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The 7 Signals Hiring Managers Actually Look For in 2026
Let's make sure you stand out in your startup job search.
Kyle Thomas
May 02, 2026
JOB SEARCH STRATEGY WITH EARLY.
We’ve all spent hours updating our resumes when looking for a new role.
You might clean up the formatting, update your recent title, and make sure you squeeze as much credibility as you can into that one or two pages.
You ran it through both ChatGPT and Claude to refine it as a "startup executive resume writer and startup recruiter" would.
You even paid someone on Fiverr to review it, which felt a little embarrassing, but you did it anyway.
And then you hit send on a few applications, and you wait.
And wait.
...Silence.
The kind of deafening silence that makes you refresh your inbox four times in an hour.
I talk to startup job seekers every day, and this is an all-too-common story.
Here’s the problem.
Startup hiring managers are looking for signals. Specific, observable behaviors that show how you think, learn, and operate before you set foot in an interview.
And unfortunately, the average resume template won’t help you achieve that.
Today, in this issue, I want to talk about what will.
IN THIS WEEK'S ISSUE:
1. WHAT USED TO MAKE YOUR RESUME STAND OUT
Hiring managers are looking at hundreds of resumes per role, and at that volume, it becomes more of a filter than a decision-making tool.
54% of candidates are now using AI to write their résumés. Over half use it for cover letters, too. Which means the pile of well-formatted, keyword-optimized documents has never been longer or more interchangeable.
These are the top three things that could work against you, and how to fix them:
A big-name company on your resume.
FAANG. Unicorns. McKinsey. The logic makes sense, if you were good enough to get in there, you must be good enough for us.
And those big names on a resume definitely open doors.
But when a startup founder sees Google or Meta on your résumé, three questions fire in their head almost immediately:
Is this person going to be too expensive for us?
Are they actually willing to roll up their sleeves and get into the weeds with us?
Do they need a massive budget and proper infrastructure to actually be effective?
These questions are fair, given how different the environments are between a big company and a fast-growing startup. Sometimes the people applying have no idea what they're getting themselves into.
So it's not just the brand name that's important. You need to make sure your work and the impact you drove scream, "I'm ready to work at a startup".
The way to overcome this "startup ready" objection is to lead with outcomes. Instead of letting Google do the talking, you need to answer those three founder questions before they're asked. They need to be present in your outreach, your positioning, and how you frame your experience.
Show them the specific problems you solved, not just the company you solved them for.
Bonus points for drawing parallels to where the work environment and the speed of execution in your previous role rhyme with how startups operate. By that I mean fast execution with incomplete data, executing with small teams with limited resources, consistent experimentation, and/or building something from zero to one.
Exact years of experience.
"5+ years in X" is shorthand for readiness and for a long time, this was true.
But... surprise surprise! That's changed.
Professionals with specialized AI skills now command salaries up to 56% higher than peers in identical roles without those skills. That's up 25% from one year earlier.
Demonstrating genuine proficiency with modern AI toolsets - (not just familiarity, but actual working knowledge and demonstrated experience of how these tools integrate into real workflows) - is your best shot at making years-of-experience requirements largely irrelevant for many roles.
The speed at which you learn and apply, combined with your ability to show your work, matters far more than the calendar time you've accumulated.
This hasn't eliminated the years of experience entirely because with years of experience comes a level of maturity, a deeper network that can help with recruiting or partnerships, seeing all the things that have worked, and, more importantly, seeing all the things that haven't worked. Especially for Director, VP, and C-Suite roles, they're going to want to see a demonstrated history of leading at a high level. But people are jumping the "years of experience" line when they can clearly demonstrate that the impact they can deliver is on par with or surpasses that of someone less AI-native.
Polished, prepared answers in interviews.
There's a version of interview prep that becomes its own liability. Candidates over-rehearse, lock in their answers, and then when a founder deliberately introduces ambiguity or changes the framing mid-question, they cling to the script even when it no longer fits the problem in front of them.
The strongest candidates do the opposite. They pause, ask clarifying questions, and adjust as new context appears.
One candidate in the Early community was recently asked: "What was the weirdest thing you did when you were a child?"
There is no rehearsed answer to that - which is precisely the point. They were looking for passion, curiosity, and a certain kind of personality. Startups want people who are a little obsessed, a little quirky, and genuinely themselves.
I have seen far too many candidates lose out in interviews because they were too rigid and unable to adapt to the questions or situations their interviewers raised.
