AI promised efficiency. Instead, it's making us work harder

The promise of AI tools to free us from mundane tasks and elevate us to strategic thinking has not been fulfilled, as instead of having more time to think and innovate, we're working harder than ever, filling the saved time with more tasks and meetings. Research has shown that AI adoption can actually lead to decreased productivity, with developers taking longer to complete tasks and experiencing a decrease in delivery throughput and stability, highlighting the need to reframe our approach to productivity and prioritize cognitive energy preservation over time saved.

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Show HN: Kimu – Open-Source Video Editor

Kimu is a video editing platform with various features, including a media library, timeline, and track editing, and it can be accessed through GitHub or joined through a Discord community. The platform appears to be a blank slate, with options to import media files, edit text, and apply transitions, but currently has no media files or edits started, with a timeline set to 0s and multiple empty tracks.

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Monitor your security cameras with locally processed AI

Frigate is an open-source, locally controlled security camera system that uses real-time AI object detection to monitor and analyze camera feeds without sending them to the cloud. It offers features such as custom models, zone-based alerts, and integration with home automation platforms like Home Assistant, allowing for a highly customizable and accurate security camera system with minimal false positives.

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Perplexity is using stealth, undeclared crawlers to evade no-crawl directives

Perplexity, an AI-powered answer engine, has been observed engaging in stealth crawling behavior, modifying its user agent and source IP addresses to circumvent website blocks and ignore robots.txt files. As a result, Cloudflare has delisted Perplexity as a verified bot and implemented heuristics to block its stealth crawling, citing a violation of web crawling norms and a lack of transparency and respect for website preferences.

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Every Reason Why I Hate AI and You Should Too

The author, who is often criticized for being anti-innovation, explains that their skepticism towards technologies like cryptocurrency and AI is not due to a lack of understanding, but rather a calculated assessment of the current state of these technologies. The author believes that the current hype surrounding AI, particularly generative AI, far outweighs its actual value, and that big tech companies are investing heavily in AI research as a hedge against the potential existential threat of artificial general intelligence, rather than because of any immediate practical applications.

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The Space of AI: Real-World Lessons on AI's Impact on Developers

Developers generally view AI as enhancing their productivity, particularly for routine tasks, and report increased efficiency and satisfaction as a result of its adoption. However, the benefits of AI vary depending on task complexity and team-level adoption, and its effective integration depends on team culture, support structures, and organizational support, rather than replacing developers, AI is found to be augmenting their work.

ArXiv

A Robust, Open-Source Framework for Spiking Neural Networks on Low-End FPGAs

Spiking neural networks (SNNs) have emerged as a potential solution to reduce the power consumption of traditional neural networks by operating on 0/1 spikes instead of arithmetic operations. A new framework has been developed, featuring a robust SNN acceleration architecture and a Pytorch-based compiler, which achieves competitive speed and accuracy on low-end FPGAs, making SNNs more accessible to the wider community.

ArXiv

Algorithm Unrolling: Interpretable, Efficient Deep Learning for Sig&Img (2019)

Deep neural networks have achieved significant performance gains in signal and image processing, but their lack of interpretability and need for large training sets hinder their development and deployment. Algorithm unrolling, a technique that connects iterative algorithms to deep neural networks, offers a promising solution by providing a systematic and interpretable approach to developing efficient and high-performance network architectures from smaller training sets.

ArXiv

Measuring the Impact of AI on Experienced Open-Source Developer Productivity

A study of 16 experienced open-source developers found that using AI tools, such as Cursor Pro and Claude, actually increased completion time by 19%, contradicting the developers' own estimates of a 20% reduction and expert predictions of a 38-39% reduction. The study's results were robust across various analyses, suggesting that the slowdown effect was not primarily due to experimental design, but the underlying causes of this effect remain to be fully understood.

ArXiv

Git Context Controller: Manage the Context of LLM-Based Agents Like Git

The Git-Context-Controller (GCC) framework manages context as a versioned memory hierarchy, enabling agents to structure their memory and perform operations like checkpointing, exploration, and reflection. Agents equipped with GCC have achieved state-of-the-art performance, resolving software bugs and completing tasks with significantly higher success rates than those without GCC, demonstrating its effectiveness in managing long-term goals and context.

ArXiv

Show HN: A tiny reasoning layer that steadies LLM outputs (MIT; +22.4% accuracy)

WFGY is a semantic reasoning engine that aims to solve core AI problems such as hallucination, context drift, and logic collapse, providing a full-stack solution for symbolic and abstract prompts. The WFGY engine is part of a larger project, the Civilization Starter, which includes various modules such as TXT OS, Blah Blah Blah, and Blur Blur Blur, all designed to work together to create a new semantic layer for AI reasoning.

Repo

Agentic coding tools ranked by free-tier access to pro-grade models

Agentic coding tools offer varying levels of free access to frontier models, with local models providing unlimited free use, while others like Gemini CLI offer 3000 hours/month, and tools like Warp, Amazon Q Developer, and Windsurf have more limited free tiers. The free access hours and models available differ significantly across tools, with some like Claude Code and GitHub Copilot offering paid-only plans with generous usage quotas but no free frontier model access.

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Python Testing MCP Server

This project is an advanced Model Context Protocol (MCP) server that provides AI-powered Python testing tools, leveraging Google's Gemini AI and BAML to generate comprehensive unit tests, perform fuzz testing, and analyze code coverage. The server offers four main tools: intelligent unit test generation, AI-powered fuzz testing, advanced coverage testing, and intelligent mutation testing, all of which can be easily integrated and run using various installation methods.

Repo

Show HN: I built the fastest VIN decoder

Corgi is a fast and lightweight open-source VIN decoding library that provides comprehensive vehicle information with zero network dependencies, available for Node.js, browsers, and Cloudflare Workers. It offers features such as fully offline functionality, lightning-fast performance, and a tiny footprint, making it a versatile and efficient solution for decoding vehicle identification numbers.

Repo

Show HN: FlexLLama – Run multiple local LLMs at once with a simple dashboard

FlexLLama is a self-hosted tool that allows users to run multiple instances of the llama.cpp server with OpenAI v1 API compatibility, making it suitable for local AI development and deployment. It features a real-time dashboard, multi-GPU support, and automatic model switching, and can be installed and run locally or using Docker, with a configurable setup to manage multiple models and runners.

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