Balancing Skills Assessments With Traditional Interviews

We've all heard the horror stories of candidates doing hours of free work for a job interview project, only to never hear back. It’s a practice that feels unfair and unethical. So how do we test for fit and skill without stepping outside ethical lines? It’s a question that needs thoughtful consideration. We've spent years refining our recruitment process to ensure it’s both effective and respectful of candidates’ time and effort. The traditional interview process often falls short when it comes to truly understanding a candidate's skills and fit for the company. This has led some companies to request free portfolio work or hypothetical projects, which can be ethically problematic. Here’s how we do it: Structured Interviews: We rely heavily on behavioral-based interview questions and practical discussions that allow us to gauge a candidate’s experience, thought process and cultural fit based on their actions and results in the past. Hypothetical Problem Sets: For skills assessment, we provide completely hypothetical problems that reflect the type of work the candidate would encounter. This ensures we get a glimpse of their problem-solving abilities without exploiting their efforts. Paid Work Trials: If the work is directly related to a real problem set or project, we compensate candidates for their time and work effort. This respects their effort and shows that we value their contribution. Keep in mind that for 2 and 3, these should be done later in the process after a candidate is equally excited about the opportunity and has at least a decent likelihood of being selected.  We believe that every interaction with a candidate should reflect our core values of respect and fairness. By adopting these practices, we maintain ethical hiring standards and help build the reputations of our clients as companies that truly value their people—even before they join the team. P.S. Have you experienced or witnessed unethical hiring practices? Share your stories and insights in the comments—I’d love to hear from you. #EthicalHiring #Recruitment #CandidateExperience #CreativeAlignments #Leadership 

Recruiting leaders in our community have wrestled with how to balance AI-enabled candidates. We worked with a team that's hiring a data analyst to develop an approach to assess for SQL skills. Here's how we structured the process to try to balance the very likely possibility of candidates using AI tools. First, making use of new tools has always been disruptive to recruiting and is the exciting part of moving our collective work forward. On the one hand, when you have someone join your team you want them to be resourceful and efficient. This is a really positive and great thing! On the other hand, you also want to make sure they understand how things work and use their individual creativity to think of new and novel solutions. Here's the process we're trying: Take-home assignment Data: we provided the database schema and sample set of data of typical recruiting data - jobs, applications, offers Questions: we asked a series of questions about the data for common use cases to test both recruiting intuition and hard skills. For example, calculating offer acceptance rates test for their intuition on anchoring to the appropriate date, handling candidates with multiple offers, and joining tables to get to a good answer. So yes, candidates can and will likely use some 'assistance' but AI responses are only as good as the prompt. Assuming the logic and explanation make sense, you can then dig deeper at onsite. Onsite interview Test their understanding by continuing to build upon the take-home assignment in a live interview. For example, pull up a candidate's response to calculating offer acceptance rates and ask them to adapt it to group by each department. If they didn't write it or understand their initial take-home response, it will be very evident in the live interview. However, someone that understood the result and just used AI to build it faster could demonstrate how to make the adjustments Curiosity - a characteristic of a high performing analyst is their level of curiosity. When given a dataset they can't help but explore it beyond the prompt. It's like an artist with paint and a canvas, the possibilities! So a great open question to assess for both curiosity and recruiting domain knowledge is to ask what other questions they have about the data, the process that drives the inputs, or other metrics that could be derived. What techniques are you trying to find a healthy balance to assess AI-enabled candidates?

Poor management of limited resources for product development ruins many startups. Especially when you hire expensive local devs too early. Solution: A hybrid team. CTO and core devs - local, other team - offshore. Hovewer, how do you ensure you’re bringing in the right devs for both skill and culture, especially in an early-stage startup? Here’s a 5-step guide I’ve used successfully: 1. Kick things off with a coding test. But don’t just focus on algorithms; include project-based questions to assess problem-solving abilities. 2. Initial video interview - this is your culture check. Look for indicators of alignment with your company’s values, mission, and team dynamics. 3. Have your lead developer dig into the nitty-gritty of the candidate’s experience. Cover topics like architecture, code reviews, and past project contributions. 4. This one’s unique: invite the candidate to a non-formal meeting with potential future teammates. You’ll learn how they fit in with the group dynamics, beyond just technical skills. 5. Combine scores from all stages, taking both hard and soft skills into account. Make an offer that includes clear growth paths and benefits. The goal is to balance technical assessments with cultural fit checks, giving you a 360-view of the candidate. And trust me, a well-structured remote interview process can be a game-changer. What’s your approach to picking the right talent? #RemoteInterviews #TechHiring #SaaS #CTOTalks