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Perplexity's WANDR is an open benchmark and evaluation harness with 500 evidence-heavy tasks. It tests whether research agents can discover many qualifying entities and back each one with cited, re-verifiable evidence. Perplexity Search as Code leads at 0.363 soft F1 and 0.133 hard F1. The post Perplexity AI Releases WANDR: An Open Benchmark Evaluating Research Agents That Must Search Wide And Deep appeared first on MarkTechPost .

Article URL: https://www.pilotcite.com Comments URL: https://news.ycombinator.com/item?id=48965687 Points: 1 # Comments: 0

Article URL: https://chaoxu.prof/posts/2026-07-18-ai-agents-for-the-working-mathematician.html Comments URL: https://news.ycombinator.com/item?id=48965610 Points: 3 # Comments: 0

<p> Company brain for AI Agents </p> <p> <a href="https://www.producthunt.com/products/flowtask?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/1200340?app_id=339">Link</a> </p>

<p> A terminal, a real browser, and Claude Code under one roof </p> <p> <a href="https://www.producthunt.com/products/tterm?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/1200336?app_id=339">Link</a> </p>

So am looking for more normal people, experienced people using AI, but I feel like whenever I hit youtube or other platforms the AI culture is way deep in the trenches and don't feel like this is how the majority of people tackle work, especially at their jobs. What I see is mostly solo-devs going full battlestar gallactica on things. And I just want to see other people, normal people talk about and show how they use these new tools. I'm also more interested in the first principles of things and

<pre style='white-space:pre-wrap;width:81ex'>fix(agents): preserve ANSI sanitizer state across bash chunks (#103706) * fix(agents): preserve ANSI sanitizer state across bash chunks * fix(agents): harden streaming ANSI sanitization Keep incremental parser state in the canonical terminal owner, avoid a second sanitizer pass, and leave OutputAccumulator and public terminal APIs unchanged.\n\nCo-authored-by: Jicheng Xu <xu.jincheng@xydigit.com> --------- Co-authored-by: Peter Steinberger <steipete@g

<pre style='white-space:pre-wrap;width:81ex'>feat(agents): Swarm core — collector spawn, agents_wait, structured output, caps (gated) (#110932) * docs: add Swarm implementation spec * feat(agents): Swarm core — collector spawn, agents_wait, structured output, fastMode, caps Implements docs/plan/swarms.md §4-6: tools.swarm config gate (default off), collector-mode sessions_spawn (collect/outputSchema/fastMode/groupId), fail-closed child approvals, agents_wait race-semantics tool, per-group FIFO s

<p>By the end of this article, you'll know:</p> <ul> <li>what Kimi K3 actually is, the architecture, the scale, and what changed from the K2 family</li> <li>how to run it today, free in the browser, through the API, or wired into Claude Code, Cursor, Cline, and RooCode</li> <li>which exact model ID and settings unlock the full 1 million token context</li> <li>how K3 stacks up on price and benchmarks against DeepSeek V4, Qwen3.7 Max, GLM-5.2, and its own sibling K2.7 Code</li> <li>whether switchi

<p>AI coding agents have dramatically shortened the distance between an idea and working software. They can inspect a project, create files, run commands, write tests, and help diagnose failures.</p> <p>What they have not eliminated is judgment.</p> <p>A polished screen is not proof that data survives a reload. A passing unit test is not proof that keyboard users can complete the core task. A successful deployment is not proof that the intended commit reached production.</p> <p>This is why I use

<pre style='white-space:pre-wrap;width:81ex'>fix(plugins): report newer registry releases for exact-pinned npm installs (#111169) Co-authored-by: Claude Fable 5 <noreply@anthropic.com></pre>

<pre style='white-space:pre-wrap;width:81ex'>fix(doctor): treat invalid legacy session stubs as warnings during session SQLite import (#111168) Co-authored-by: Claude Fable 5 <noreply@anthropic.com></pre>

