Incept Labs required specific skilled engineers (Data and DevOps) who think from first principles, had experience at high-growth startups, and deep technical fundamentals
What they used before
Mostly a mix of manual screening + online job boards
Key Challenges
It's always difficult hiring for roles with specific criteria
Incept Labs needed a Senior Data Engineer and a DevOps Engineer with deep technical expertise, first-principles thinking, and experience scaling infrastructure at high-growth startups
Key Outcomes
Incept Labs were able to hire 2 exceptional engineers in ~14 days using our platform.
Both hires had terrific job performance — after months of failed searches through traditional channels
What They Were Doing Before
Incept Labs tried several things to find strong engineers. And nothing worked.
Job Boards: Posted on LinkedIn, AngelList —all the usual suspects. Applications came in, but the quality was super weak. Junior developers applying for senior roles. People with "Kubernetes" on their resume who'd never actually managed a production cluster. AI engineers who'd fine-tuned one model and called themselves experts.
Recruiters: Worked with multiple recruitment agencies who promised "pre-screened technical talent." The recruiters sent candidates with impressive CVs, but five minutes into a technical conversation, it became clear they didn't understand the fundamentals. They'd memorized frameworks but couldn't think from first principles.
The process looked like this:
Post the role everywhere and ask everyone they knew
Get flooded with applications from unqualified candidates
Screen 20-30 resumes, most of which were clearly unfit
Interview 5-10 candidates who sounded good on paper
Watch them fail basic first-principles technical questions
Repeat for months
Start questioning if this hire is even possible
Challenges & Pain Points
They had specific criteria to hire for tech roles.
1. Specific-Skill Requirements That Most Candidates Couldn't Meet
Needed candidates who had -
Built and managed Kubernetes clusters at scale
First-principles thinking: The ability to look at a problem and architect a solution from scratch, not just copy-paste from Stack Overflow or blindly follow a framework.
Experience at high-growth startups: People who'd seen the chaos of rapid scaling and knew how to build systems that wouldn't break under pressure.
Deep technical fundamentals: Not surface-level knowledge. Real understanding of distributed systems, data pipelines, infrastructure as code, LLM orchestration.
2. Lack of Fundamental Skills in the Candidate Pool
The candidates they were seeing fell into two categories:
Category 1: Resume Padders
People who listed every buzzword under the sun—Kubernetes, Docker, Terraform, PyTorch, LangChain, Vector DBs—but couldn't explain how any of it actually worked.
Category 2: Framework Followers
Engineers who could use tools but couldn't think independently. Ask them to solve a new problem or architect a system from first principles? Blank stares.
3. Traditional Hiring Methods Couldn't Filter for What Actually Mattered
They did manual phone screens, which wasn't helping. They'd ask surface-level questions that can't reveal true depth -
"What's the difference between a Pod and a Deployment?"
"Explain how transformers work."
"What's your experience with CI/CD?"
By the time Incept Labs got to the technical interview stage, they'd already wasted hours on candidates who had no business being there. And the right candidates—the ones who could actually do this work—weren't making it through the broken filter.
4. High Agency and Bias for Action Were Non-Negotiable
Incept Labs wasn't just looking for technical skill. They needed people with:
High agency: The ability to take ownership, make decisions, and move forward without constant hand-holding
Bias for action: The instinct to build and ship, not overthink and wait for perfect information
These are cultural traits, not technical skills. And they're impossible to assess from a resume or a 30-minute phone screen.
For a startup building foundational AI infrastructure, that doesn't work. They needed engineers who could see a problem, propose a solution, and execute—without needing their hand held.
How Utkrusht's Assessment Platform Helped
The High-Level Process:
Incept Labs explained their requirements: Senior Data Engineer and DevOps Engineer with Kubernetes at scale, first-principles thinking, and high agency.
Posted the job (Utkrusht also sourced candidates from our pre-vetted database) and shared the assessment link to candidates
All candidates completed "build something" simulation assessments: Utkrusht's assessments are different — candidates have to build something in 20 minutes. 20-minute real-world technical challenges that revealed depth, not just surface knowledge.
Utkrusht's platform shortlisted and sent 5 qualified candidates: All had passed the assessments. All had the technical depth Incept Labs needed. All had proof-of-skill.
Incept Labs interviewed all 5 and hired 2: One Data Engineer, one DevOps Engineer. Both cleared because the assessments had already validated their skills.
