The "Amazing Opportunity" Lie: Why Contingent Recruitment Fails Senior AI Hiring
Written by: Matt Reaney | Reading time: 7 mins
When "amazing" is just noise
"I've got an amazing opportunity for you."
I've said it thousands of times across 25 years. I trained teams to say it. And I want to be fair — I've had genuinely good clients, long relationships built on trust, placements I'm still proud of.
But the faceless contingent and PSL model doesn't work for senior technical hiring. In that world, "amazing" is usually just noise. Sometimes the focus quietly shifted from the right match to volume. To stay in the game and hit a KPI, I just needed your CV.
So we sold the dream. World-class tech. Growth, development, new skills. Pool table, gym, snacks (blah, blah). It was rubbish.
Why the contingent model produces bad shortlists
Because of what it pays for.
Contingent recruitment pays only on placement, which means the supplier's incentive is speed and volume, not accuracy. Four agencies compete on the same role with the same tools, so the rational strategy is to submit fast and submit plenty. Nobody is paid to hold a weak candidate back — so nobody does. That single mechanic explains almost everything clients complain about.
The costs are real and they land in places people don't always track.
You get duplicate CVs from four suppliers working one talent pool with identical toolsets. You've seen the same profile three times this month and assumed it was bad luck. It isn't — it's structural. Your employer brand gets spent on your behalf by recruiters desperate for candidates, pitching your company to anyone who'll listen.
Every exaggerated pitch that ends in a bad experience is a withdrawal from your reputation made by someone who doesn't hold the account. The senior AI engineers you most want to hire are the ones most likely to have been burned by this and least likely to answer the next approach.
It's a lottery. One lucky candidate, one lucky recruiter, one lucky hiring manager. Everyone else has lost weeks of their life.
It cost me too. I paid wages and overheads for a team that couldn't always deliver under that model. My consultants lost commission. Candidates lost trust. Clients lost too. Cost, cost, cost.
The AI layer made it worse, not better
The obvious fix was supposed to be automation. Source faster, screen faster, sequence outreach faster.
What actually happened is that everyone bought the same tools and pointed them at the same market. Standard toolsets converge to the average — that's what they're designed to do. So the contingent model now produces the same median shortlist as before, only quicker and in higher volume, while candidates use the same technology to make themselves look uniformly excellent on paper.
Two averaging machines, pointed at each other.
The outlier — the perception lead who moved across from robotics, the engineer who shipped the thing before it had a category name — gets filtered out by both.
My confession
Here's the honest part, and it's the reason I rebuilt the business.
I knew how to find people and run a process. Salary conversations, notice periods, the close. But the technical vetting? We mostly hoped for the best. "Rate yourself one to ten on Python." I taught people to ask that. It was a guess dressed up as a question.
In 2026 that isn't good enough, because AI can make anyone look perfect on paper. It has never been easier to look great without being it.
Recruiters failing at technical hiring is not primarily an effort problem. It's an understanding problem. The fix isn't a harder-working recruiter — it's a different person doing the assessment.
What we do instead
No big office. No ego. Just me and a group of experts.
Before I speak to a single candidate, I've met the client and looked them in the eye. I don't work from a job spec — I get the reality. What's the actual problem we're trying to solve? A year from now, what headache has gone, and what's changed for the person we hire? What is it genuinely like to work there every day — and if it's five days in the office with no flexibility, I'll say so. No hiding it until the offer stage.
If the answers don't add up, I don't take the work.
Then every shortlisted candidate goes through the System Check — technically vetted by an active CTO, CISO or engineering leader from our Industry Advisory Panel before you ever see a CV. Peers, not recruiters. People currently building the systems the role is about. The output is a 30-Day Technical Shortlist — verified candidates, delivered inside thirty days. Not an open-ended search that quietly runs for a quarter.
Why we work on retainer
Because you cannot do any of the above on a contingent basis. The economics forbid it.
Holding a candidate back, commissioning a CTO's time to assess someone properly, telling a client their brief is wrong — all of that costs money in a model where you're only paid if you win the race.
We work the way solicitors and accountants do. You engage professional judgement and you get an answer — including the answer you didn't want.
If a client won't commit to a retainer, I'm not the right partner. I'm not gambling my team's time on no-win, no-fee ghosts.
I want the person who's actually best at the job to get it. That's the world I want for my two daughters. One where a person's word means something.
The "amazing" pitch is dead. Just the truth, and the work, checked.
FAQ
What's the difference between retained and contingent recruitment?
Contingent pays only on placement, which rewards speed and volume. Retained is paid for the search itself — which funds proper assessment, market mapping and the ability to reject candidates, and clients, who don't fit.
Is retained search worth it for a single senior hire?
For scarce, high-impact roles, usually yes. The comparison isn't fee versus fee — it's fee versus the cost of a failed senior hire, which comfortably reaches six figures once lost productivity and a second search are counted.
Who technically assesses reaney.ai candidates?
Active CTOs, CISOs and engineering leaders on our Industry Advisory Panel — never recruiters — and always before the client sees a CV.
Matt Reaney has run technical search since 2013 and worked in recruitment for 25 years. Book a search briefing today.