Startup Hiring Hacks: Unconventional Methods That Build Strong Teams

I was spending 8 to 10 hours a week on phone screens that mostly went nowhere. Same questions every time, half the candidates were a clear no within the first two minutes. So I built a fix for it. I started running AI voice interviews to screen every candidate before anyone on the team talked to them.

It’s pretty simple. Candidates get a link, answer 5 or 6 questions on their own time, and the AI scores their responses. No more scheduling back and forth. No more blocking out my whole afternoon for calls. I went from screening maybe 15 people a week to reviewing 50 plus without adding a single hour to my day.

The biggest surprise was how it changed who we were actually hiring. Before, I was unconsciously favoring people who were easy to schedule. Usually that meant people between jobs. Once I removed that bottleneck, I started hearing from stronger candidates who were still employed and just couldn’t hop on a random Tuesday call. Quality went up immediately.

If I had one piece of advice for other founders, it’s to focus on consistency. Early stage hiring is messy because your standards shift based on your mood or how busy you are that week. When every candidate answers the same questions and gets evaluated the same way, you just make better calls. And you have something to go back to when you’re choosing between two strong people.

The hiring process itself is a product. If it’s slow or frustrating for candidates, you’re losing good people before you even get to make an offer.

In Tallenxis, we used a method that some people found unusual at first: before making a hire, we put candidates into a short, real-world working session with the people they would actually collaborate with, not just a standard interview panel. We were less interested in polished answers and more interested in how someone handled ambiguity, communicated under pressure, and responded to feedback in the moment. That gave us a much clearer view of who could operate well in a fast-moving environment like ours.

The impact was significant because it changed the kind of people we brought into the business. We ended up with a team that was more collaborative, more adaptable, and much less driven by ego. My main advice to other founders is this: be very clear about the behaviors you want before you start interviewing. If you do not define that upfront, it becomes too easy to hire the most impressive talker instead of the person who will actually strengthen the team.

One unconventional method I’ve used to improve hiring is shifting part of the evaluation process from traditional interviews to a short, structured “working session.” Instead of relying solely on how well someone interviews, we invite final candidates to walk through a real (but scoped) scenario they would encounter in the role—whether that’s prioritizing competing requests, responding to a difficult employee situation, or mapping out a simple project plan.

What makes this different is that it’s not framed as a test. It’s collaborative. We’re less focused on the “right” answer and more on how the person thinks, communicates, and adapts in real time. It also gives candidates a much clearer picture of the work and expectations, which leads to more informed decisions on both sides.

The impact has been significant. We’ve seen stronger alignment in hires, fewer surprises after onboarding, and better retention, especially in roles that require a mix of technical skill and stakeholder management. It’s also helped us build a team that is not just capable, but highly collaborative and self-aware.

One key consideration for others is to be intentional about what you’re actually evaluating. It’s easy to design exercises that favor speed or polish, but that doesn’t always translate to success in the role. Focus on the core behaviors that matter most: how someone approaches ambiguity, communicates with others, and makes decisions—and design your process around that.

We made an effort to take a different approach to hiring by hiring based on behaviors rather than resumes. Instead of defining jobs based on their previous positions, we used a real life situation that they would encounter on the job, and then asked them to answer the question in the way they would have done it on the job. For example, in hospitality, we create a situation where they will be under a lot of stress with an angry customer or you have a staff shortage at the last minute, and we can see how their minds work as opposed to just what their mouths say.

We were surprised to find that many of the best hires actually did not have perfect career paths. They had the right instincts, ways of communicating and making decisions under pressure. This caused our team to become composed of people who are quick to adapt and take ownership, which is likely to have greater impact in fast-paced environments than polished experience.

The effect on retention was huge. Those people who were hired this way would stay longer because they had an understanding of what the job actually was from the beginning.

One thing to consider is creating scenarios that represent a real-life, rather than a fantasy life. You aren’t measuring perfect answers, but rather how they problem-solve when things don’t go as expected.

My name is Gregg Carey. I’m CEO of More Staffing, a staffing firm that places Filipino remote professionals with founders and operators in the US, UK, Canada, and Australia.

We stopped hiring for availability and started hiring for proof of output.

Every candidate gets a small paid task before the first interview — $50 to $100, a real problem we need solved. But the task isn’t the whole assessment. We build in an iteration round. We give feedback on their submission and see how they respond to it. Every job depends on how well someone handles feedback. A work sample without a revision round only tells you half the story.