This is where your familiarity with the company, your interviewer, the product, and your function is a massive advantage. The better you know the space, your interviewer, the industry, and your function, the easier it is not to get flustered and to turn those more ambiguous questions into a conversation instead of trying to "get it right" immediately.
2. WHAT HIRING MANAGERS ARE ACTUALLY LOOKING FOR IN 2026
AI has raised the baseline for what "good enough" looks like on paper.
It also has changed how candidates get filtered.
99% of hiring managers now report using AI in some capacity, according to Insight Global's 2025 survey. The tool that's flooding inbound pipelines with polished applications is now the same tool used to filter them.
There are seven signals we've consistently seen separate the candidates who land strong roles from those who don't:
AI fluency: not just using tools, but understanding where AI helps and where it doesn't
An online presence: ideas, thinking, or work that's visible before the interview
Free work or side projects: proof of initiative and impact without being asked
Clear thinking under ambiguity: how you reason, not just what you answer
Ownership mindset: acting like a problem-solver, not a task-taker
Intrapreneurial drive: adapting quickly and persevering through setbacks
Learning velocity: evidence that you can apply new knowledge fast
Here’s what I want you to do. Get out a Google doc or journal, run through this list of signals, and write down examples of when you’ve been able to achieve them. This can be in a role or as a side project.
When you prepare for a specific role (in the application or interview stage), you can pick from your list of stories, choosing signals that apply to the role and what it’s looking for.
Let’s go deeper on this…
DON’T JOB SEARCH ALONE
If you’re reading through this thinking “I want help to do this step-by-step” that’s exactly what the Early Accelerator is built for.
Here’s what our members get:
One Early member recently landed a remote senior leadership role at a $500M startup that wasn’t even hiring.
Another went from VP to a COO role less than 90 days after joining.
These aren’t flukes - they’re the result of the playbooks, mentorship, company research, and community we provide.
It’s the best way I’ve found to cut through the noise and land a role at the next generation of world-changing startups.
3. HOW TO BUILD EACH SIGNAL TO GET HIRED
Credentials tell a hiring manager what you've done in the past.
Signals tell them the type of hire you’ll be in the context of their company.
That distinction matters because startups don't hire for your past. They hire for what you'll do in an environment that's messier, faster, and less resourced than anything on your resume.
Signal 1: AI fluency
Don't think that adding "AI native" in your LinkedIn headline is going to be enough to show them you know your shit.
AI fluency is the ability to demonstrate that you know where AI genuinely helps and, critically, where it doesn't. It's also about your ability to prove it.
88% of hiring managers say they can tell when candidates have used AI on their application. This isn't to say that they're penalizing the use of AI. But they are penalizing candidates who've outsourced their thinking entirely.
That's an important distinction.
How to show it: In interviews and outreach, explain how you used AI to prepare, research, iterate, or create and how you use it in your day-to-day workflow - not just that you use it.
"I used Claude to help me research your competitors" is table stakes.
"I built a workflow to scrape competitor landing pages and customer sentiment and used it to map three gaps in how you're positioned against [Competitor], and I have a view on which one is worth addressing first. I can share the Claude skills, a map of the workflow, a walkthrough of how I pulled the data and compiled the research, and all the markdown files after the interview if it would be helpful to the team." is a signal because you've done the work, formed an opinion, are sharing your work, and have shown you think like someone already inside the business.
Signal 2: Online presence
Hiring managers can see how you think before they ever meet you. Your posts, comments, and the way you engage with ideas in public all create a picture of who you are before the first call is booked.
For most people, all the team has to go off of is a resume and a bare bones LinkedIn profile.
Before you scream, "I DON'T WANT TO BE A LINKEDIN INFLUENCER" (trust me, I hear this a lot with the people in the Early Accelerator), don't worry. You don't need to. Just 1% of LinkedIn users post content weekly, yet those users generate 9 billion impressions per week, so the bar for standing out as someone with a point of view is low.
I want to take a moment and emphasize this should be YOUR point of view written in YOUR words. Not writing a prompt asking, "What should I write to post content on LinkedIn? Once you come up with the topics, write a post for each." and then posting verbatim what the LLM produced.
That gives hiring teams zero signal other than, "This person outsources their thinking and puts slop out online."... Not a good look.
That said, all it takes is one thoughtful post per week. If you stay consistent it will compound into something meaningful over a quarter.
If you want to post more, it will result in more impressions, more profile views, more connections, and a stronger backlog of data for hiring teams to use to get a good understanding of who you are.
But, you need to start somewhere, so make it an easy and attainable goal of 1 post per week for the first week. Then do 2 in the second week, 3 in the third, and so on.