Timeline: ~14 days from position opened to offers accepted.
"We spent months looking for engineers who could think from first principles and handle the scale we needed. Job boards gave us junior candidates. Recruiters gave us resume padders. Our networks dried up. We were starting to think this hire was impossible—until Utkrusht showed us it wasn't."
— Incept Labs Founding Team
Key Outcomes and Results
Incept Labs didn't just fill two standard looking roles. They found two engineers with their specific criteria and requirements in ~14 days, something that almost never happens when you're hiring for highly specialized, senior positions
~14 days from first conversation to offers accepted
5 strong candidates delivered who had shown proof-of-skill
2 exceptional hires who hit the ground up and running from day 1
Cost Savings: Impossible to Quantify, Impossible to Ignore
Let's do the math on what Incept Labs avoided:
Months of failed hiring:
3+ months of an empty role = 3 months of project delays, missed milestones, and competitive disadvantage
Founder/CTO time wasted on bad interviews = 40+ hours @ $200+/hour = $8,000+ in opportunity cost
Recruiter fees for failed placements = $10,000+ wasted
Bad hires they avoided:
1 bad senior hire = 6-12 months of reduced productivity + severance + team morale damage = $100,000+ in total cost
This saved Incept Labs from the compounding cost of hiring wrong or not hiring at all.
Process Shift: Assessment-First Hiring for Tech Roles
Incept Labs learned something that will change how they hire forever — For tech roles, resume-first hiring is a complete waste of time. Proof-of-Skill via Assessment-first hiring works every single time.
When you make someone build something in 20 minutes — no Google, no hand-holding, just raw technical skill—you learn everything you need to know.
Can they think from first principles? The assessment shows you
Do they understand fundamentals or just frameworks? The assessment shows you
Can they execute under pressure? The assessment shows you
What Stood Out Most
When we asked Incept Labs what made the biggest difference, they pointed to one thing: how Utkrusht accurately assesses and evaluates candidates and identifies the 10 strongest.
Most technical assessments test whether you can answer questions about concepts—not whether you can apply those concepts to solve real problems.
For Incept Labs, this was the breakthrough. They'd been trying to assess these qualities through resumes and interviews for months. It didn't work.
Utkrusht's "build something" assessments revealed depth in 20 minutes that a resume never could.
Why Incept Labs Chose Utkrusht's Platform Over Others
Few things -
1. Accurately Identifies Quality Candidates from the Huge Applicant Pool
Most platforms and recruiters operate at scale. They're designed for companies hiring 100+ generic software engineers, not for small companies hiring for few exceptional senior engineers for foundational AI work.
2. Assessment Philosophy That Actually Tests What Matters
Utkrusht's "build something" assessments tested for all of this. And when Incept Labs saw the assessment results, they immediately understood why these candidates were different from everyone else they'd interviewed.
The assessments revealed:
✅ Depth of understanding: Not just "I know Docker," but "I can architect containerized systems for scale and cost efficiency."
✅ First-principles thinking: The ability to solve novel problems without relying on pre-built solutions.
✅ Execution speed: Can they build under pressure, or do they freeze?
✅ Technical judgment: Do they make smart trade-offs between speed, cost, and reliability?
3. Also Access to Pre-Vetted Candidate Database Saved Months of Wasted Time
Incept Labs didn't have time to interview 50 candidates hoping to find 1 good one. They needed a shortlist of people who'd already proven their technical depth—and that's exactly what Utkrusht provided.
By maintaining a pre-vetted database of engineers who'd completed rigorous assessments, Utkrusht eliminated the most painful part of hiring: the endless screening of unqualified candidates.
"Most assessments test whether you've memorized things. Utkrusht's assessments test whether you can actually build."
What's Next
Incept Labs isn't going back to job boards and recruiters. They're not posting on LinkedIn and hoping. They're not working with recruiters who send generic candidates. They're not wasting months on people who can't pass basic technical challenges.
They've seen what assessment-first hiring can do, and the difference is night and day.
When they need to scale their team further—whether it's more AI engineers, infrastructure engineers, or data engineers—they know exactly where to go.
For companies where technical depth is everything, assessment-first hiring isn't optional—it's the only approach that works.
"We needed engineers who could build foundational AI systems, not just use pre-built tools. Utkrusht's 'build something' assessments filtered for exactly that—and both hires exceeded our expectations.
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