Software estimation is hard. And when done poorly, the negative impacts are limitless: business planning miscalculations, lack of trust between stakeholders, stress around launches, death marches followed by bugs and technical debt, loss of good talent and difficulty hiring… Those are problems all the pizza and foosball tables in the world won’t solve.
Leveraging the high usability of Dash Enterprise, we were able to build a machine learning tool for product managers to run their software teams in an agile and realistic way.
And here is how we built it, using the AE Studio agile product development framework:
Congrats, your team is growing! You need to hire a developer (or developers).
While it’s ideal that everyone feels involved in the process of picking their new coworker, it can be more challenging for non-technical founders or team members.
Here is some help to navigate the in-person interview for a technical position and get as much relevant information to hire your next great teammate!
This article is a summary of this lengthy, but oh so amazing, piece about how badly performed A/B tests can produce winning results which are more likely to be false than true. The bad news? You can really put your business at risk with bad A/B testing.
Let’s say you are trying to answer the following question: are adult dogs or kittens heavier?
You might want to weigh more than 1 kitten and 1 adult dog, because if not, you have a real chance of picking an extraordinary small dog. (Have you seen Yuki, our office dog?).
Statistical significance is…
To do so, you have to know who your users are. For instance, if your product services remote workers, go on Slack groups and forums dedicated to remote work. You can also look for full-remote companies and connect with their users on LinkedIn. Or go to a local café and ask the people working on a laptop.
The typical “Starbucks technique” is not always adequate though. …
Holiday parties are just around the corner and you have no idea which wine goes with what. Most importantly, you don’t want to spend a fortune on a bottle which will be disappointing. Follow this advice and hedge your bets at the store.
Pinot Grigio drinker? You probably like dry wines. Pick a Sancerre or a Chablis, you won’t be disappointed.
Chardonnay drinker? You will want something a little sweeter. Try a Riesling for something tangy and aromatic.
The lighter the color the better the rosé. …
Women leave their jobs 2.5 times more frequently than men. The quit rate in the tech industry is 17% for men vs. 41% for women.
So, what should we do to encourage women to stay? I will use the same format as for my last article here — sharing practical, immediately actionable advice, in hope to make it available to as many people possible.
Obviously, don’t harass women. Chances are not a lot of people who read that far are guilty of that.
But sometimes, the line is harder to draw. Just keep in mind that some people are not…
On many occasions over the past few years, I had conversations with male friends, coworkers and managers about the recruitment of women in the tech industry.
I’ll spare you a full page of statistics as we all agree with the facts: there are not enough women in tech (only 24% of computer scientists are women) and they tend to leave more frequently from their jobs (the quit rate is 17% for men vs. 41% for women).
These are the two sentences I heard most often during these conversations:
“But we want to hire women!”
“There are not enough female candidates.”