π About recruitment
The recruitment process is a key process that has a tremendous impact on your team.
There are so many aspects, still, to keep it simple, here are some key phases I will focus on today :
- π’ Communicate about the job opportunity, make it appealing and describe what's it's all about
- π Review candidates submissions (curriculum, motivation letter,..)
- π€ Interview candidates
- βοΈ Choose the new collaborator
The ambition of this post is NOT to detail the whole process, but just to point some things that, from my point of view have a huge impact on the "recruitment experience".
π In this experience, both recruiters and candidates experience matters a lot, in various ways. π
My bet (and past own experience) is that:
both experiences must be carefully delivered, and... fun fact, has a continuous impact on the daily life & activities of the team.
βΎοΈ Make it continuous
So if it has a continuous impact (making it continuous is a key factor), here was the question I managed to created :
"How to build something that has continuous benefits... with less efforts... or even better totally effortless for you and your team ?"
πΏ For impatients
πΉοΈ Play with the ChatBot : https://bit.ly/4da7Ct9
π‘ Inception journey
In this demo, you'll see how I:
- π€ Got the main idea,
- π Started to work on this process,
- πͺ Started to build a dedicated assistant
- π Collected the data
- π Prepared & patched data
- π Delivered the experience
-
π€© Implemented incremental loops of -
git
based - improvements
π° Benefits
Candidate perspective : the "left-shift"
- Preview the culture of the team
- Better answers at very early stage of the process
- Self-training opportunities w. ChatBot
- Curriculum Vitae tuning: focus on the most relevant skills
- Motivation letter eval/enhancement based on chatBot answers
Recruiter side
- Better introspection about what matters the most
- Find "holes" in the description (the ones that may cause LLM hallucination because of lack of knowledge)
-
Deliver better answers to candidates, earlier and without bias : the assistant answers with the same
LLM
and the same data to all - Challenging ourselves and our own team : does it match reality ?
- Does it make me/us want to work on the team ? If yes or not... Why ? Why not ?
- Ask the team if it really matches reality ? ... If not: why ?
- Make the vision clean: the cleaner the vision, the cleaner the data... the better the assistant
πΈ About on-boarding
Onboarding is a crucial process that you may face during turnover, for example:
- As part of the recruitment process
- Internships
- Welcome colleagues for a limited period of time on a very specific project
- Just let people know what you do
- ...
π and it comes at a cost.
The more you have to perform on-boarding, the more energy you and your team spend at something else than your primary goal : create something new, achieve things.
So, in the real world..
sharing knowledge has a cost, an impact on the core team who often shares the same information
again and again... and generally:
"who gives a f@%#k about wikis on how to discover & learn a team's culture ?"
π Putting the AI assistant in the team helps a lot to cover the most common questions.
π° For Core team
Building the assistant is a collaborative effort:
- Better knowledge of the team's culture by collaborators
- Easier answering of daily incoming questions
-
Apply classical
git
driven collaborative and reviewing workflows (issues, Pull Requests, discussions & polls, review process,...) - ...
π Further : give it a try
Hopefully these steps and experience could help you imagine something to enhance your recruitment experience.
I've put minimalist elements... my advice would:
"Give it a try, experiment and see what happens: you and your team won't regret it."
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