According to GeekWire, Seattle tech veteran Nikesh Parekh has launched Provn, a startup aiming to disrupt how companies recruit AI talent by replacing traditional resumes with portfolios of real work and challenge-based assessments. The platform facilitates “AI challenges” where candidates build AI agents or solve business problems, records video walkthroughs, and uses analytics to measure performance. Provn is targeting both large companies that regularly hire early- and mid-career information workers and smaller startups without recruiting teams, with partners including Read AI, Yoodli, and other Seattle-area employers. The self-funded startup plans to raise a seed round and will charge employers per hire while offering premium tools for candidates, building on Parekh’s background as co-founder of Suplari (acquired by Microsoft in 2021) and his work on Copilot Studio and Power Platform. This ambitious approach enters a crowded field where fundamental hiring problems have proven stubbornly resistant to technological solutions.
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The Fundamental Flaw in Skills-Based Hiring
Provn’s premise that skills assessments can replace resume screening sounds compelling, but it overlooks a critical reality: most companies don’t actually hire based on skills alone. Organizational psychology research consistently shows that hiring decisions are influenced by factors like cultural fit, communication style, educational pedigree, and network connections—elements that traditional resumes capture imperfectly but that pure skills assessments miss entirely. The company’s approach assumes that what companies say they want (skills) aligns with what they actually hire for (a complex mix of qualifications and intangibles). This disconnect has doomed many previous skills-first platforms that discovered too late that hiring managers still wanted to see where candidates worked previously and what schools they attended.
The Coming Assessment Fatigue Crisis
One of the biggest unaddressed challenges in Provn’s model is the growing problem of candidate assessment fatigue. As more companies adopt lengthy technical evaluations, qualified candidates are becoming increasingly selective about which assessments they’ll complete. High-demand AI talent—the very people Provn wants to attract—are already inundated with coding challenges, take-home projects, and multi-stage interviews. Adding another layer of “AI challenges” and video walkthroughs risks creating exactly the friction that discourages top performers from engaging. Unlike traditional resumes that candidates can reuse across multiple applications, Provn’s intensive assessments require significant time investment for each opportunity, potentially limiting the platform’s appeal to the most sought-after talent.
The Market Timing Paradox
Provn is launching during one of the most paradoxical moments in tech hiring history. While AI skills are in unprecedented demand, the broader tech job market has seen massive layoffs and hiring freezes. This creates a challenging environment for any hiring-focused startup: companies are simultaneously desperate for AI talent but cutting recruiting budgets and becoming more risk-averse about new hiring tools. The platform’s planned revenue model—charging per hire—faces particular headwinds when companies are reducing overall hiring volumes. Previous hiring platform successes like LinkedIn and Indeed gained traction during periods of hiring expansion, not contraction, suggesting Provn may be fighting against broader market currents that could limit adoption.
The Limits of Technical Evaluation
While Provn aims to go beyond “narrow” technical testing tools like HackerRank, the fundamental challenge of evaluating AI talent through standardized assessments remains. Real-world AI work involves ambiguity, collaboration, business context, and iterative problem-solving—elements that are difficult to capture in any assessment format. Many failed hiring platforms have discovered that the skills that make someone successful in timed challenges don’t necessarily predict on-the-job performance. More concerning, standardized assessments often disadvantage candidates from non-traditional backgrounds who may have exceptional practical skills but lack experience with the specific format or types of problems presented in technical evaluations.
The Crowded Competitive Landscape
Provn enters a space already crowded with well-funded competitors, each attacking different parts of the hiring problem. Technical interviewing platforms like Karat have established relationships with major tech companies, while AI-powered screening tools are being integrated directly into existing ATS systems. More concerning for Provn’s differentiation strategy: LinkedIn and Indeed are rapidly adding AI capabilities to their existing massive networks. The platform’s focus on Seattle-area partnerships provides an initial beachhead but may limit scaling potential against competitors with global reach. Previous specialized hiring platforms have struggled to achieve the network effects needed to become sustainable businesses, often getting acquired by larger players or pivoting to enterprise solutions.
A Realistic Path to Impact
For Provn to succeed where others have struggled, the company will need to demonstrate clear ROI in an environment where hiring managers are increasingly skeptical of “silver bullet” solutions. The most viable path may be focusing on specific high-volume hiring use cases where standardized assessments have proven value—such as entry-level AI roles or technical support positions—rather than attempting to replace resumes across the entire hiring spectrum. Partnering with educational institutions and bootcamps to create certification pathways could also provide a more sustainable talent pipeline than trying to attract already-employed top performers. Ultimately, the platform’s success will depend on whether it can deliver measurable improvements in hiring quality and retention rates—metrics that have eluded many previous attempts to “fix” technical hiring.
