How we developed a Machine learning mentorship platform
We use a Machine Learning algorithm to predict the best fit and to create the most extraordinary experience. So basically, we match mentors with mentees at the appropriate seniority level and help them go through the process and the stages.
We use an algorithm that is called bayesian network and it is basically getting all the possibilities of what could be a best fit, a best match. Currently, it takes quite a lot of time to make one match because we focus on really good matches and what is important is not the product or all the features, but what experience you create and how these users are feeling and if you really make any difference in their lives.
How agility works in our team
We have weekly meetings with different people from different sectors. If you take a person that is in the financial sector and then you have a developer, they have totally different points of view so we discuss the next steps. This helps us align our priorities in business, in product, and every part of the business and then think about what is really important and where the foundations are.
Then, we implement something and we test with users.
You just try, test, see the feedback and then you go back, test again, get the feedback.
That kind of feedback loop really makes sense, especially if you are a startup because you have to be able to, if you want, break stuff quickly, learn and improve and that’s how you get to the real point.
The importance of failure
People need to switch their mentality when it comes to the word failure: from negative to positive. Test, build, break stuff very quickly: you move faster and that’s how progress happens.