🧑‍💼 Recruitment assistant: why, howto & long term continuous benefits

#ai #softwareengineering #management #productivity

💭 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 :

📢 Communicate about the job opportunity, make it appealing and describe what's it's all about
🔎 Review candidates submissions (curriculum, motivation letter,..)
🤝 Interview candidates
⚖️ 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".

👉 In this experience, both recruiters and candidates experience matters a lot, in various ways. 👈

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.

♾️ 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 ?"

🍿 For impatients

🕹️ Play with the ChatBot : https://bit.ly/4da7Ct9

💡 Inception journey

In this demo, you'll see how I:

🤔 Got the main idea,
🚀 Started to work on this process,
🪛 Started to build a dedicated assistant
📘 Collected the data
📝 Prepared & patched data
🎀 Delivered the experience
🤩 Implemented incremental loops of - git based - improvements

💰 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

💸 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
...

👉 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 ?"

👉 Putting the AI assistant in the team helps a lot to cover the most common questions.

💰 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,...)
...