Nineteen years of finding what's broken, one year of finding who fits
Lida spent nineteen years in QA before she gave recruiting a chance.
What she found out was that this job used the same instinct her old one did, aimed at people instead of software: she likes connecting with people and helping them, which is what pulled her toward being the go-between for recruiters and the candidates looking for work.
What specifically drew her to Tech Tree was the platform's automation and AI layer, seen against the alternative she already knew: manual Boolean search on LinkedIn. Tech Tree let her pull in her existing LinkedIn network and immediately surface which connections were relevant to open roles, plus run precise searches and test-fit a single candidate against a role in a way she says she'd never seen elsewhere.
So, what I found interesting in Tech Tree is that this automation, the AI, everything that was developed with the tool that's used for recruitment, it's absolutely amazing and is changing a lot the traditional way of recruitment.
An hour or two, after everything else is done
Lida's week doesn't have a fixed slot for TechTree. It fits around whatever else she's doing that day.
I am using it like every day. I do it mainly after I'm finishing with my other jobs, other tasks. I dedicate it like one, two hours per day.
The LinkedIn connection is what makes that time count for something: it surfaces people already in her network who are relevant to open roles, without her having to go looking for them from scratch.
She doesn't limit herself to candidates who are actively looking. When she knows a role is better than what someone already has, she'll go after them anyway.
I do head hunting also for the people that are already having a job, because I know the offer is better than what they have. In some cases, I know for sure.
Finding the right fit, not just a fit
Lida's clearest description of how she actually works a candidate isn't one placement story. It's what she does when the first role isn't right.
The way I connect with them, how I try not to convince them if this role is not a fit, maybe there is something else that is better. I'm just trying to find what exactly they need, what exactly they prefer.
Rather than move on, she keeps looking on that candidate's behalf.
I don't give up. I try to see if something else is good for them.
She names that persistence, more than any single search, as the actual source of whatever success she's had, and credits it simply to liking the process of connecting with people.
What AI can process, and what it can't hear
Asked where AI helps and where it doesn't, Lida draws the line at the interview itself. A model can read a document. It can't read a person.
It cannot understand the social issues, the political issues. There are sensitive cases and I saw some roles where we needed specific set of skills and location. Human touch is not yet to be replaced because we can understand differently when we screen - the tone of the voice, gestures, body language and all these things. I don't think that AI can really understand that.
She's specific about what that costs when it's skipped, not just cautious in the abstract: a model can only judge a candidate from what's written on a page, while an actual conversation reveals whether someone is nervous, whether they really have what the role needs, and whether they're stretching the truth about their experience.
We sometimes misjudge and we don't give a chance to the person to explain the experience and how it was done. Not all the instruments are created equally. In some we have the details, in some we don't have. And sometimes LinkedIn is not aligned with the resume.
Passion first, and don't judge too fast
Asked what she'd tell a recruiter thinking about joining, Lida goes to how you treat people before how you use the tool.
To do it with passion, first of all. To understand everybody's needs, everybody's requirements. Don't lose the human touch, the human behavior. Be empathic with the people.
Her caution on AI isn't a rejection of it: use it, but don't rely on only one source of truth, and don't let a fast rejection stand in for actually hearing someone out.