ACM Queue

In the wake of the recent Meltdown and Spectre vulnerabilities, it’s worth spending some time looking at root causes. Both of these vulnerabilities involved processors speculatively executing instructions past some kind of access check and allowing the attacker to observe the results via a side channel.

We are redesigning the Queue website. Take a look and let us know what you think. August 24, 2026 Volume 24, issue 4 PDF What happens inside an LLM when it tries to calculate with nothing but matrices How does a large language model do arithmetic when all it has are matrices—no fingers, no scratch paper, no columns of digits?

We are redesigning the Queue website. Take a look and let us know what you think. August 17, 2026 Volume 24, issue 4 PDF DevEx Metrics Compass: making sense of developer experience measurement As AI-augmented development becomes standard practice, engineering leaders face mounting pressure to demonstrate its impact. Yet most organizations are measuring AI adoption and output while the effect on developer experience (DevEx) remains largely unknown.

We are redesigning the Queue website. Take a look and let us know what you think. August 13, 2026 Volume 24, issue 4 PDF  Distributed systems lessons from serving inference The mechanisms that make production inference affordable are the same ones that dissolve the isolation and recovery guarantees built over two decades. This is a property of the workload, not a failure of the people running it.

We are redesigning the Queue website. Take a look and let us know what you think. August 10, 2026 Volume 24, issue 4 PDF Is ignoring it unethical? You can ignore it, tie it to unrelated company initiatives, or feign ignorance and simply not offer solutions that add to it. Or… you can adopt more above-board techniques such as Crawl/Walk/Run and the Reverse Farmer’s Rule, which reframe projects so that confronting tech debt is an upfront part of the plan.

We are redesigning the Queue website. Take a look and let us know what you think. August 5, 2026 Volume 24, issue 4 PDF  Which decisions should not be handed over to LLMs? In the teams that have leaned hardest into AI, models already write most, and sometimes all, of the code. Increasingly, no human reads that code before it ships. I argue that this inevitable automation is only replacing the visible artifact of software engineering, not the actual job.

We are redesigning the Queue website. Take a look and let us know what you think. August 2, 2026 Volume 24, issue 3 PDF The Coding Philosopher Language, truth, and LLMs How can LLMs appear to know facts about the world when they are trained only on patterns in language rather than direct experience of reality? Hallucinations shouldn’t surprise us. The real mystery is how these systems get anything right at all. Plato’s Cave. Jan Pieterszoon Saenredam.

We are redesigning the Queue website. Take a look and let us know what you think. July 27, 2026 Volume 24, issue 4 PDF AI can compress, but not replace AI-assisted development is now the default expectation for new software engineers, but the productivity it delivers depends on professional judgment, and AI is taking over exactly the work that used to develop that judgment.

We are redesigning the Queue website. Take a look and let us know what you think. July 22, 2026 Volume 24, issue 3 PDF The ghost in the machine While training LLMs, OpenAI observed what it termed the compute-efficient frontier (CEF), which characterizes a lower bound on token-prediction error or test loss. This limit has raised concerns that it might constitute a universal constraint on the scalability of GenAI systems.

We are redesigning the Queue website. Take a look and let us know what you think. July 20, 2026 Volume 24, issue 3 PDF The rise of autonomous AI agents and the accelerating velocity of corporate data access are stretching the application-centric model of zero trust security to its breaking point. This article introduces Beyond Zero, a new security paradigm designed for the AI era. The Beyond Zero architecture performs per-resource access decisions for humans and agents at machine speed.