My guess is that by the second month, you won't be as scared of posting anymore, and you'll be pumping out content like it's your job.
Don't want to post on LinkedIn? Post on X.
Not down with Elon? Write a newsletter on Beehiiv or Substack.
It doesn't matter where you're doing it so much as that you have things to say and are sharing those ideas with the world.
Don't believe me, this works?
I was just speaking with a seed-stage startup last month who hired one of their first 6 employees because the founder liked his content on X. Not only that, the team is full-time in-person in NYC, and this guy lived in Georgia, but the founder liked him so much he said, "Screw it" and gave him an exception to work remotely.
How to show it: Don't just share announcements. Share insights, what you wish you had known 2 years ago, what and how you're building things today, what you think most people get wrong about X . A take on something your target companies are actively navigating is more useful than a career update.
If posting feels like a stretch right now, start by leaving comments that actually provide value. These value-driven comments don't look like "great post, really insightful!". Share your perspective, a story from your experience, ask a question of the poster, share a relevant news article/tool/podcast. Add to and continue the conversation with value.
Signal 3: Free work / side projects
Doing free work and/or working on side projects shows You build things and explore ideas without being asked. It also shows you're motivated by problems, not just titles or compensation.
For a founder hiring into a small team, this is one of the hardest things to fake and one of the most valuable things to find. It tells them you won't need a brief to get started, won't need a manager to stay motivated, and won't stop at the edge of your job description when something important needs solving.
This doesn't just apply to the early-stage startups either. It applies to all sizes, all stages, and all industries. The best way to stand out today is to SHOW, not TELL. In reality, it has always been that way, and it's becoming increasingly important as the hiring landscape grows more competitive.
How to show it: Small, scoped projects beat large speculative decks every time.
When I was going after my role at Avo (a Series A same-day delivery startup with $35.27M raised from Kleiner Perkins and Y-Combinator), I walked through their warehouse and told them all the things they should fix, provided software recommendations, coached their warehouse manager for an hour, shared the way I thought they should be tracking their metrics, and consulted their operations team before receiving an offer.
Nobody asked me to do any of that. That's free work. And it's why I got the job, bumping me from Senior Operations Manager at Uber to VP of Operations at Avo and a $100k cash comp increase.
Charlie Hoehn did the same thing to land a role as Tim Ferriss' first employee (Charlie now runs Author.inc, a highly successful publishing company).
Noah Kagan did it to become Mint's 4th employee (Mint would be purchased for $170M by Inuit and Noah would go on to found AppSumo and bootstrap it to >$100M ARR).
Caleb Ralston did it to land a job working with Gary Vee (He then worked for Alex Hormozi and now is one of the most sought-after personal branding experts on the planet.)
Ryan Graves did it to land a job at Foursquare before later becoming Uber's first CEO (He is now a billionaire, living in Hawaii with his family... look how far free work can get you.).
The pattern is consistent.
Deliver value wherever possible.
It doesn't matter if it's an actual working prototype, a case study of your prior work that directly relates to what you would do in the job, a playbook or document laying out a process they need, a 30-60-90 day plan demonstrating you have a clear understanding of what you would do if you were in the role, a connection to someone in your network who can help them, a link to a relevant and interesting newsletter/podcast/article, or simply a Loom video expressing your enthusiasm in what they're building and how you think you can drive impact.
It's about showing them that you're not worried to give away your best stuff because you know that people pay for implementation, not information, and that what you're sharing is only a taste of what they'll get when you're in the company full-time.
These types of candidates are mouth-wateringly attractive to hiring managers and unbelievably rare.
Everyone either is too scared to hit send, too jaded to give their work away, or too cautious of looking like a "try hard".
The ones who compete on generosity and give it all away are the ones who win in the end.
Signal 4: Clear thinking under ambiguity
This one is harder to manufacture. Which is exactly why it differentiates so effectively.
Startups operate in constant ambiguity.
When asked a tough question, weak candidates mask the discomfort with false confidence and jump straight to solutions before they understand the actual problem.
Founders, hiring managers, and cross-functional panel interviewers can see through it immediately.
How to show it: Narrate your thinking rather than rushing to "the right answer."
When a question is vague, open-ended, or comes with a lack of clear information, ask clarifying questions and share your thought process out loud as you deliver your answer.
Don't worry, this won't indicate to the interviewer that you don't know the answer.
In fact, it does the opposite.
Pausing and asking clarifying questions does many things:
It gives you more time to compile your thoughts.