The candidate pool self-selects fast. The people who complete it, absorb the feedback, and come back stronger are the people you want.

“The closer the task is to day one reality — including the feedback loop — the faster you’ll know if the hire is right.”

The biggest improvement we made to hiring was removing resumes from the first stage entirely. Every candidate got the same real-world scenario they’d face in the role and 48 hours to respond. No strict format, no word limits — just their thinking. We reviewed these responses blindly, without names or backgrounds, before ever looking at a resume.

This came from a pattern we couldn’t ignore. We were hiring people with great credentials who underperformed, while overlooking candidates from non-traditional backgrounds who might have been better. Resumes were filtering for pedigree, not ability.

At first, it felt slower and more uncomfortable. Our hiring manager was used to quickly scanning resumes to build a shortlist. Evaluating scenario responses took more time. But the results were eye-opening.

The shortlist looked completely different. Candidates we would’ve normally rejected, career switchers, people without the right degrees, even someone returning after a break, submitted some of the strongest responses. Their thinking was sharper, more practical, and more creative than that of candidates with perfect-looking resumes.

We hired two people from that first round who wouldn’t have made it through a traditional process. Both became top performers within a year. One now leads a team despite having a two-year gap and no prior industry experience at the time.

It also changed our team in a meaningful way. We became more diverse in terms of backgrounds, experiences, and perspectives, not because we aimed for it, but because we stopped filtering people out too early. When you evaluate how people think instead of where they’ve been, the talent pool opens up.

The key is designing the right scenario. It should reflect real work, be specific enough to show capability, but still accessible to someone outside your industry. If it requires insider knowledge, you’ve just recreated the same bias in a different form.

Resumes tell you what someone has done. Scenarios show you how they think. And in most roles, especially in fast-moving teams, how someone thinks matters far more.

One unconventional method I’ve used to improve our hiring process at OneBlog is replacing traditional interviews and test assignments with what I call a “passion project pitch.” Instead of giving candidates a hypothetical task or grilling them with standard questions, I ask them to bring a paid project they’ve personally taken on, walk me through why they chose it, and explain how they executed it from start to finish.

This came from a frustration I had with conventional hiring. I kept meeting candidates who could ace interviews and crush sample assignments but then struggled with ambiguity once they were actually on the team. The skills that matter most at a startup aren’t just technical. They’re decision-making, resourcefulness, and the ability to own a problem without someone handing you a playbook. A polished portfolio doesn’t always reveal that. But listening to someone explain why they chose a specific project, how they scoped it, where they got stuck, and how they pushed through tells you almost everything you need to know.

The impact on our team composition has been significant. We’ve ended up with people who are naturally entrepreneurial, who think like owners rather than task completers. That mindset is hard to screen for in a traditional process, but it becomes obvious when someone is walking you through real work they initiated and delivered on their own terms. It also levels the playing field. Candidates who may not have prestigious resumes but have gone out and built something real get a genuine chance to shine.

For anyone looking to build a strong team, my key consideration is this: optimize your hiring process for agency, not just ability. Skills can be taught. Tools can be learned. But the instinct to take ownership, make decisions under uncertainty, and see something through without constant direction is incredibly difficult to train. Design your process to surface that quality and you’ll build a team that doesn’t just execute your vision but actively strengthens it.

We decided to change our hiring process from the traditional interview format to giving candidates some real world problems that we were actually struggling with at the time.

For example, we experienced a spike in false positives and decided to bring in a candidate and provide them with some anonymized detection output data and ask, “If you were given this, what would you do in the next 48 hours?” This created ambiguity and uncertainty and did not provide them with any “perfect data” to utilize, nor was there a right answer. The best candidates we interviewed did not try to come to the “right answer,” but instead asked insightful questions, defined the trade-offs, and created a decision based on the available information.

In the end, we hired one candidate who was able to challenge our assumptions during the interview process, and this hire later led to an extensive model refinement for our team.

This has shifted our entire team structure to hiring individuals to work in an ambiguous environment, not just those that interview well, which we found to decrease the number of bad hires, as we were able to see how the candidates thought before we hired them.

