Tech hiring is at a crossroads. The standard code challenge, once a trusted test of skill, is losing ground as AI tools like ChatGPT quietly rewrite the rules. Suddenly, quick coding tests can be cracked with a few AI prompts, blurring the line between authentic skill and assisted answers.
At Get on Board, we've seen the shift firsthand. Deep portfolio reviews increasingly outshine rigid coding tests when it comes to spotting real tech talent. Let's break down why portfolios offer a richer, more reliable window into a candidate’s abilities.
🤖 Code challenges: losing their edge in the AI era
But AI-assisted coding changes everything. Tools like ChatGPT, Cursor, Windsurf, Claude Code or GitHub Copilot can whip out optimized code snippets faster than many developers, casting doubt on whether the output reflects the candidate’s own craft.
- AI interference: When code is AI-generated or AI-inspired, it’s tough to gauge true individual skill.
- Missing team dynamics: Code challenges focus on solo work, ignoring essential collaboration and communication skills.
- Time pressure skews results: Some brilliant programmers need space to think rather than ticking clocks.
📁 Portfolio reviews reveal the real story behind the code
- Authentic skill evolution: Portfolios reflect ongoing learning and adaptability, not a single moment frozen in time.
- Collaboration in action: Pull requests, code reviews, and issue discussions reveal communication skills and teamwork.
- Context matters: Understanding why and how decisions were made paints a fuller picture than a decontextualized code snippet.
True tech hiring success comes from understanding not just what is coded, but the story behind the code.
Moreover, AI-based tools can uncover hidden gems and validate skills beyond resumes. Read more about this in our article on AI-driven talent insights.
🔍 How Latin American recruiters can adapt
- Make portfolio review your foundation: Look beyond snapshots; investigate real work histories for authentic growth.
- Use code challenges wisely: Prefer tailored challenges emphasizing system design or architecture, where AI help is less straightforward.
- Lean on AI tools: Platforms like Superpower AI can quickly analyze portfolios and reduce human bias.
- Train your team: Help interviewers spot teamwork and problem-solving narratives within portfolios.
- Encourage storytelling: Ask candidates to explain decisions behind their code for genuine insight.