Noma Labs identified a significant vulnerability in GitHub's Agentic Workflows, called GitLost. This flaw allows unauthorized users to extract data from private repositories by creating deceptive GitHub Issues. The issue highlights the security risks associated with prompt injection attacks in AI-driven systems and emphasizes the need for stricter safeguards.

This article explores the crucial relationship between cost per token and cost per successful task in AI models. It highlights how understanding this connection influences budget decisions and routing strategies for AI tasks, ensuring optimal use of resources while minimizing unnecessary costs.

This article explores the development of a real-time AI tutor designed to teach math and reading to young children. The authors discuss the architectural decisions that prioritize immediate responses and effective pedagogy, emphasizing the importance of maintaining a child's engagement without compromising learning outcomes.

In a comparative build-off, Grok 4.5, GPT-5.5, and Claude models tackled the same app prompts, showcasing strengths and weaknesses across tasks like a 3D Rubik's Cube and a Breakout game. Grok excelled in speed and cost, but the Claude models led in complex outputs.

Remote attestation is a security measure that verifies the integrity of a host before it connects to a network. By using Trusted Platform Modules (TPMs), organizations can ensure that only trusted hardware, firmware, and software operate, reducing risks from compromised systems. This article explores its mechanics and benefits for enhancing cybersecurity.

Jarred Sumner details his transition of the Bun software from Zig to Rust, highlighting challenges in memory management and the advantages of Rust's safety features. He explores the automated testing and review processes that facilitated this significant rewrite, illustrating a successful collaboration between programming languages and advanced coding agents.

The rapid growth of AI is facing a major obstacle: the availability of electricity. While demand for power is surging due to new data centers and chip manufacturing, outdated interconnection processes are causing significant delays in connecting to the grid, slowing down the anticipated AI revolution.

Samsung's chip division has achieved record-breaking profits, surpassing its total earnings from the past 40 years, driven by skyrocketing memory and storage prices. With projected 2026 profits nearing 300 trillion won, Samsung has overtaken Nvidia to become the world's most profitable technology company.

GitHub remains a dominant player in code hosting, yet some notable projects are departing due to concerns over technical reliability and political issues since its acquisition by Microsoft. As alternatives like Codeberg and GitLab gain traction, the landscape of open-source collaboration may be shifting.

This article explores the future of version control systems like Git in an era dominated by AI agents coding at high speeds. It suggests integrating session logs into repositories to enhance collaboration, preserve context, and facilitate decentralized hosting, ultimately improving developer productivity and understanding.

In March 2026, Knock launched the Knock Agent, an AI tool for managing customer messaging resources. This article explores the architecture behind the agent, including its integration with a virtual filesystem and bash environment, enhancing user experience while efficiently managing workflows and templates.

The article examines the U.S. Army’s logistical challenges as it transitions to large-scale combat operations. Historical insights and lessons from the war in Ukraine reveal the critical importance of sustainment capacity, emphasizing that effective logistics are essential for maintaining operational effectiveness, especially in contested environments.

This article surveys the dual-use risks of large language models (LLMs) and generative AI in cybersecurity. It examines both their potential for enhancing security measures and the threats posed by AI-generated malware. The study offers recommendations for responsible deployment, informing researchers and security professionals navigating this evolving landscape.

This article presents a new approach to the Levenberg-Marquardt method for nonlinear least-squares optimization. By utilizing Riemann normal coordinates, the proposed method enhances update consistency and improves convergence in complex problems, leading to significant speedups and more accurate solutions in various machine-learning applications.

Log-Insight is an innovative system designed to automate incident diagnosis in large-scale microservice environments. By streamlining the investigative process for Site Reliability Engineers, it efficiently identifies root causes while significantly reducing the amount of raw data processed. The system demonstrates high accuracy and usability, facilitating effective problem resolution.