One thing we’ve been doing that works really well is when we open a new role, we don’t rely only on traditional hiring channels. We do a C-level push on LinkedIn. So myself, my co-founders, other leaders in the company, we all post about the role. Not just a job description, but a bit of a story around who we’re looking for and why.

If you do it right, those posts can get good reach. And then we usually put a small budget behind them, around $20 to $30, to boost them to a very specific audience. It’s simple, but it works.

For example, when we were hiring a Head of Sales, we created a post, added a short AI video, boosted it, and it actually went a bit viral. That’s how we ended up finding the right person. We didn’t use recruiters for that role, it all came through that process.

In terms of impact, you get a very different type of candidate. People who resonate with how you think, how you communicate, not just people applying because they saw a job opening.

One thing I’d say for anyone trying this, don’t just post a generic job description – in this case, the story and positioning matter more than the role itself. If it looks like every other hiring post, it won’t work.

Here’s my post, as an example: https://www.linkedin.com/posts/michael-maximoff_closeddeals-activity-7419782849001644033-lAGC

The most unconventional thing about our hiring process is that I often conduct a technical interview myself as CEO. Most candidates don’t expect that. They come prepared for strategy and vision questions, and I catch them off guard with specific, hands-on technical questions about the services they claim to know. That dynamic tells me a lot before we even get into the substance of the answer.

For engineering roles, I focus heavily on AWS Solution Architects with real hands-on experience. Certifications matter as a baseline, but they test theory. The real world is different. Knowing what a service does on paper doesn’t mean you know how it behaves under load, how to troubleshoot it when something breaks, or how to automate around its limitations. So I ask candidates to walk me through exactly how they’ve used specific services, and then I dig. I want to understand whether they can speak to the operational reality or whether they’re reciting documentation.

What consistently surprises me is how many candidates exaggerate their experience or lean on credentials when pressed. A lot of them eventually confess they don’t have the hands-on depth they implied. That’s useful information, but it reinforces why the verbal technical interview works: a resume and a certification can’t replicate the pressure of being asked a specific, detailed question in real time by someone who knows the answer.

The key consideration for anyone building a technical team is to test depth, not breadth. Candidates who claim equal strength across every domain are almost always overstating somewhere. Find the area they say they know best and go deep. That’s where you learn what you’re actually hiring.

One unconventional approach we took was treating hiring like an operational bottleneck to be diagnosed with data, not just a recruiting problem.

In mental healthcare, especially in the US, the constraint isn’t demand – it’s provider supply. We were facing a severe shortage of qualified clinicians, and traditional hiring processes were too slow and manual to keep up. So instead of just trying to “hire better,” we built an internal, data-driven system to analyze and optimize the entire hiring funnel.

We created a centralized “hiring data room” where we tracked conversion and drop-off at every stage – sourcing, screening, credential verification, interviews, and onboarding. This allowed us to identify that our biggest bottleneck wasn’t top-of-funnel volume, but the manual screening process.

The challenge is that provider screening is unusually complex:

– verifying state-by-state licensing

– confirming ability to prescribe controlled medications

– checking criminal history

– validating identity and credentials

We were spending massive human effort reviewing thousands of candidates just to find a small subset of qualified providers.

So we built AI tools to handle this layer:

– automated credential and compliance checks in seconds instead of hours

– filtering candidates based on real regulatory requirements

– prioritizing only high-probability, fully qualified providers for human review

On top of that, we extended the system beyond hiring:

– demand forecasting: predicting which states and specialties we need to hire for based on patient demand trends

– performance analytics: peer-review AI that evaluates provider performance and recommends improvements post-hire

Impact on team composition:

– dramatically increased the ratio of qualified candidates entering interviews

– reduced time spent on low-signal screening work

– allowed our hiring team to focus on quality, not volume

– improved geographic coverage by hiring proactively where demand is growing

– created a tighter feedback loop between hiring and provider performance

Don’t optimize hiring in isolation – treat it as a system connected to demand, compliance, and post-hire performance. The biggest gains came when we stopped thinking of hiring as a pipeline and started treating it like a data problem with measurable constraints.

Audition-style work previews keep people longer than credentials ever will.

Most startup hiring fails because the interviewing measures how good someone performs a conversation. Delivery roles call for something else entirely. A 2 to 3 hour paid task is similar to real work conditions and reveals more to you in one afternoon than 5 rounds of interviews. Candidates hired via work previews have been found by research to stay 40 to 60 percent longer than those hired just on credentials.