<p>A video-to-prompt tool looks simple from the outside: upload a clip, wait a moment, and copy the result. The hard part is not generating text. It is preserving enough of the source video's structure that the prompt remains useful when another model interprets it.</p> <p>I learned this while working on a small video analysis workflow. Early versions produced fluent paragraphs, but they often dropped a camera move, merged two events, or placed dialogue in the wrong shot. The output sounded good

<p>I set out to deploy a fine-tuned LLM fully offline, on a mid-range Android phone, answering medical questions in Yoruba, Hausa, Igbo, and Nigerian Pidgin. No internet connection required, because that's the reality for a lot of the people this was meant to help.</p> <p>The model worked. Getting there broke three times, in three completely different ways, and left me with one problem I still haven't solved.</p> <h2> The setup </h2> <p>I fine-tuned <code>unsloth/Llama-3.2-3B-Instruct</code>, Un

<p>New laws would give Vcat power to force social and AI platforms to identify anonymous users in move premier says will protect children</p><ul><li><p>Get our <a href="https://www.theguardian.com/email-newsletters?CMP=cvau_sfl">breaking news email</a>, <a href="https://app.adjust.com/w4u7jx3">free app</a> or <a href="https://www.theguardian.com/australia-news/series/full-story?CMP=cvau_sfl">daily news podcast</a></p></li></ul><p>Social media companies could be forced to identify anonymous accou

<pre style='white-space:pre-wrap;width:81ex'>fix(state): make managed-image additive migration portable across SQLite versions (#111167) Co-authored-by: Claude Fable 5 <noreply@anthropic.com></pre>

Retrieval, agents, and workflows now ship as visual and plain-English tools. This roundup covers 10 open-source no-code and low-code platforms for building LLM apps, RAG systems, and AI agents, each with its verified license, repository, and best-fit use case. The post 10 Open-Source No-Code AI Platforms for Building LLM Apps, RAG Systems, and AI Agents appeared first on MarkTechPost .

<pre style='white-space:pre-wrap;width:81ex'>feat(agents): canonical agent creation with Custodian hatch flow (#111052) * refactor(agents): centralize agent creation * feat(ui): add new agent hatch flow * refactor(agents): keep creation paths lean * fix(agents): hide internal creation types</pre>

Article URL: https://norwegianscitechnews.com/2026/07/ai-is-not-displacing-young-job-seekers-yet/ Comments URL: https://news.ycombinator.com/item?id=48965293 Points: 1 # Comments: 0

Article URL: https://dl.acm.org/doi/10.1145/3830422.3830425 Comments URL: https://news.ycombinator.com/item?id=48965245 Points: 2 # Comments: 0

<p><strong><a href="https://ludic.mataroa.blog/blog/ai-mania-is-eviscerating-global-decision-making/">AI Mania Is Eviscerating Global Decision-Making</a></strong></p> Here's an entertaining perspective from Nik Suresh on the AI mania that is overwhelming the large companies that he consults with. It's crammed with spicy anecdotes from anonymous sources.</p> <blockquote> <p>In one extreme case, I have seen an executive confess that they had never even used ChatGPT or any AI tool in their life, im

Article URL: https://zlvox.com/ Comments URL: https://news.ycombinator.com/item?id=48965137 Points: 3 # Comments: 1

Article URL: https://variety.com/2026/film/news/netflix-paid-587-million-ben-affleck-ai-interpositive-1236815111/ Comments URL: https://news.ycombinator.com/item?id=48964935 Points: 3 # Comments: 1

Article URL: https://engineerprofiles.com Comments URL: https://news.ycombinator.com/item?id=48964896 Points: 1 # Comments: 0

Article URL: https://www.getonwave.com/ Comments URL: https://news.ycombinator.com/item?id=48964876 Points: 1 # Comments: 0

The enterprise technology ecosystem is caught in a costly cycle. Over the past two years, millions of dollars have been funneled into generative AI pilots, yet many of these initiatives stall out before ever reaching a live production environment. When a project fails, the immediate instinct of technical leadership is often to blame the model: The context window was too restrictive, the latency was too high, or the reasoning capabilities simply were not there. But as data engineers building the

