Testlio blog

For a long time, we spoke about “AI agents” like they were a future concept, something that might eventually book flights, run workflows, or make payments on our behalf.

Accessibility and localization often seem like separate disciplines, each with its own set of guidelines and goals.

Over the past few years, model providers have invested heavily in “guardrails”: safety layers around large language models that detect risky content, block some harmful queries, and make systems harder to jailbreak.

AI testing careers are shifting in ways that most people in QA are not fully prepared for, and the changes are creating opportunities that did not exist even a few years ago.

AI systems change faster than traditional QA models can react, which means quality risks now emerge in real time rather than at release.

AI is evolving faster than the guardrails meant to validate it, leaving organizations exposed to compliance risk, model drift, opaque decision paths, and breakdowns in trust.

Solution combats AI hallucinations, bias, and privacy threats as early-adopter data shows 82% of AI bugs stem from misinformation and high-severity accuracy failures.

Across industries, AI systems are being scrutinized under new laws that demand proof of fairness, transparency, and human oversight.

Two weeks ago, our team gathered in Mexico City for our annual company offsite, LionFest, where we celebrated all the wins and milestones we achieved this year.