Less is more, even in a broken job market
Realising that most of my applications were just wishful thinking was a tough pill to swallow but it finally changed how I look for work.
TL;DR
- Write down what you actually want from your next role before you look at any jobs. Note down your required seniority, domain, tech stack, work pattern, and salary floor. Use it as a strict filter.
- Build a proper master profile somewhere. Do not just make a standard CV. Build a full record of what you have done because you will reuse it constantly.
- Before applying score the role against your profile honestly. If it is a weak match and you cannot explain why you still want it then skip it.
- Pay attention to roles that score higher than you expected. That is where your blind spots live.
- Only tailor a CV once you have decided the role is worth your time. Do not tailor first and rationalise later.
The spray and pray phase
For a long time my job search looked like this. See a title that sort of matched, skim the JD, tweak the CV a bit, hit apply. Repeat until I was too tired to think.
I told myself it was a numbers game. More applications, more chances. In reality I was just adding noise to my own search and getting ghosted at scale. The CIPD's Resourcing and Talent Planning report has been saying for years that employers are drowning in applications and struggling to filter, and data on LinkedIn Easy Apply shows it makes the problem worse, not better — average response rates sit at just 3–13%. I was part of that problem.
At some point I realised I was not being strategic. I was coping.
Why more applications is not the answer
Sending 200 half-relevant applications does not make you look keen. It just means 200 versions of you with a slightly off CV floating through ATS systems that were never going to shortlist you.
What actually moves the needle is fewer, better targeted applications where:
- The role genuinely fits your experience.
- Your CV speaks to what the JD is really asking.
- You have a clear reason for applying beyond "it was there".
That sounds obvious. The hard part is being honest with yourself about which jobs those are.
The big name trap
Here is where my brain betrays me. A familiar logo shows up and suddenly I am ignoring the fact that the role wants five years of something I have barely touched. I convince myself I can "grow into it" because the company looks good on a CV.
I have wasted hours on applications like this. Nice rejection email, if I got one at all.
The opposite trap: the underqualified illusion
The flip side is just as bad. A JD lists a stack of tools I have not used, phrased in language I do not recognise, and I scroll past. Then weeks later I realise the role was essentially what I do every day, just described in someone else's vocabulary.
Technical hiring is full of this. One company's "platform engineer" is another's "DevOps lead" is another's "SRE". Gartner's Future of Work research keeps pointing out that job titles and skill labels are drifting apart faster than most people can track — skills are now overtaking degrees and titles as the real signal. If you are filtering purely on familiar terms, you are missing roles that actually suit you.
Why I started using AI scoring
This is where an honest second opinion helps. I now run roles I am considering through an AI scoring step before I spend any real time on them.
What I want from it is simple. Tell me, based on my actual profile, how well this role matches. Show me where I am strong. Show me where I am weak. Do not flatter me. Do not dismiss me because I phrased something differently from the JD.
The useful thing about AI here is that it does not care about the logo. It does not get excited about a famous employer and it does not get intimidated by a dense JD. It just compares what you have done to what the role is asking for.
A few things changed for me once I started doing this:
- I stopped applying to shiny roles that scored badly once I looked past the brand.
- I started applying to roles I would previously have skipped, because the scoring showed my experience mapped well even when the vocabulary did not.
- I spent more time on fewer applications, and the response rate went up.
What good AI scoring actually looks like
Not all of it is useful. A generic "you are a 72 percent match" number means nothing on its own. What I want is:
- A breakdown of which requirements I clearly meet.
- Which ones are partial, and why.
- Which ones I do not meet at all, and whether they are dealbreakers or nice to haves.
- Suggestions for how to frame my existing experience against the JD without making things up.
That last point matters. The goal is not to invent skills. It is to notice the ones I already have but have been describing in the wrong language.
How I use AI for this, and why I built OutRung
I started out with a pretty rough setup. Prompts I had cobbled together, bits of my CV pasted into chat windows, scoring logic I was tweaking every other day. My own prototype was wonky, hard to use, and far too technical for anyone who was not me. But even in that messy state I could see it was a diamond in the rough. The signal it gave me was genuinely better than anything I got from scrolling job boards or trusting my own gut.
That is why I ended up building OutRung. Same underlying idea, but a more polished experience so I am not fighting my own tools every time I want to evaluate a role.
The flow is straightforward now. I keep one master profile with my real career history, skills, and achievements. When a role comes up, I score it against that profile before I commit to applying. The scoring gives me the unflattering version of the truth. Sometimes it tells me the dream role is not actually a fit and saves me an afternoon. Sometimes it tells me a role I almost skipped is a strong match and nudges me to look again. Either way I am making decisions with more signal and less ego.
For the roles that do pass the bar, I use the same profile to generate a tailored CV for that specific JD, and track the application alongside the rest. One place, one source of truth, far less admin.
Practical tips if you want to try this
- Write down what you actually want from your next role before you look at any jobs. Seniority, domain, tech, work pattern, salary floor. Use it as a filter.
- Build a proper master profile somewhere. Not a CV, a full record of what you have done. You will reuse it constantly.
- Before applying, score the role against your profile honestly. If it is a weak match and you cannot explain why you still want it, skip.
- Pay attention to roles that score higher than you expected. That is where your blind spots live.
- Only tailor a CV once you have decided the role is worth it. Do not tailor first and rationalise later.
The quiet version of job searching
I apply to fewer jobs now. I spend more time on each one. I get more replies. It is not dramatic and it is not a hack. It is just what happens when you stop treating your career like a lottery ticket and start treating each application like it should actually mean something.
The broken bits of hiring are not going away soon. But I can at least stop adding to the chaos on my own side of it.
Written by
Tian - Founder of OutRung
Tian is an AI professional, builder, and the founder of OutRung. Holding a PhD in deeptech, Tian navigated the frustrating modern job market first-hand before transitioning into the AI space. OutRung was built to share the exact strategies that made that transition successful. Tian’s goal is to help everyday job seekers use AI to find their ideal roles efficiently, without needing to be computer experts themselves.
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