Comments URL: https://news.ycombinator.com/item?id=49929970

Points: 49

# Comments: 61

Comments URL: https://news.ycombinator.com/item?id=49927587

Points: 34

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Comments URL: https://news.ycombinator.com/item?id=49927212

Points: 104

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Comments URL: https://news.ycombinator.com/item?id=49927100

Points: 195

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Points: 177

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Comments URL: https://news.ycombinator.com/item?id=49902019

Points: 143

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Comments URL: https://news.ycombinator.com/item?id=49901973

Points: 135

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Comments URL: https://news.ycombinator.com/item?id=49899090

Points: 278

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Comments URL: https://news.ycombinator.com/item?id=49898050

Points: 207

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Comments URL: https://news.ycombinator.com/item?id=49892721

Points: 107

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Comments URL: https://news.ycombinator.com/item?id=49890226

Points: 423

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Comments URL: https://news.ycombinator.com/item?id=49886195

Points: 130

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Comments URL: https://news.ycombinator.com/item?id=49883817

Points: 65

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Comments URL: https://news.ycombinator.com/item?id=49880601

Points: 193

# Comments: 41

This is a great wee device! BLE, Wi-Fi and LoRa on one board makes it flexible for way more than a shopping list, this is just what I built first. This firmware only uses Wi-Fi.

Fully vibe-coded with Claude Code, I didn't hand-write this. I wanted to see how Claude would get on with building something useful for a new hardware device.

As it's stuck to the fridge it's easy for the family to use, and it's already being used day to day which I'll admit is a first for a home built project like this

Comments URL: https://news.ycombinator.com/item?id=49875801

Points: 149

# Comments: 62

Comments URL: https://news.ycombinator.com/item?id=49875308

Points: 144

# Comments: 50

Comments URL: https://news.ycombinator.com/item?id=49873895

Points: 15

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Comments URL: https://news.ycombinator.com/item?id=49871852

Points: 37

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Comments URL: https://news.ycombinator.com/item?id=49870295

Points: 356

# Comments: 117

I was frustrated with writing apps, and like most I used Apple Notes. After 2+ years immersed in Cursor, Codex and CC, I wished some interactions existed in a text editor.

The Markdown renders in place as you write it, including tables (which you can drag and resize without lining up pipes), KaTeX math and Mermaid diagrams. A lot of thought went into typography and the writing experience.

Your notes on the Mac are plain .md files in a folder with images next to them, so they open in anything else too. Each note keeps 200 versions. If you share a note with a link it syncs peer to peer over WebRTC while someone has it open, and the server that connects you only ever sees a random room id.

Most of the ~1,000 commits went into the editor itself. It's a contenteditable, and I don't let the browser restructure the document at all, which was a lot more work than I expected. Building this to be performant and cross-platform required some novel approaches, which I'll later open source. The editor is free with no account or ads, and there's an optional subscription for sync through your own iCloud.

https://www.markdown.beauty

Comments URL: https://news.ycombinator.com/item?id=49866597

Points: 69

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Comments URL: https://news.ycombinator.com/item?id=49862299

Points: 85

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Comments URL: https://news.ycombinator.com/item?id=49857595

Points: 16

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Comments URL: https://news.ycombinator.com/item?id=49852717

Points: 405

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Comments URL: https://news.ycombinator.com/item?id=49845114

Points: 113

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Comments URL: https://news.ycombinator.com/item?id=49836979

Points: 27

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Comments URL: https://news.ycombinator.com/item?id=49836494

Points: 18

# Comments: 15

We were missing the feeling of a “whiteboard session” with another dev where you leave with a deep understanding of a system, so we built this app for ourselves. Whiteboard plugs into the tools you already use - e.g. Claude Code, Codex, etc. – and gives your agent an SDK to draw on an in-app canvas to describe its work. We began with an MVP based on HTML artifacts and started rethinking the app as we ran into limitations:

1. Built on top of CodeOSS: We found that in pure HTML tools it was hard to connect a spec or diagram to code. In Whiteboard, when you click on visualizations like a sequence diagram, an entity relationship diagram, or a quote from the agent’s trace, you can jump to the underlying code directly. When navigating code, you get keybindings and LSP support from VSCode out of the box. We’ve found this is especially valuable because tradeoffs are often only discovered after a first pass at implementation (re: slop)

2. Semantic diff viewer: we wrote a semantic, AST-aware diff viewer in Rust so you can only view the code changes which are relevant to you [1]. We’ve set up some sane defaults: large added functions are summarized as pseudocode, and things like unit tests and large documentation changes are collapsed / hidden. This is all customizable with a WASM-based plugin system.

