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How software gets built: developer tools, engineering practice, platforms and the open-source economy, from The Silicon Ledger.
AI code generators ship fast, but they can silently violate architectural boundaries. Executable Architecture tools like pytest-archon catch these violations in CI/CD before they merge.
Security teams face an overwhelming flood of vulnerability alerts that scanners cannot properly contextualize. Experts argue that understanding business impact—not just technical severity—is essential to deciding what to fix first.
ReProgman, a newly released nostalgia project, recreates the classic Windows 3.1 Program Manager interface and runs on contemporary Windows 11 and macOS systems with minimal overhead.
Sierra's new Hyper-τ-bench benchmark measures how well AI systems can autonomously construct other AI agents. The results reveal significant gaps in information gathering and design exploration.
OpenAI has given artificial intelligence models the authority to reject code submissions when they detect security vulnerabilities, a shift that engineers say is transforming how the company handles reviews, maintenance, and refactoring.
As AI agents begin handling security alert investigations, technology leaders face a critical question: how much decision-making authority should machines have in security operations centers?
The Institute of Foundation Models released six open-source AI models with training code and data, claiming unprecedented openness—yet some components remain incomplete, and critics question whether the transparency goes far enough.
Martin Reynolds, field CTO at Harness, discusses how AI coding agents are overwhelming engineering teams with pull requests and why the company rebuilt its repository infrastructure to manage the deluge.
