InfoQ - Programming - Articles

Article: Artificial Intelligence-Driven Phishing: How Phishing Technique Is Evolving and Implemented

Marco Rizzi — Mon, 08 Jun 2026 11:00:00 GMT

In this article, the author examines how AI is transforming phishing from a manual, targeted activity into an automated and scalable attack model. The article breaks down each stage of the phishing lifecycle, showing how AI improves reconnaissance, profiling, content generation, delivery, and interaction, while outlining layered defenses that combine controls, processes, and user awareness.

By Marco Rizzi

Article: The Technology Adoption Curve, Twenty Years On

Renato Losio, Dio Synodinos — Mon, 08 Jun 2026 08:30:00 GMT

Today, June 8th, InfoQ celebrates 20 years. This is not a comprehensive history, but a deliberately selective look at the technologies and practices InfoQ identified early, where they sit on the adoption curve in 2026, and how that curve may evolve over the next five to ten years.

By Renato Losio, Dio Synodinos

Article Series: Securing the AI Stack: from Model to Production

Claudio Masolo — Fri, 05 Jun 2026 09:00:00 GMT

This series provides your roadmap for the machine age, exploring how to move from vulnerable prototypes to resilient systems through layered defense, robust MLOps, and integrated governance.

By Claudio Masolo

Article: Why Vector Search Alone Isn't Enough: Hybrid Retrieval for RAG

Aaditya Chauhan — Tue, 02 Jun 2026 09:00:00 GMT

In this article, author Aaditya Chauhan discusses the limitations of RAG pipelines based purely on vector search and how an internal omni-search application using Reciprocal Rank Fusion (RRF) that combines BM25 and vector results, can enhance the search solution.

By Aaditya Chauhan

Article: The AI Productivity Paradox in Test Automation: Moving beyond Structural Validation to Perception and Intent

Amanul Chowdhury, Vinay Gummadavelli — Mon, 01 Jun 2026 11:00:00 GMT

The AI productivity paradox states that AI scales whatever abstraction it is built on. If that abstraction is structurally brittle, it scales structural brittleness. This article shows that to build a future of reliable, AI-driven test automation, we must stop scaling DOM-centric abstractions and build a new testing paradigm grounded in perception and intent.

By Amanul Chowdhury, Vinay Gummadavelli