms

flavianh
2pts0
medium.com 8y ago

The Secrets of Successful Startups

flavianh
4pts0
medium.com 8y ago

Top articles in AI published in July – half of them business-friendly

flavianh
2pts0
medium.com 8y ago

Top articles in machine learning and AI in July, handpicked by data scientists

flavianh
9pts0
medium.com 9y ago

A comparison of the most used charting libraries in JavaScript

flavianh
2pts0
blog.sicara.com 9y ago

Top articles in data in the last month, handpicked with love by data scientists

flavianh
3pts0
medium.com 9y ago

My Favorite SEO Hack on Medium – Take Control Over the URL

flavianh
9pts0

Interesting to note that two of your decision points are on "shipping product improvements at a regular cadence" or "shipping so slow that it's negatively impacting customers". Both relate to a productivity discussion, ie "how to define what it means to 'ship' as an engineering team". In that sense, we're aligned on why it's important to measure productivity. It would however be a mistake to try to optimize for maximum productivity in a vacuum, but note that this is not what this thread is about. This thread is about the unit of measurement that people use in their teams. In that sense it's purely a research / curiosity question

I agree 100%, you need to have a strong product foundation to turn good output into good business outcome. A productive team that delivers features no one wants is pointless. Both go hand in hand, but as far as engineering management goes, it is still a challenge to find a good productivity metric. What’s used in your organization @przeor and what do you think of it?

Don't get me wrong, pairing has merits. Let me give you an example. I'm in the middle of going through type challenges in Typescript (https://github.com/type-challenges/type-challenges). If I knew absolutely nothing about types, pair-programming would have helped me get started. But some of these challenges teach me important insights about the Typescript typing system that take time to wrap my head around. You don't get this amount of system 2 focus when pair programming because pair programming is (to a large amount) communication.

You're right in a way, but you're missing the "10x compared to what?". Consider the 1x baseline as being the median productivity of your development team (which is definitely hard to approximate, but for the sake of the exercise let's take 'value-added tickets per developer' [which excludes bugs/rework]). Then the goal is to do 10x on this median in a reasonable amount of time. Rince and repeat.

That's an interesting try! I think the default assignment is done by reference as well, so when i changes in the loop the default value changes as well? Similarly to methods=[]. Can't say for sure though. The solution I give in the article is the only one I could come up with, I'm interested if you find another one :)

Article author here. I agree with your point, I shouldn't have been so cautious. I consistently observed people being faster when using debuggers and I wanted to give it a test on this problem. Most people don't see that they can get a significant speedup in using debuggers, so that sentence wanted to give a sense on how much quicker you can be. I'd be happy to hear of a better way to convince a non-debugger user that he could have debugged this code faster with a debugger!