Well, that number changes when you use one more filter.

Pace tolerance is a better predictor of output consistency than any skill-set in the first 90 days. Startups are faster and have less guardrails than most people anticipate. In a team composed of 10 people, even if two of them stall because of ambiguity, they can hold up the whole operation by a day or more per week.

Start with the paying job before you post the job description. The candidates that appear without having to be sold are worth your time.

One unconventional approach we’ve taken is prioritising attitude and ownership over experience, while hiring internationally and promoting from within whenever possible.

Instead of focusing heavily on local talent or traditional credentials, we’ve intentionally expanded our hiring globally and looked for people who show initiative, adaptability, and a strong sense of responsibility. In several cases, we’ve also promoted individuals internally into larger roles rather than hiring externally.

The impact has been noticeable. We’ve built a team that takes more ownership of their work and is more aligned with the company’s pace and expectations. It’s also helped us identify high-potential individuals who may have been overlooked in a more traditional hiring process.

One key consideration is that this approach only works if you have strong alignment, clear expectations, and consistent management in place. Hiring for attitude over experience can backfire quickly without the right structure, but when supported properly, it creates a highly accountable and motivated team.

Hiring as a start-up at the beginning of a business venture can be scary and with a small team every addition to the team has a big impact on dynamics and results for the business.

As a result you might think that you need to really get the best of the best talent which can be expensive. However I strongly believe that you get a much bigger return on hiring someone more junior for many reasons:

– They are often more motivated to learn, adapt and invest energy into your business. It makes them more loyal to the cause of your business and more motivated to be loud and proud about their new job.

– They have less experience – yes, I think that’s a great thing because they think outside the box and are not stuck in what they already know has worked in the past. They are creative thinkers and want to contribute to solving problems. You don’t have to try to help them escape bad habits because they simply haven’t formed yet.

– They are generalists and can adapt and cover more than one specific role you are trying to fill in your business. This is great because your business is still evolving and you want this to be reflected in your workforce and for them to be able to react to sudden changes.

– It contributes to the team learning from each other and creates an inclusive culture.

– The most obvious reason, but I don’t consider it the most important one: Economically it allows flexibility for your business.

First, I recommend that startups not even try to compete with corporations using standard offering principles.

Don’t try to copy or outshine them – it’s practically impossible. Second, there’s no need – people who are suited to working in startups and corporate environments are fundamentally different from each other. Focus on what the person will do at your company. The more inspiring the mission behind your product, the easier hiring becomes. You need to be the opposite of a soulless corporate environment – and that’s actually an advantage if you lean into it.

Most importantly, give candidates what they can never get at a big company: real decision-making authority, fast approvals, minimal pointless meetings, interesting work, equity, and the chance to grow quickly. That package beats a slightly higher salary every time for the right person.

One of my biggest recruitment methods during my career were annual parties.

For the last tech company I started, I threw annual parties where we rented out night clubs, open bar, animal shows, magic shows, DJs, contortionists and more.

Most company parties only allow you to bring a spouse, at most.

We asked our team of 100 how many tickets they each needed (limit of around 400) and our engineers brought their engineer friends.

After the party, job applications would always skyrocket (mostly personal emails to the founders asking to chat).

We had well over 100 applicants for an open role, with details scattered across Google Sheets, questionnaire responses coming in via Google Forms. Overall, a bit of a mess.

Now it’s all in one place, built around how we actually work. Emails for each step of our process can be sent out from the dashboard, this alone will save us hours per job.

That’s been the theme of Q1 for us. I set a focus for the quarter: review every tool we’re paying for and work out whether we could build something better ourselves. The answer has been yes way more than I expected.

HR software was first. Didn’t like the UI, the review and development processes didn’t fit how we operate. Rebuilt it in about two days.

Here’s where it gets interesting for agencies and ecom teams though.

Everyone’s pitching on the same stack. Same platforms, same tools, same processes. But if you’re building custom tooling around how you actually work, that’s a genuine differentiator. Not a vague nod to “our internal process” that nobody’s ever written down.

It feels like a new frontier. And I think the ones who lean into it rather than fear it are going to pull away from the pack.

We’re investing heavily in putting AI at the centre of our ops across development, SEO and PPC, but not just asking our staff to use ChatGPT. I mean building real tools to solve real problems and frictions that come up in our daily work.