This week’s theme is what I keep hearing from Python developers and hiring teams: the market is challenging, but the hiring experience is what’s pushing people over the edge. The frustration is not just rejections. It’s wasted time, unclear processes, and systems that feel designed to remove humans from decisions.
This edition is a playbook: what candidates are reacting to, what companies can change quickly, and the value I bring as a recruiter when hiring feels messy.
What candidates are running into right now
1) AI interviews are becoming common, and candidates are opting out
Greenhouse reports 63% of job seekers have been interviewed by AI. UK reporting on the same survey highlights:
47% of UK job seekers have done an AI interview
82% were not clearly told beforehand
30% walked away from a process because it involved an AI interview
The pattern is consistent: candidates do not hate AI. They hate surprise AI, unclear evaluation, and the feeling nobody reviewed it.
2) Ghosting is now expected, which damages trust
Greenhouse-linked reporting says 61% of job seekers have been ghosted during the recruitment process.
When candidates assume they’ll be ghosted, they apply more, commit less, and treat every process as low trust until an offer exists.
3) Ghost jobs are distorting the market
UK research from StandOut CV reported 34.4% of listings across 20 roles were “ghost jobs,” and for software engineers it reported 46.5%.
Other studies show lower numbers, but the direction is the same: enough stale ads exist to waste meaningful candidate time.
4) Long take-homes and slow loops are creating drop-off
Monster’s deal-breaker research says:
53% would drop out due to long delays or lack of communication
57% would withdraw due to a poor interview experience
5) Flexibility mismatch is a real funnel leak
Gartner survey results cited in UK HR press show:
nearly 20% discontinued a hiring process because location flexibility didn’t match preferences
25% discontinued because working-hours flexibility didn’t match
What hiring managers can do this week to win candidates without raising budget
1) Publish the process and stick to it
Put these in the job spec and repeat on the first call:
number of stages
what each stage tests
expected timeline end to end
2) Set a feedback SLA
Commit to a simple rule: update every 5 business days even if it’s “still reviewing.” With ghosting so common, communication is now a differentiator.
3) Shrink take-homes or pay for them
If your task takes longer than ~90 minutes, either pay or replace it with a short live work sample. Long delays and poor experiences are already causing withdrawals.
4) If you use AI in interviews, disclose it and offer a human option
Tell candidates up front, explain what’s being assessed, confirm a human reviews results, and offer a human-led alternative where possible. Drop-off is real when AI feels hidden or unreviewed.
5) Separate “onsite culture” from “onsite requirement”
If you want speed, offer candidates remote, hybrid, or onsite where the role allows, then anchor culture with one hub and predictable in-person moments. Flex mismatch is a measurable source of drop-off.
What Python developers can do to protect time and increase conversion
1) Ask three questions on the first call
What are the stages and what does each assess?
What’s the timeline end to end?
Is there a take-home and how long should it take?
2) Push for clarity if AI is involved
Ask what is being evaluated, whether a human reviews, and whether there’s a human-led option. A meaningful portion of candidates are walking away when the process feels unclear.
3) Filter out likely ghost jobs
Red flags: constantly reposted roles, no urgency, vague “always hiring” language, no hiring manager context. Enough listings are stale that this is worth treating as a real risk.
Where I help as a recruiter when the market feels like this
Process clarity upfront: stages, timelines, take-home expectations, decision-makers
No-ghosting pressure: I chase feedback and keep momentum moving
Offer protection: comp bands, flexibility, and approvals aligned early
Prep that maps to reality: what that team screens for and how they score it
Close support: negotiation, competing offers, and keeping things respectful
Job of the week
Lead Python Developer (IC) | AI x Electronics | London hybrid | £90k–£130k + equity
AI x Electronics startup in London that just raised a $18.5m Series A.
Role
Lead Python Developer but staying individual contributor
Strong Python required. Django core, open to Flask or FastAPI backgrounds
You’ll operate close to product and delivery, with real ownership and technical influence
Setup
2 days per week in London
5 weeks per year working remotely from anywhere in the world
Flexible working hours
Comp
£90k–£130k base + equity (depending on level)
If you want the full brief and context on the team, message me and I’ll share it.
The big takeaway this week: candidates are not being difficult. They’re being selective because too many processes waste time and hide information. Companies that communicate clearly, respect candidate time, and keep humans in the loop will hire faster at the same budget.
Open question to spark debate: Are companies creating their own “talent shortage” by making hiring slow and opaque, or is this just the new normal?
Hiring? Contact
Josh Smith
LinkedIn: https://www.linkedin.com/in/python-recruitment/
Email: [email protected]
Phone: 01727 225 552