<p>In <a href="https://bun.com/blog/bun-in-rust">Rewriting Bun in Rust</a> Jarred Sumner made the following claim:</p> <blockquote> <p>Claude Code v2.1.181 (released June 17th) and later use the Rust port of Bun. Startup got 10% faster on Linux but otherwise, barely anyone noticed. Boring is good.</p> </blockquote> <p>I decided to have a poke at my own Claude Code installation to see if I could find evidence that it was using Bun written in Rust.</p> <p>I found these two commands convincing:</p>

Article URL: https://github.com/nrkoka786/synapse Comments URL: https://news.ycombinator.com/item?id=48964755 Points: 1 # Comments: 0

Article URL: https://kotaku.com/disney-has-started-feeding-your-kids-ai-slop-2000717222 Comments URL: https://news.ycombinator.com/item?id=48964602 Points: 7 # Comments: 0

Article URL: https://www.legalcheek.com/2026/07/lawyers-risk-being-sued-for-failing-to-use-ai/ Comments URL: https://news.ycombinator.com/item?id=48964599 Points: 6 # Comments: 0

Article URL: https://calculus.academa.ai/ Comments URL: https://news.ycombinator.com/item?id=48964585 Points: 15 # Comments: 7

Article URL: https://www.abc.net.au/news/2026-07-19/china-cracks-down-on-artificial-intelligence-companions/106925352 Comments URL: https://news.ycombinator.com/item?id=48964310 Points: 2 # Comments: 1

<pre style='white-space:pre-wrap;width:81ex'>fix(browser): make copilot runtime bundle deterministic (#111109)</pre>

<blockquote> <p><em>Capture the ringleader first. The rest will scatter on their own.</em><br> — The 36 Stratagems, <a href="https://en.wikipedia.org/wiki/Thirty-Six_Stratagems#Defeat_the_enemy_by_capturing_their_chief_(%E6%93%92%E8%B3%8A%E6%93%92%E7%8E%8B,_Q%C3%ADn_z%C3%A9i_q%C3%ADn_w%C3%A1ng)" rel="noopener noreferrer">Capture the Ringleader</a></p> </blockquote> <p><strong>Previously on this series:</strong></p> <p><a href="https://dev.to/xulingfeng/stratagems-5-leo-walked-into-a-burning-hous

<pre style='white-space:pre-wrap;width:81ex'>fix(anthropic): guard invalid timestamps in history imports (#110536) * fix(anthropic): guard invalid timestamps in history imports * fix(anthropic): reject pre-epoch history timestamps * fix(anthropic): preserve valid transcript dates --------- Co-authored-by: Peter Steinberger <steipete@gmail.com></pre>

I cannot be the only person who feels this way. Claude is antogonistic and frankly an absolute nightmare to use. SLOW is an understatement... I get faster output from a 16GB mac mini using deepseek 8B model....and not much worse output... I ask Gemini something. I get a response in 10 seconds and its long and well detailed. I ask claude, it wastes my tokens talking to itself, makes insulting stupid and frankly rude shortcuts that have no basis in reason except for Anthropics profits... Its unuse

Comments

<p>Over the past few days, I came across a project that made me stop everything to understand how it worked. It wasn't just another framework for running language models, nor another GPU-based optimization. It was something different.</p> <p>The project is called <strong>Colibri</strong>.</p> <p>At first glance, it almost seems impossible. The idea is simple, yet remarkably bold: run a massive Mixture of Experts (MoE) model on an ordinary computer using nothing more than a CPU and an SSD, loadin

<pre style='white-space:pre-wrap;width:81ex'>refactor(agents): unify Responses tool-call id resolver (#111103)</pre>

Article URL: https://knightcolumbia.org/content/ai-as-normal-technology Comments URL: https://news.ycombinator.com/item?id=48964162 Points: 2 # Comments: 0