Programmer Weekly (Issue 268 September 11 2025)

Author

Rahul Chaudhary
September 11, 2025

Welcome to issue 268 of Programmer Weekly. Let's get straight to the links this week.

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Quote of the Week

"You want it in one line? Does it have to fit in 80 columns?" — Larry Wall


Reading List

Take a tour through hundreds of performance improvements in .NET 10.

On macOS, disabling XProtect for Terminal dramatically speeds up Rust build and test scripts by skipping per-executable malware scans. This optimization can reduce build times for Rust and other compiled languages, but involves trading off some OS security for development performance.

An engineer used Anthropic's Claude Code AI to modernize a 25-year-old Linux kernel driver for legacy QIC-80 tape drives, updating deprecated APIs and enabling it to compile and run on modern Linux kernels. The process, involving iterative feedback and some manual fixes, transformed this obsolete driver into a working standalone loadable module compatible with current hardware and OS environments within just a few days.

Hilbert spaces let us apply the tools of linear algebra to functions by viewing them as vectors in infinite-dimensional spaces. Square integrable functions form a complete inner product space, enabling concepts like orthogonality and basis expansion, which underpin applications such as Fourier series and quantum mechanics.

OCaml has steadily evolved for nearly three decades, combining simplicity and stability with innovations like multicore parallelism and effect handlers. Its open, user-driven governance and adoption in industry (Jane Street, Meta, Docker, etc.) highlight how thoughtful stewardship sustains a programming language’s relevance over time.

The article demonstrates how to build a full-text search engine in about 150 lines of Haskell, showing that Haskell can be practical and efficient for real-world tasks like indexing and searching large document collections. It uses composable data structures (like Semigroup and Monoid) to elegantly aggregate and query term-document mappings, achieving highly efficient search performance compared to a similar Python implementation.

The article provides a detailed walkthrough of using Hound, an AI-powered code auditing tool that builds adaptive knowledge graphs to model and analyze software systems, enabling detection of security bugs with reasoning across multiple code layers and ongoing refinement of findings. It demonstrates how Hound automates security audits from graph building to hypothesis generation, verification, and report generation, accelerating vulnerability discovery in complex projects like the Rustic Rust server.

How developers are experimenting with structure, orchestration, and standards to get more out of AI coding.

Uber’s HiveSync service provides bi-directional, event-driven replication that keeps Uber’s massive dual-region data lake consistent, resilient, and highly available for analytics and disaster recovery. By orchestrating real-time metadata change detection and fast incremental copying across regions, HiveSync enables Uber to scale its batch data platform efficiently while maintaining strict replication SLAs and reliability.

The post explains how to run local large language models (LLMs) on macOS for privacy, experimentation, and independence from cloud AI providers, recommending tools like llama.cpp and LM Studio for ease of use and configuration. It offers practical advice on choosing model size, runtime, quantization, and security, highlighting that local LLMs enable control over sensitive data and hands-on learning.


Watch, Listen

Meta developed directory branching for its monorepo, enabling teams to branch, cherry-pick, and merge at the directory level rather than for the entire codebase, preserving both monorepo and branching benefits. This approach, supported by custom tooling and metadata, helps teams manage parallel dev and stable branches, streamline CI, and integrate external repositories without disrupting the linear history of the main repo.

Will Wilson of Antithesis describes using a deterministic hypervisor to simulate and test entire distributed systems, going beyond traditional unit and integration testing to autonomously explore millions of execution paths and uncover unexpected bugs before production. By enabling reproducible, large-scale property-based testing—even emulating complete infrastructures like AWS and running Nintendo games—the approach helps teams proactively catch rare and complex system failures that conventional tests miss.

The video explains how code controls hardware using the concept of memory mapped I/O, showing that writing to special memory addresses directly affects devices ranging from LEDs to printers and even laptop screens. It demonstrates that beneath all abstractions, embedded systems universally interact with hardware by flipping bits in memory, making software-hardware control fundamentally seamless.


Book

This comprehensive three-book series takes you from fundamental concepts to implementing enterprise-ready collaborative systems.


Interesting Projects, Tools and Libraries

Semantic grep tool for use by AI and humans!

Toolkit to help you get started with Spec-Driven Development.

A simple blog where you can read all the horror stories of serverless.

Lightweight tool for managing linux virtual machines.

Self-hosted GitHub Actions runners made simple. For AWS. 10x cheaper, 30% faster, and unlimited caching.

The Go based TUI for log analysis.


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