It shows the team you don't jump to conclusions.
It demonstrates your level of subject matter expertise.
It allows you to collect further details to improve your answer.
It gives you a better understanding of what the team is looking for in an answer.
It shows the team you're good at digging deeper to uncover necessary information.
It gives the team an opportunity to hear your thought process
All of those things are characteristics of a great hire.
Asking them questions is also a great way to turn what would be a "gotchya" question into an active conversation and simulation of what it would actually be like to work with you.
In practice, this sounds like: "Before I answer that, can I just check: are you asking about X or Y? Because my answer is quite different depending on which one you mean." Or, "I want to ensure I have all the information I need to deliver a clear answer and share my thinking, so in this scenario, where does [INSERT IMPORTANT METRIC] stand and how much of a priority is [OUTCOME 1] over [OUTCOME 2]?"
After you ask your questions, it's also completely ok, if not encouraged, to take a minute or two to compile your thoughts in a notebook or journal, then deliver your answer and clearly walk them through your thinking.
That willingness to slow down before jumping in is the signal. It tells a founder you won't make expensive assumptions when the stakes are high.
Signal 5: Ownership mindset
This is the difference between "I worked on the campaign" and "I owned the campaign."
Founders and hiring managers are making a significant bet of time, money, and culture fit on every hire. What they're really trying to understand is: when something important isn't getting done, will this person wait to be asked, or will they just handle it?
Ownership isn't about working harder or longer and it definitely doesn't mean, "This was in my job description, so this is mine.".
It's about the instinct to identify that there is a problem or opportunity in the first place, then to treat thata problem as yours until it's solved, regardless of whether it sits neatly inside your job description.
In the early days of Uber, we had the cultural value "Be an owner, not a renter". It meant that they wanted operators who would treat their work as if they were the CEO of the company, regardless of their function or level.
See a problem or opportunity, raise said problem or opportunity with a proposed plan of attack, execute, measure, report, iterate, execute again.
Ownership is, "I identified this problem. I believe the best way for us to solve it is X. If I don't hear back from you, I'll run with it and report back. If you have any thoughts, feedback, or recommended changes in approach, please let me know."
In the interview process and on the job search, it's important to show through your stories, experience, and examples that you're that kind of person.
How to show it: Give clear, specific examples of problems you took full responsibility for, including ones that didn't go perfectly, and frame them entirely around outcomes.
The structure that works best is really simple:
What was broken or missing?
How did you identify that it was a problem or an opportunity?
What was the impact that thing had or would have on the company if nothing was done?
What did you decide to own?
What actions did you take?
What was the initial result?
What were the long-term impacts on the company as a result?
The specificity is what does the work.
"I led a project that improved retention" is not only forgettable but reeks of someone who didn't actually own anything and is either faking it or was too removed from the action on the ground to be effective in a startup.
"When monitoring new member numbers, I noticed we were crushing it with 25% MoM user growth, but when I looked at the user usage data, it was only seeing modest growth MoM. I dug into the user data further and identified we were losing customers at the onboarding stage. They were signing up, but it wasn't clear to them how to take the first action that would ultimately drive immediate value and get them hooked on the product from day one. This would present a significant issue for us going forward, as all the money we were spending on marketing to attract user ts was being wasted because we couldn't keep them in the product. To combat the onboarding dropoff, I built a new check-in sequence without being asked and ran it past the Head of Product with all the data to back it up. He approved my plan and told me to run with it, so I deployed it and, within a few weeks, had reduced 30-day churn by 18%.".
That's what ownership looks like.
Signal 6: Intrapreneurially driven
Startups move fast and change direction often, not because of disorganization (well... sometimes because of disorganization), but because new information arrives constantly.
The best operators are able to adjust quickly without a fuss.
The ability to adapt when the goalposts move (and trust me, they will move), without losing momentum, is rarer than most people think.
For many people inside a startup for the first time, the ping-pong feeling of "This is really important, I need you to make this your top priority. No, wait, that's not important anymore. This thing is important now. Focus on that." can leave their heads spinning and looking for the exit.
What founders are screening for here is anti-fragility.
These are the special few who are not only just able to absorb a setback and carry on, but actually get better and think more clearly when things get hard.
In a 25-100 person company navigating a pivot, that quality is worth more than almost anything else on your résumé.
How to show it: Prepare a specific story where the original plan failed, and you adjusted mid-project, and be precise about what the adjustment actually was. Don't give a vague "we had to change direction, and I adapted well." Paint the picture of what was going on, give a concrete account of what broke or why things needed to change, what decision you made, the actions you took, and what the outcome was.
