I read hundreds of job descriptions a year. That is the part of headhunting nobody romanticizes, sitting with a hiring manager going line by line through what they actually need versus what sounds good on a job board. And the conversation has changed dramatically over the past year. A few years ago, I would get a brief for a senior engineer that read like a wish list: five-plus years of experience, strong communication skills, team player, thriving in a fast-paced environment. Vague enough to fit almost anyone with a decent resume. These days the brief lands looking completely different. It names the exact tools, the exact prior company stage, the exact kind of problem the person needs to have already solved. The job requirements are no longer a general filter, but a precise description of one specific person, and the hiring manager already has a clear picture of who that is before the post even goes live.
Why this is a very positive signal
I happen to like this change, and I think most experienced headhunters would tell you the same thing once they got past the initial adjustment. Vague job requirements were never doing anyone favors. They created an illusion of a wide net while wasting time for everyone caught in it. A hiring manager would write “experience with blockchain technology” because that felt safer and more inclusive than naming the actual protocol they were building on, and then spend three months interviewing people who had never touched the specific environment the role demanded. Candidates would read “experience with blockchain technology,” convince themselves their six-month NFT project counted, and apply anyway. Everyone loses weeks of their life to a requirement that was too soft to mean anything.
The data backs up what hiring managers are telling me directly
The job market itself is producing the proof. Recent research analyzing nearly a thousand engineering job postings found that companies have moved sharply away from hiring generalists who handle a bit of everything, toward professionals who can own a process end to end with deep, specific expertise in the tools that process actually requires. The researchers built a specialization score to track this and found the trend holding across nearly every technical category they measured.
Compensation data tells a similar story from a different angle. Engineering leaders surveyed for a 2026 hiring report said strong, specifically skilled engineers are now worth roughly three times their total compensation in output, a gap that has widened sharply since 2023. When a single hire is worth that much more than another candidate with a similar title, a hiring manager has every incentive to write the job description tightly enough to find exactly that person, instead of casting wide and hoping the right candidate surfaces from the noise.
Skills-based hiring
There is also a quieter shift happening underneath the “skills over degrees” conversation that gets a lot of coverage lately. Plenty of companies have publicly said they are moving toward skills-based hiring, and degree requirements have loosened in some sectors. Research from Harvard Business School and the Burning Glass Institute found that very few actual hires were affected by companies removing degree requirements from their postings. The headline policy got softer in public, while the underlying requirement for verifiable, specific skill quietly got harder. Companies are not hiring more loosely. They are hiring just as selectively, with the filter moved from a credential to a precise set of skills the candidate has to prove they actually have.
What this looks like inside crypto and AI hiring specifically
This is where I spend most of my working hours, so I will speak to it directly. A few years ago, a DeFi protocol hiring a smart contract engineer might ask for general Solidity experience and call it sufficient. Today the same role will specify the exact category of protocol the candidate needs to have shipped in, whether that is lending markets, derivatives, or cross-chain bridges, because the failure modes and security considerations in each of those are genuinely different skill sets, not interchangeable variations on the same job.
AI hiring shows the same pattern, maybe even more sharply. Machine learning engineer postings used to ask for general experience training models. Now they ask for production experience with retrieval pipelines, specific vector database tools, particular evaluation frameworks, or fine-tuning work on a defined model family. The growth in these roles has been enormous, with machine learning engineering becoming one of the fastest growing job categories in tech over the past year, and that growth has come with a corresponding rise in how precisely companies describe what they need. A title like “AI engineer” used to tell you almost nothing about the actual day-to-day work. Now the job description usually tells you exactly what kind of AI engineer they mean.
Compliance and regulatory hiring in crypto follows the same logic. As regulatory frameworks across different markets have matured and diverged, companies hiring for these roles increasingly want someone who already understands the specific regime relevant to where they operate, rather than someone with general compliance experience who would need months to get up to speed on the details. The candidates who get interviews are the ones whose background already matches the regulatory environment named in the post.
What narrow job requirements mean if you are job hunting right now
The instinct when job requirements feel this specific is to assume you are excluded unless you check every single box. That instinct is usually wrong, and it leads people toward the opposite mistake, which is giving up on roles they would actually be strong candidates for. The better way to read a tightly written job description is as a clear signal of what the hiring manager actually cares about, which makes your job easier, not harder, once you adjust your approach.
The first thing to drop is the spray and pray habit. Recent data from a major job search platform tracked over a hundred thousand applications through the first quarter of this year and found something candidates rarely hear stated this plainly: as application volume per person climbed, interview conversion dropped sharply, falling from roughly nine percent for people sending a modest number of targeted applications down to under three percent for people sending over a hundred. Submitting more applications was not only inefficient but actively reducing the odds of landing an interview, because the time that should have gone into tailoring each one was instead spread thin across dozens of mismatched attempts.
A separate survey from Monster found that nearly half of job seekers admit to applying broadly and not selectively, often because they feel like submitting more is the only way to get noticed when feedback from employers is rare. I understand that instinct completely. But the data and what I see firsthand both point the same direction. A handful of applications where your background really lines up with the specific requirements in the post will outperform a much larger number sent to roles where you are hoping the hiring manager overlooks the gap. Believe me, they don’t overlook the gaps.
What you should do now
So before you apply, read the job requirements the way the hiring manager wrote them, as a description of a real person they are picturing. If the post names a specific protocol, a specific framework, or a specific regulatory environment, that detail is there because someone on the other end has already been burned by candidates who did not actually have it. Match what you have against what they specifically named, and lead your application with that overlap instead of a general summary of your career. If the overlap is real but partial, say so directly and explain how close the gap is. Hiring managers who write requirements this precisely tend to respect a candidate who engages with the specifics honestly far more than one who sends a generic application and hopes volume does the work.
Why this is good news for serious candidates
Specific job requirements favor people who have built real depth in something, even if that depth came from an unconventional path. A candidate who has shipped production work on one particular kind of protocol, or fine-tuned one particular family of models, now has a much clearer way to stand out than they did when every job description sounded the same. The generalist resume that used to work everywhere now works nowhere in particular. The specialized one, even a narrow one, suddenly has a much shorter list of roles it needs to compete against, because most other applicants will not match the specifics nearly as well.
Narrow job requirements are not the market closing a door on you. They are the market finally telling you, in plain language, exactly what is being asked for, so you can stop guessing and start applying with intention. The candidates I see land roles fastest right now are the ones who read three job descriptions closely, recognize which one actually fits the work they have already done, and put real effort into showing that fit clearly. We talk about a far better use of anyone’s time than sending the same resume to fifty postings and waiting to see what sticks.
Hi, I’m Savvina
I’m a Web3 and AI headhunter working with people in Stablecoins, DeFi, Blockchain, Fintech, AI Research, and AI for Science. I take on a small number of searches at a time, which means every candidate I put forward has been properly assessed and every client gets my full attention.
If you’re a company looking for the kind of hire that has real impact, or a professional who wants to be found when the right role comes up, I’d love to connect.
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