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Article URL: https://github.com/caihongfairys/QMP-Dynamic-Anchors Comments URL: https://news.ycombinator.com/item?id=48617894 Points: 2 # Comments: 0

<pre style='white-space:pre-wrap;width:81ex'>fix(qa): reject non-object mock Anthropic JSON</pre>

Article URL: https://www.reuters.com/world/china/china-tightens-indium-export-checks-ai-demand-increases-2026-06-19/ Comments URL: https://news.ycombinator.com/item?id=48617740 Points: 1 # Comments: 0

Article URL: https://www.youtube.com/watch?v=7Wg894k6bqU Comments URL: https://news.ycombinator.com/item?id=48617721 Points: 2 # Comments: 0

<pre style='white-space:pre-wrap;width:81ex'>fix(qa): reject malformed mock OpenAI JSON</pre>

As an indie engineer, I wanted some real feedback on my productivity, like having an actual external boss. I tried using time trackers (even a physical timer), but they weren't good at tracking everything. So I built Didon, an AI time tracker that watches the screen periodically and generates work logs, then summarizes them into your workday report. Comments URL: https://news.ycombinator.com/item?id=48617640 Points: 1 # Comments: 0

<table> <tr><td> <a href="https://www.reddit.com/r/MachineLearning/comments/1ubmybr/i_released_a_softmaxfree_attention_model_at_gpt2/"> <img src="https://external-preview.redd.it/fzbusCnVMF6KiLx-XGEbOtJ2hfOGlk4ouLmg5Wsh_8c.png?width=640&crop=smart&auto=webp&s=fb342a515f360dfb611d261f135a028577e8e501" alt="I released a softmax-free attention model at GPT-2 Medium scale (~354M params, 11.5B tokens): structural sparsity + tile-skipping kernels for long-context VRAM savings. Open weights + custom Tr

Article URL: https://kitaabai.com Comments URL: https://news.ycombinator.com/item?id=48617594 Points: 1 # Comments: 0

Sure, anyone can use OpenAI’s chatbot. But with smart engineering, you can get way more interesting results.

Article URL: https://blog.andymasley.com/p/what-does-it-mean-for-ai-to-be-democratic Comments URL: https://news.ycombinator.com/item?id=48617311 Points: 1 # Comments: 0

Article URL: https://adlrocha.substack.com/p/adlrocha-form-before-data-the-real Comments URL: https://news.ycombinator.com/item?id=48617124 Points: 2 # Comments: 0

At a Stanford talk, Sam Altman defended LLM scaling and hit back at skeptics, saying a whole generation of researchers slowed the field by underestimating what scaling could do. He cited OpenAI's recent disproof of a mathematical conjecture as evidence. The article Sam Altman says a whole generation of researchers held AI back by underestimating what scaling could do appeared first on The Decoder .

Article URL: https://age-of-product.com/ai-definition-of-done/ Comments URL: https://news.ycombinator.com/item?id=48617064 Points: 1 # Comments: 0

Upgrade your PC with Microsoft Windows 11 Pro for just $12.97 and get modern security, productivity tools, gaming upgrades, and AI-powered features.

Article URL: https://fivetakes.news/did-anthropic-talk-its-way-into-an-ai-export-ban Comments URL: https://news.ycombinator.com/item?id=48616892 Points: 2 # Comments: 0

Article URL: https://github.com/bryanyzhu/agentic-ai-system-course Comments URL: https://news.ycombinator.com/item?id=48616863 Points: 1 # Comments: 0

At its summit in New York, AWS unveiled two new services. Continuum automatically detects, prioritizes, and fixes code vulnerabilities. Context builds a knowledge graph from corporate data to give AI agents the business context they need. Both tackle the same problem: agents that write code fast but get things wrong too often. The article AWS says AI agents lack business context and security, launches two services to patch the gaps appeared first on The Decoder .

Article URL: https://faridsaid.com/en/blog/event-loop-starvation-trading.html Comments URL: https://news.ycombinator.com/item?id=48616819 Points: 1 # Comments: 0

Article URL: https://fivetakes.news/using-ai-for-financial-advice-proceed-with-caution Comments URL: https://news.ycombinator.com/item?id=48616810 Points: 1 # Comments: 0

Back to the drawing board? ScienceAlert stories are written, fact-checked, and edited by humans, never generated by AI. Don't miss a story, subscribe here.

Article URL: https://zenodo.org/records/20774491 Comments URL: https://news.ycombinator.com/item?id=48616674 Points: 1 # Comments: 0

Article URL: https://github.com/cursor/agent-trace Comments URL: https://news.ycombinator.com/item?id=48616614 Points: 1 # Comments: 0

Domain: https://hourly.krl.kr Github: https://github.com/3289david/hourly Features: Time based web IDE Unlimited AI for that session A secure terminal with 0.5vcpu and 512MB ram Github integration Code Editor Access your workspace on other devices too! hourly.krl.kr Comments URL: https://news.ycombinator.com/item?id=48616596 Points: 1 # Comments: 1

