Systems | Development | Analytics | API | Testing

Quality People: Gastón Marichal on Why Agentic QA's Hardest Problem Isn't the Technology

A conversation with Gastón Marichal, QA Manager at QAlified, on why the hardest part of agentic QA has nothing to do with the technology. In the first installment of this series, we heard from Huy Tieu, a Katalon product manager building an AI quality companion from the inside. This time we wanted the other side of the table: someone who has to make agentic QA work for real client teams, on real delivery timelines, with real consequences if it goes wrong.

CI/CD Testing: Complete Guide To Continuous Testing (2026)

CI/CD testing is the practice of running automated tests throughout a Continuous Integration and Continuous Delivery (CI/CD) pipeline to validate every code change before deployment. By automating unit, integration, API, and end-to-end tests, teams can catch bugs early, improve code quality, and release software faster with confidence.

What Is Vibe Testing? A Practical Guide For Developers

Vibe testing is what happens when the way software gets built changes faster than the way it gets tested. For years, QA worked on a simple assumption: developers write the code, testers verify it. That assumption breaks down when the code is being generated by an AI from a plain English prompt. The person shipping the feature may not have written a single line of it – and may not fully understand how it works under the hood.

Flexible Crypto Invoicing: How Configurable Payment Windows Support Complex Business Scenarios

Cryptocurrency transactions are widely recognized for their settlement speed, with transfers often processing and finalizing in just a few minutes. While rapid execution is a core advantage of blockchain technology, digital payment workflows must accommodate more than just instant execution. Many corporate setups-such as subscription billing, reservation management, account funding, and enterprise B2B contracts-require structural flexibility that standard automated systems cannot support due to internal approval delays or operational buffer times.

7 Best Unstructured Data Tools for Enterprise AI (2026 List)

Enterprise AI depends on data that was never designed for AI. Most business knowledge is not sitting neatly in rows and columns. It is spread across documents, emails, chats, tickets, logs, telemetry streams, PDFs, customer conversations, search indexes, knowledge bases, product content, operational systems, and digital experience platforms.

Best 7 Virtual CDN (vCDN) Providers in 2026

Organizations no longer deliver content through a single website hosted in one region. Modern digital services power everything from SaaS applications and ecommerce stores to media platforms, gaming environments, APIs, software downloads, and AI-driven applications. Every interaction depends on fast, reliable delivery regardless of where users are located or how network conditions change throughout the day.

Real-Time Fraud Detection Pipelines: How Fintechs Use ETL for Streaming Data

Your fraud detection system analyzes yesterday's transactions while criminals steal millions today. Financial institutions lose an estimated $33 billion annually to card fraud alone, much of it preventable with real-time detection capabilities. Traditional batch processing that analyzes data hours or days after transactions occur simply cannot keep pace with sophisticated fraud schemes exploiting the settlement window gap.

How to Consolidate Multi-Bank Transaction Data With Low-Code ETL

Every finance team managing multiple banking relationships knows the pain: downloading statements from six different portals, copying transaction data into spreadsheets, and spending hours reconciling figures that should match but don't always align. With businesses losing significant productivity due to manual data handling and delayed system synchronization, multi-bank data consolidation has become a critical operational challenge.

How to Build a Scalable Enterprise Testing Strategy for Engineering Teams

Enterprise software today isn't just complex, it's mission-critical. A single production issue can disrupt operations, impact revenue, and erode customer trust overnight. Yet despite years of investment in enterprise test automation and growing QA headcount, many organizations still ship broken software and miss release windows. The uncomfortable truth? Enterprise software doesn't fail because teams aren't testing enough.

Automating the Exception: How a Second LLM Judge Drives Straight-Through Processing

Document-centric workflows have been difficult to automate and required human intervention. Attempts to automate document handling often failed or did not scale, because legacy intelligent document processing (IDP) systems were fragile. They often required manually retraining models on dozens of documents just to identify specific fields—only to repeat the process whenever a format changes. The result was a costly cycle of maintenance and manual data entry.