Tag: Talent Evaluation

Tools, methods and techniques for candidate competency evaluation.

Evaluating The Talent Of Cyborgs

A cyborg is a being that is part biological and part mechanical or electronic. The term was originally coined to describe humans enhanced with technology.

Today, in a way, we have all become a type of cyborg.

Without technology, most of us would accomplish only a fraction of what we do today.

As technology has advanced, the amount of work a single person can accomplish has increased dramatically.

So, in a world like this, how should we evaluate the talent of candidates during recruitment?

Should we measure only their raw talent? Or should we measure what they can achieve with modern digital tools?

Raw Talent

Raw talent is a person’s processing power.

It includes their ability to understand new concepts quickly, think logically, solve problems, learn rapidly, exercise good judgment, and communicate effectively.

These are the underlying abilities that remain valuable regardless of which tools are available.

Talent with Digital Tools

Talent with digital tools is a person’s real-world productivity.

It measures how effectively they use Google, AI, documentation, IDEs, design tools, automation, and other technologies. It reflects how quickly they can produce high-quality work and how well they combine multiple tools into an efficient workflow.

Assessing Only One Side

Some interviewers try to eliminate every digital aid.

They ask candidates to write algorithms on a whiteboard, remember obscure syntax, or solve problems they would normally Google in 30 seconds.

While this reveals certain aspects of raw ability, it often ignores how people actually work.

There is the opposite mistake too.

Candidates are allowed to use AI for everything, and interviewers never discover whether the candidate truly understands the solution. The candidate may simply be copying AI-generated answers without being able to verify, adapt, or troubleshoot them.

Neither approach gives the full picture.

Performance = Raw Ability × Tool Effectiveness

The strongest employees usually have:

  • Solid fundamentals.
  • Good judgment.
  • Excellent use of modern tools.

Someone with exceptional raw talent but poor tool usage may not be very productive.

Likewise, someone who only knows how to prompt AI, but lacks fundamental understanding, will eventually hit a ceiling because they cannot verify, adjust or troubleshoot the AI’s output.

What Should You Test in an Interview?

A better approach is to split the assessment into two parts.

1 – Fundamentals (No AI)

Evaluate the candidate’s:

  • Logical reasoning.
  • Understanding of core concepts.
  • Ability to explain how something works.
  • Ability to debug a simple problem.
  • Ability to discuss trade-offs and justify decisions.

2 – Practical Task (AI Allowed)

Give candidates a realistic work assignment.

Observe:

  • How they use AI.
  • Why they accept or reject AI suggestions.
  • Whether they verify AI-generated answers.
  • The quality of the final result, not just the speed.

This reflects how they will actually perform on the job.

Weighting Must Be Changed to the Role

The balance between raw ability and tool usage should vary depending on the role.

Junior engineers should be evaluated more on raw ability and learning potential. AI skills can be learned quickly, but strong fundamentals take years to develop.

Mid-level engineers should demonstrate both solid technical foundations and effective use of modern tools.

Senior engineers, architects, and project managers should be evaluated more heavily on judgment, decision-making, communication, system thinking, and their ability to use technology to increase the productivity of themselves and their teams.

The Shift of the Evaluation

As AI becomes a standard part of professional work, hiring solely based on raw memory and intelligence is becoming less predictive of success.

At the same time, hiring solely based on AI-assisted output is risky too.

The candidates who consistently perform best are those with strong fundamentals who know how to amplify their abilities with modern tools.

6 Level Buckets: A Framework to Classify Anyone’s AI Expertise

Everybody claims to be an AI expert. Of course they are. But how do you measure it?

Level 0: AI Unaware

Has little or no understanding of modern AI tools. May have heard of ChatGPT but doesn’t use AI in their work.

Evaluation: Ask how they currently perform common work tasks such as research, writing, problem-solving, or coding. Person at this level typically do not mention AI tools or are unable to explain how AI could improve their workflow.

Level 1: AI User

Uses AI for simple tasks such as asking questions, writing emails, summarising text, or generating ideas. Mostly copies and pastes prompts.

Evidence: Occasionally uses AI assistants for simple tasks.

Evaluation: Ask to complete a simple task using an AI assistant, such as drafting an email, summarising a document, or generating ideas. Observe whether they can write an effective prompt and critically review the AI’s response instead of accepting it without question.

Level 2: AI Practitioner

Regularly integrates AI into daily work. Understands prompt engineering, evaluates AI output, chains prompts together, and knows each tool’s strengths and limitations.

Evidence: Reliably improves work quality and productivity with AI.

Evaluation: Present a realistic work scenario and ask how they would use AI to complete it. Look for structured prompting, iterative refinement, validation of AI-generated content, and an understanding of when AI should or should not be used.

Level 3: AI Builder

Designs AI-powered workflows or applications. Uses APIs, automation platforms, RAG, agents, embeddings, MCPs, or AI SDKs to solve business problems. Doesn’t necessarily build foundation models.

Evidence: Designs AI-powered workflows and automations.

Evaluation: Ask to explain or design an AI-powered solution for a business problem. They should be able to describe the overall architecture, data flow, model selection, integration points, and trade-offs rather than simply naming AI technologies.

Level 4: AI Engineer

Builds and deploys production AI systems. Fine-tunes models, evaluates performance, manages infrastructure, optimises inference, handles security, monitoring, and scalability.

Evidence: Builds and deploys AI solutions in production.

