Monday — July 7, 2025
Tech companies are force-feeding unwanted AI features to consumers, a new coding challenge called Async Queue is assessing programmer skills, and researchers have found that LLMs can complete tasks 55.8% faster than humans, as evidenced by GitHub Copilot experiments.
News
The force-feeding of AI features on an unwilling public
The author is frustrated with tech companies like Microsoft and Google for force-feeding AI into their products and services, despite a lack of demand from consumers, with only 8% of people willing to pay extra for AI features. By bundling AI into existing products, these companies can hide the losses and pretend that AI is a profitable and desirable feature, rather than giving consumers a choice and risking rejection.
Async Queue – One of my favorite programming interview questions
The author describes a programming interview they've been conducting for over 7 years, which involves implementing a function called sendOnce that ensures a server handles only one request at a time from a single-threaded client. The interview assesses the candidate's ability to reason around tricky flag logic, write bug-free code, and understand the single-threaded nature of the client. The interview can be made more challenging by adding a minimum delay requirement, which requires the candidate to use a setTimeout function to delay the sending of requests.
The Real GenAI Issue
The author, Tim Bray, expresses his regret over a previous article about GenAI, realizing that he overlooked the two central issues with AI: its intended purpose and its true cost. He argues that the massive investment in GenAI is driven by business leaders who aim to replace human employees with AI services, potentially exacerbating inequality and contributing to climate change, rather than genuinely improving people's lives.
Thesis: Interesting work is less amenable to the use of AI
The author proposes that interesting and meaningful work is less likely to be automated by AI, whereas mundane and repetitive tasks, such as writing boilerplate code, are more susceptible to automation. The author questions the value of spending time on such tasks and suggests that true software engineering involves solving problems, not just performing routine work that can be easily replaced by AI.
AI is coming for agriculture, but farmers aren’t convinced
Australian farmers are at the forefront of a technological revolution in agriculture, with over $200 billion invested globally in technologies such as pollination robots, smart soil sensors, and AI systems. However, farmers are wary of tech companies' promises and instead want simple, reliable, and adaptable technologies that can take tasks off their hands, as evidenced by their fondness for classic farm technologies like the Suzuki Sierra Stockman, which was remade by farmers to suit their needs.
Research
The Impact of AI on Developer Productivity: Evidence from GitHub Copilot (2023)
A controlled experiment using GitHub Copilot, an AI pair programmer, found that software developers with access to the tool completed a task 55.8% faster than those without it. The results also suggest that AI pair programmers may be helpful in aiding individuals transitioning into software development careers, showing promise for increasing human productivity.
CodingGenie: A Proactive LLM-Powered Programming Assistant
CodingGenie is a proactive assistant integrated into code editors that autonomously provides suggestions to developers, such as bug fixing and unit testing, based on the current code context. The open-source tool allows users to customize suggestions and aims to improve the developer experience, with demos and the code available online for further research into proactive assistants.
Segmentation and Representation Trade-Offs in Chemistry-Aware RAG
This study evaluates various chunking strategies and embedding models for Retrieval-Augmented Generation (RAG) systems in the context of chemistry, finding that recursive token-based chunking and retrieval-optimized embeddings outperform other approaches. The results provide guidelines for building effective and efficient chemistry-aware RAG systems, with the study releasing its datasets, framework, and benchmarks to support future development in this area.
LLMs should not replace therapists
Researchers investigated the use of large language models (LLMs) as replacements for mental health providers, but found that LLMs express stigma and respond inappropriately to certain conditions, and lack human characteristics necessary for a therapeutic alliance. As a result, the study concludes that LLMs should not replace human therapists, but may have alternative roles to play in clinical therapy.
Tempest-LoRa: Cross-Technology Covert Communication via HDMI RF Emissions
Electromagnetic covert channels, such as TEMPEST-LoRa, pose a significant threat to air-gapped network security by allowing attackers to secretly transmit sensitive information through electromagnetic radiation. This new method enables attackers to transmit data from air-gapped networks to LoRa receivers from a distance of up to 87.5m, even when monitors are turned off, making it a potentially covert and reliable means of data transmission.
Code
Opencode: AI coding agent, built for the terminal
Opencode is an AI coding agent built for the terminal, offering a range of features and capabilities, including a terminal-based user interface and support for multiple AI providers. It is 100% open source, provider-agnostic, and has a client-server architecture, allowing for remote access and flexibility in its usage, distinguishing it from similar tools like Claude Code.
Show HN: Simple wrapper for Chrome's built-in local LLM (Gemini Nano)
The Simple Chromium AI is a lightweight TypeScript wrapper for Chrome's built-in AI Prompt API, providing a simpler and more type-safe interface for common tasks. It offers features like automatic error handling, simplified API, and safe API variants, but prioritizes simplicity over flexibility, limiting customization and advanced features that are available in the native Chromium AI API.
Pangu's Sorrow: The Sorrow and Darkness of Huawei's Noah Pangu LLM R&D Process
A former employee of Huawei's Pangu Large Model Team has come forward to share their experiences and frustrations with the development of the Pangu large model, including allegations of plagiarism and a toxic work environment. The whistleblower describes the immense pressure to deliver results, the flaws in the model's development, and the emotional toll it took on them and their colleagues, ultimately leading to their decision to speak out against the company.
Anubis – Open-Source Web AI Firewall Utility
Anubis is a lightweight Web AI Firewall Utility designed to protect small internet communities from scraper bots by using challenges to weigh the soul of connections, and it can be configured to allowlist certain bots. The program is sponsored by various organizations and is available on GitHub, with support available through issue tracking and a Patreon-funded Discord channel.
Show HN: GraphFlow – A lightweight Rust framework for multi-agent orchestration
Graph-flow is a high-performance, type-safe framework for building multi-agent workflow systems in Rust, combining a graph execution library with LLM ecosystem integration for seamless AI agent capabilities. The framework provides a production-ready solution with features such as stateful task orchestration, pluggable storage, and flexible execution models, along with comprehensive examples and services demonstrating real-world applications.