A candidate who can tell that story clearly, without making it sound like a crisis they survived signals that they'll do the same thing inside the company.
Often, the right startup candidates will tell stories that, from the outside, look like crises, with a smile on their faces because they know those are the scenarios where they shine.
Signal 7: Learning velocity
Startups are constantly evolving, and they want operators who match that energy.
The pace of evolution has never been faster, with the rapid changes in AI.
Learning velocity is about picking up new skills quickly and demonstrating the relationship you have with feedback and failure.
Candidates who are precious about being wrong, defend their original position when new evidence appears, or treat criticism as a personal slight rather than useful data, are a significant liability.
No one wants to work with the person who is clearly wrong but continues to fight to the death to preserve face. Those people are exhausting to work with, and they kill company culture.
The operators who compound fastest are the ones who actively seek out the moments that made them uncomfortable, extract what they can from them, and change their behavior and approach accordingly. That willingness to be wrong and to improve is what learning velocity actually looks like in practice.
In the end, a successful startup is just a set of failed experiments that were learned from and improved upon.
A failed startup is a set of failed experiments that were never learned from or weren't improved upon fast enough.
How to show it: Reference something specific that you got wrong or an experiment you executed that didn't have the intended result, the feedback you received, and what you changed as a direct result. The more honest and precise you are, the more powerful this signal becomes.
"Initially, I thought 'do X get Y' incentives would drive the biggest improvement in customer performance and incentive efficiency. We saw a bump in performance, but the incentives were expensive relative to the performance gain. So, I tested something different. It was clear that customers were responding to the goals we set, so I crafted an experiment to test guarantee-based incentives. After rolling it out, we saw a massive bump in productivity (+30%), and it reduced the overall incentive spend by 60%." is infinitely more compelling than "I'm always looking to learn and improve."
One sounds like a candidate. The other sounds like someone who already works in the business.
A note on all of the above: signals don't come from trying to stand out.
It's more about aligning with the startup environment you're looking to join and ensuring that how you think and work is consistently visible.
Most candidates fail here because they confuse signaling with performing: over-polished answers, forced personal branding, and enthusiasm that clearly isn't real.
Strong candidates do the opposite.
They naturally demonstrate signals through action, and they do it long before anyone is formally evaluating them.
4. YOUR NEXT 7 DAYS OF SEARCHING
The mistake most people make after reading something like this is trying to fix everything at once.
All seven signals suddenly feel urgent. So you start a LinkedIn strategy, kick off three side projects, rewrite your résumé, revamp your interview prep, and commit to posting daily.
By Thursday, you've done none of it properly, and you're questioning whether any of it was worth starting.
So instead, I want you to prioritize.
Pick one signal, build it properly, let the evidence accumulate, and only then move to the next.
Take AI fluency as an example. One week of focused signal-building could look like this:
Use AI to research a target company or role more deeply than you otherwise would have
Turn that insight into a short LinkedIn post, a Loom, a more specific outreach message, or a product/prototype/workflow/document/deck focused on a specific aspect of the role you can send as a demonstration of the value you'll bring (AI can help you create this)
Reference how you used it in your next interview or conversation
In the space of a week, you've demonstrated curiosity, practical AI use, and modern working habits, all from a single, focused effort. That one signal does more for your candidacy than a perfectly written résumé.
The same logic applies to every signal on the list.
You don't need all seven.
You need one done well, repeated consistently, until it becomes the thing you're known for.
Look, I know how this goes.
You read something like this, feel the clarity, maybe open a notes app and write a signal or two down. Then life happens and the week disappears.
I'm not saying that to be harsh. I've just watched it happen to a lot of people who had everything they needed to land something great.
So here's what I want to know.
Which signal are you starting with? Reply to this email and tell me.
I read every single one, and if you're stuck on where to begin, I'll tell you exactly where I'd start based on the role you're going after.
And if you want to build the whole system properly, including figuring out which signals matter most for the roles you're targeting and making them visible in a way that actually gets responses, that's exactly what we do inside the Early Accelerator.
Applications are open at BeEarly.com.
🔗 RESOURCES MENTIONED:
Startup Jobs NYC - How to find the best New York startup roles in 2026
Forbes - 20 Important traits to look for in technology startup candidates
Ureed - What startups really look for when hiring - beyond your resume
Insight Global - 2025 AI in Hiring Survey
PwC - 2025 Global AI Jobs Barometer
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