Evaluation: Discuss production experience by exploring topics such as deployment, model evaluation, latency, cost optimisation, security, monitoring, and reliability. They hould be able to explain technical decisions, lessons learned, and challenges from real-world AI systems they have built or maintained.

Level 5: AI Researcher / Innovator

Advances the field through research or significant innovation. Develops new architectures, training methods, evaluation techniques, or publishes original work.

Evidence: Conducts advanced AI engineering or research.

Evaluation: Evaluate original contributions rather than general knowledge. Discuss research publications, patents, open-source contributions, novel algorithms, benchmarking methodologies, or significant technical innovations. The focus should be on how the candidate has advanced AI beyond applying existing techniques.

Two Types of CVs – Which One Do You Have?

When applying for jobs, your CV is crucial in getting noticed and securing an interview. In a previous post, I discussed how simply enhancing a CV isn’t the only factor affecting your job search. However, this doesn’t mean we should neglect optimizing our CVs before applying.

Personally, when reviewing or helping someone enhance their CV, I notice two main types of optimization.

CVs Optimized for Shortlisting

First, there are CVs optimized for shortlisting. These CVs are designed to pass applicant tracking systems (ATS) and capture recruiters’ attention. They include relevant keywords from the job description, a clean, structured format, and highlights of your skills and achievements. The goal is to get past initial filters and increase your chances of an interview.

CVs Optimized for Truthfulness

Second, there are CVs optimized for truthfulness. These CVs focus on accuracy and honesty. Instead of manipulating content to match job descriptions, they reflect your real skills and experience, avoid exaggeration or buzzwords, and provide a clear, authentic view of your career. This builds realistic expectations and fosters trust with potential employers.

Which type is better? That’s the question I keep pondering. I’ve noticed most people try to make their CVs pass computer filters and catch a recruiter’s eye. Personally, I believe prioritizing truthfulness is most important, something often lacking in today’s job market. When everyone’s worried about keywords and how their CV looks to computers. I’m wondering if we’ve lost sight of the value of genuine representation in our professional narratives. It’s a thought I wanted to share and explore.

This is my personal opinion. I’d love to hear your thoughts in the comments!

Other Side: Things Job Applicants Never Tell You

While we’ve explored the less-discussed aspects of the recruitment process from the recruiters’ perspective, it’s equally important to consider the other side of the equation- job applicants. Just as recruiters have their unspoken realities, job seekers also have things they rarely disclose during the hiring process. Understanding these hidden truths can help both recruiters and employers build more authentic and productive relationships with potential employees.

The Applicant’s Unspoken Realities

Current Job Satisfaction

What They Say: “I’m looking for new challenges.”

What They Mean: “I’m unhappy with my current job, boss, or company culture.”

Why It Matters: Knowing this can help you understand their motivations better and assess if your company can truly offer what they are seeking.

True Career Aspirations

What They Say: “I’m excited about this position.”

What They Mean: “I see this job as a stepping stone to something else.”

Why It Matters: Recognizing their long-term goals can help in offering roles that align better with their career paths and increase retention.

Strengths and Weaknesses

What They Say: “My biggest weakness is that I’m too much of a perfectionist.”

What They Mean: “I’m mentioning a safe weakness to avoid appearing incompetent.”

Why It Matters: Digging deeper can reveal true areas for improvement and how they handle challenges.

Reason for Leaving Previous Job

What They Say: “I’m looking for growth opportunities.”

What They Mean: “I left because of conflicts, dissatisfaction, or job insecurity.”

Why It Matters: Understanding the real reason can help in assessing their fit within your organization’s culture.

Work-Life Balance Preferences

What They Say: “I’m flexible with working hours.”

What They Mean: “I need a job that respects my personal time and family commitments.”

Why It Matters: Being clear about work-life balance can help attract candidates who align with your company’s policies and culture.

Salary Expectations

What They Say: “I’m open to discussing salary.”

What They Mean: “I have a minimum salary requirement but don’t want to seem greedy.”

Why It Matters: Having an open and honest discussion about salary expectations can prevent future dissatisfaction and turnover.

Company Research

What They Say: “I’ve researched your company thoroughly.”

What They Mean: “I’ve skimmed through your website and read a few reviews.”

Why It Matters: Providing more information about your company’s culture, mission, and values can help candidates make more informed decisions.

Bridging the Gap

Just as recruiters try to understand and mitigate biases in their processes, job seekers often aim to present the best version of themselves, sometimes glossing over less favorable truths. To make better hiring decisions, both parties can benefit from open communication and mutual understanding.

For Recruiters

  • Encourage Honesty: Create a safe space for applicants to share their true aspirations and concerns.
  • Ask Open-Ended Questions: This can help reveal more about the candidate’s genuine motivations and experiences.
  • Provide Clear Information: Be upfront about job expectations, company culture, and growth opportunities to help candidates make informed decisions.

For Job Seekers

  • Be Transparent: Honesty about your career goals and expectations can help you find a job that truly fits your needs.
  • Research Thoroughly: Understanding the company’s values and culture can help you assess if it’s the right place for you.
  • Communicate Needs: Clearly express your requirements for work-life balance, career growth, and other important factors.

By recognizing and addressing the unspoken realities on both sides, we can work towards a more authentic and effective hiring process. After all, transparency and honesty are key to building trust and ensuring long-term satisfaction for both employers and employees.