<p> Evaluate AI agent, pinpoint issues, and fix with one click. </p> <p> <a href="https://www.producthunt.com/products/agentx?utm_campaign=producthunt-atom-posts-feed&utm_medium=rss-feed&utm_source=producthunt-atom-posts-feed">Discussion</a> | <a href="https://www.producthunt.com/r/p/1177141?app_id=339">Link</a> </p>

Article URL: https://github.com/Letterblack0306/LetterBlack-Sentinel Comments URL: https://news.ycombinator.com/item?id=48616412 Points: 2 # Comments: 0

Article URL: https://github.com/calesthio/OpenMontage Comments URL: https://news.ycombinator.com/item?id=48616398 Points: 4 # Comments: 0

Article URL: https://livekit.com/blog/why-webrtc-beats-websockets-for-voice-ai-agents Comments URL: https://news.ycombinator.com/item?id=48616386 Points: 2 # Comments: 0

In this tutorial, we build a complete Crawlee for Python workflow from setup to AI-ready output. We generate a local demo website, then crawl it with BeautifulSoupCrawler, ParselCrawler, and PlaywrightCrawler. We extract titles, metadata, product fields, and JavaScript-rendered cards, and capture full-page screenshots. We then normalize the data, build a link graph, and export JSON, CSV, and RAG-ready JSONL chunks. The post Crawlee for Python: Build a Web Crawling Pipeline with Robots Handling,

<p>Everyone blames hallucination. I've started blaming the design.</p> <p>I work on a fintech banking platform — Java, Spring Boot, microservices. When a payment fails, we don't shrug and say "the network is probabilistic." We trace it. We find the exact hop where something went wrong. We fix it.</p> <p>But when an LLM-powered feature fails, the default reaction is usually: "yeah, AI hallucinates sometimes."</p> <p>And after going through a structured ML cohort over the last few weeks, I think I

<p>When a stronger model ships, there are two questions every skill author should want answered, and evals are the only honest way to answer either:</p> <ol> <li> <strong>Which skills just got absorbed?</strong> A model that now knows how to do X natively does not need a skill telling it to do X. Fewer skills to maintain, leaner context, lower cost.</li> <li> <strong>Which skills still matter?</strong> Behaviour-level guidance (conventions, preferences, project-specific workflows) is not somethi

<h2> You wrote the graph by hand. Then the requirements changed. </h2> <p>Most TypeScript agent frameworks make you draw the graph yourself. You declare the nodes, wire the edges, decide what runs after what, where it branches, where it joins. It works, right up until the goal shifts and you are back in the graph editor re-wiring a pipeline you already built once.</p> <p>There is another way to model this: describe the goal, and let a coordinator build the graph for you.</p> <p>That is what <cod

<p>If you've been exploring AI agents recently, chances are you've come across RAG (Retrieval-Augmented Generation).</p> <p>A typical RAG system looks something like this:<br> </p> <div class="highlight js-code-highlight"> <pre class="highlight plaintext"><code>Documents ↓ Chunking ↓ Embeddings ↓ Vector Database ↓ Similarity Search ↓ LLM </code></pre> </div> <p>This architecture has become the foundation for many AI assistants, chatbots, and knowledge-based agents.</p> <p>And for good reason.</p

Show HN: Pyor - A better alternative to Github for reviewing PRs since the introduction of AI, the bottleneck for shipping code shifted from producing code to reviewing it, and the PR reviewing experience on Github is lackluster, leaving a lot to be desired. my team now ships too much code and it sits in review for too long, review AI code is not easy and we need a better tool to review code, especially on large PRs. So I built Pyor, a website and a performant desktop app to review code at least

Hi HN- This past year I've built and maintained Quikdown, a bidirectional markdown parser and companion editor in pure js, with batteries included fences for rendering rich content. Try it live: https://deftio.github.io/quikdown/pages/edit/ The motivation was working with many different LLM frameworks and wanting to test tool calling and collaborative editing. Often I just wanted a pretty final output with rich support for diagrams, math, or other rendered content but, keep it editable . So a us

Article URL: https://idiallo.com/blog/unsubscribed-from-ai-generated-newsletters Comments URL: https://news.ycombinator.com/item?id=48616227 Points: 5 # Comments: 1

Article URL: https://sant.ajinkya.ai/tukaram Comments URL: https://news.ycombinator.com/item?id=48616224 Points: 3 # Comments: 4

Article URL: https://kage-core.com/ Comments URL: https://news.ycombinator.com/item?id=48616216 Points: 1 # Comments: 0

<pre style='white-space:pre-wrap;width:81ex'>test(scripts): route prompt snapshot helper changes</pre>

<p>Investigation finds AI content that purports to show genuine customers, prompting calls for greater transparency</p><p>Brands promoting their products online are quietly deploying AI-generated influencers on social media, an investigation has found, prompting calls for greater transparency.</p><p>The findings suggest companies are increasingly turning to AI-generated content that purports to show genuine customer experiences while giving no obvious indication that the people featured are not

Feels like every idea now has “AI” stapled onto it. Curious what people would focus on if that wasn’t an option, what problems would actually be worth solving? Comments URL: https://news.ycombinator.com/item?id=48616031 Points: 4 # Comments: 4