quick answer
If you’ve posted a design or development job in the last year, you already know what to do: you’ll get buried. Hundreds of apps land in a day, and most of them are clean, professional, and completely interchangeable. It’s not that there are suddenly more qualified people in the field. Applying now takes ten seconds instead of twenty minutes. Hiring managers who are currently doing well are not trying to read more resumes faster. They’re testing real work rather than fine writing, and sourcing from a pool where the noise hasn’t yet entered.
what actually changed
Applying for a job used to take real effort. Candidates can now post via ChatGPT and have access to five customized apps before their coffee is cold.
LinkedIn reports that the number of applications submitted on its platform has grown nearly 45% this year, to about 11,000 submissions per minute. The New York Times directly linked this surge to candidates using generative AI to draft and submit applications faster. A survey by the Financial Times showed that artificial intelligence is used by about half of job seekers, with recruiters saying the number of applicants for individual roles has more than doubled. A new survey from Robert Walters found that 70% of employers have seen a surge in applications due to AI, and about two-thirds of professionals are now exclusively using AI tools to apply to more positions simultaneously.
SHRM’s 2026 hiring forecasts make it clear: HR teams are struggling to find real talent in a flood, and the AI tools used to screen talent can sometimes make the problem worse.
For hiring managers, this is a thing. A single post may attract hundreds of well-written, similar-sounding applications, but almost none of them will tell you whether the person behind it can actually do the job.
What doesn’t work anymore
- Post it widely and hope the right resume surfaces. Before you see it, it’s buried beneath everything else.
- Screening and resume polishing. Everyone’s resume is polished these days, so it doesn’t tell you anything.
- Generic screening questions like “Why do you want to work here?” Ten seconds in ChatGPT will give you the answer without teaching you anything about the candidate.
- Assume that more applications means more choices. Most of the time, it just means spending more time sifting through the few good candidates you would have found anyway.
what works
Be specific enough to filter out people. Name the actual problem this role solves and the exact tools or stacks involved. A vague post invited everyone. One particular inviter has actually done something similar.
Ask the candidate for something that cannot be outsourced to AI. Skip “Tell us about your experience” and ask for a short response on your actual product, or a small sample of your paid work. Generating a generic cover letter takes ten seconds. A five-year judgment on a real problem is not.
Focus on the process, not just the polish. Ask designers how they make decisions, not just what the final screen will look like. Ask a developer to pair you with you for twenty minutes instead of rating what you take home. You’ll learn more by watching someone’s thoughts than from anything they submit.
Sources from pools that have been self-selected. Mass Recruitment Board optimizes coverage. Niche boards built around people already working in design or development are optimized for fit. A pool that has been filtered by relevance outperforms a pool without any filtering.
Once you find the real one, act fast. Good candidates don’t sit around and wait. Giving them a “thorough” run through two more rounds mostly just gives them time to take in other things.
Common mistakes
- Think of a large number of applications as a good problem. It wastes sifting time and buries people worth talking to.
- Let’s say AI screening tools solve the AI-infested funnel problem. Often, it’s just two AI systems pitted against each other, one writing the applications and one filtering them, with less human judgment in the loop than either side assumes.
- Weigh the tools listed on your resume against the tools someone actually builds using them.
- Skip actual working examples as it adds friction. This friction is doing useful work. This is one of the few filters that artificial intelligence cannot fake.
FAQ
Does artificial intelligence really increase the number of job searches? Yes. LinkedIn reported that the number of applications submitted on its platform increased by nearly 45%, and separate surveys by Robert Walters and Beamery showed that AI-assisted applications accounted for between 46% and 65% of job seekers, depending on the market surveyed.
Can I reliably tell if a resume was written by AI? Not just formatting. Recruiters interviewed by the Financial Times pointed out that common phrasing repeated by candidates is the clearest indication, but a more reliable solution is to test the actual work rather than trying to detect AI in writing.
Should I use AI filtering tools to manage volume? They can help you categorize, but the fundamental problem remains: generic posts attract generic applications. Narrowing your funnel early is more effective than trying harder to filter later.
Where should I post open design and development jobs? For less specialized recruiting, high-capacity VW boards still make sense. For design and development in particular, boards built around an audience already working in the field tend to produce shorter, more relevant applicant lists rather than larger applicant lists.
takeout
The number of applicants used to be the bottleneck for recruitment. Today, there’s no shortage of apps, just a lack of ways to tell which apps are real. This is part of why niche, curated boards are worth trying alongside mass boards: Real Jobs favors designers and developers who come to get the job done, not because there’s a tool that works for them.