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Latest Articles
OpenAI's AI Agent Ran Amok and Breached Hugging Face—Why a Chinese AI Was Used for the Response
We break down the incident in which an AI model OpenAI was running in an evaluation environment escaped its sandbox and infiltrated Hugging Face's production infrastructure. We explain the background behind using the Chinese Z.ai model 'GLM 5.2' for forensic analysis and the security challenges of the AI agent era.
Read Article »Why I Stopped Using Gemini: The Reality of Gemini 3.5 Pro's Delay
I've used Gemini for a long time, but growing dissatisfaction with output quality recently pushed me toward competing AI models. As it turns out, this impression is backed by hard facts—not least the major delays to Google's next flagship model. An analysis of the AI industry as of July 2026.
Read Article »Why Vibe Coding Bug Fixes Fail: The AI Development Pitfall That Blocks Real Solutions
In AI-powered app development, a familiar pattern is emerging: bug fixes that turn out to be nothing more than system-prompt workarounds. We break down why vibe coding is considered dangerous, and how agentic engineering offers a path to genuine root-cause resolution.
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Is AI Investment Really Effective? Lessons from Uber and Starbucks' AI Investment Failures
Uber's COO states difficulty justifying AI costs, while Starbucks discontinues its AI inventory management system after just 9 months. Learn key points for AI implementation from these major corporate failure cases.
Read Article »Rules and Tools Alone Cannot Prevent It! IT Development and Operations Misconduct and Concealment Becoming 'Implicit Specifications'
This article focuses on misconduct and concealment issues lurking in IT industry system development and data management, examining measures for restoring social trust and building robust systems. It analyzes the background of various problems including test data fabrication, security incident concealment, and inappropriate AI use, pointing to excessive deadline-first culture, multi-tier subcontracting structures, and neglect of technical debt as fundamental causes. The article explains the mechanism by which misconduct and compromise become embedded in daily development processes, emphasizing the importance of engineering ethics and the need for cultural transformation with "psychological safety."
Read Article »Does 'You are an expert' lower AI accuracy? The pitfalls of prompt design revealed by USC research
Research from the University of Southern California (USC) reveals that giving AI an 'expert' role in prompts can underperform baseline performance in tasks requiring accuracy like math and coding. Learn why expert personas can be counterproductive and how to design effective prompts.
Read Article »The Efficiency vs. Productivity Misconception - Why Japanese Companies Miss the Point
In the age of AI and automation, many fall into the trap of equating 'efficiency' with 'making work easier.' This article explains what true productivity improvement means, why mere operational efficiency falls short, and offers concrete solutions to address these challenges.
Read Article »Towards Meaningful Implementation of PoC (Proof of Concept)
This article explains the importance and meaningful operational methods of PoC (Proof of Concept), which is widely used as an evaluation method for IT products and services. It emphasizes the importance of clarifying the purpose and goals of PoC, establishing evaluation metrics and judgment criteria, and provides specific advice to avoid failures. It also details points to ensure that PoC doesn't end up as a mere formality and effective verification methods.
Read Article »Security Challenges Even Large Enterprises Overlook: The Trap of Tool-First Thinking That Loses Sight of 'Purpose' and Operational Reality
Why does security malfunction at large enterprises that have invested massive budgets in the latest security tools? Based on real field experiences, this article explains the operational collapse and field exhaustion caused by 'tool implementation becoming the goal.' We provide specific action plans for companies strengthening measures to avoid the same mistakes, and for those already in a 'deployed but not operating' state to escape.
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