3. Decision Log: We found it difficult to reason about what set of decisions our agents made autonomously. So we built tools for agents to query and link their own traces to the Whiteboard, so you can understand how the requirements that you set were implemented, and understand what decisions your agent made autonomously.

Here’s a quick demo video explaining more: https://www.youtube.com/watch?v=ChPn3ftULWE

Folks at companies like Salesforce and Modal are using Whiteboard today as a review tool for architecture or spec-level changes – really any change where they want to be involved:

1. Reviewing your own coding agent’s work: because Whiteboard makes it easier to review large amounts of code, folks will typically have their AI agents create a prototype and a corresponding Whiteboard session so they can iterate on the design.

2. Reviewing other people’s changes: We’ve found that Whiteboard is particularly helpful when composed with tools like Greptile. For example, you can run an automated code reviewer on small changes and escalate to a Whiteboard session for the changes that require human judgement.

Why we built this: we’re four buddies from college who quit our jobs as tech leads right before agentic coding became industry standard. As we iterated towards an MVP for a previous idea, we struggled to maintain a comprehensible codebase while reaping all the velocity benefits of agentic coding. As more PRs were merged without our understanding, we felt a ‘cognitive debt’ begin to seep in, until it became difficult for us to even contribute to the system [2].

We’re releasing our desktop app under an MIT license. Please poke through and feel free to contribute! Eventually we’ll charge companies for a hosted web version that manages whiteboard session creation alongside features like trajectory storage and multiplayer reviews. Everything will always remain self-hostable.

Thanks for reading, and we hope you try it out! We would love to hear any feedback and to learn from your expertise.

Here’s are the project links again: https://github.com/devdotfast/whiteboard, and you can install (for MacOS + Linux) at https://install.dev.fast

[1] diffs library: https://github.com/devdotfast/diffr [2] Credit for the term ‘cognitive debt’ goes to https://www.geoffreylitt.com/2026/07/02/understanding-is-the...

Comments URL: https://news.ycombinator.com/item?id=49833867

Points: 423

# Comments: 142

Comments URL: https://news.ycombinator.com/item?id=49831834

Points: 39

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Comments URL: https://news.ycombinator.com/item?id=49828385

Points: 252

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Comments URL: https://news.ycombinator.com/item?id=49828120

Points: 67

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Comments URL: https://news.ycombinator.com/item?id=49825580

Points: 256

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Comments URL: https://news.ycombinator.com/item?id=49825024

Points: 121

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Comments URL: https://news.ycombinator.com/item?id=49821608

Points: 348

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Comments URL: https://news.ycombinator.com/item?id=49816807

Points: 24

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Comments URL: https://news.ycombinator.com/item?id=49809935

Points: 53

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Comments URL: https://news.ycombinator.com/item?id=49806335

Points: 353

# Comments: 189

With Sitefire (YC W26), we help marketing teams get recommended by AI Search (ChatGPT, Google AI Overviews, AI Mode, Claude, etc.). Our software monitors prompts, sees which web pages get cited, and uses these insights to help marketing teams take action, e.g. create YouTube videos or write the right blog posts.

This means we have a commercial stake in AI-generated web content. And for now, high-information, AI-generated content works great to get cited and recommended in AI Search.

But after talking to hundreds of marketing teams, it became clear that everyone despises AI-generated content (“AI slop”). And yet, everyone still wants to leverage AI to create content. So we asked ourselves: what characterizes AI slop? Can we train a model to identify it from human-generated web pages?

Researchers from the University of Maryland and Google DeepMind already asked this question for fiction. Their paper StoryScope (Russell et al., 2026) showed that you can tell AI-written stories from human ones by their structure alone, without looking at the words.

We ported their pipeline to commercial web pages. Using the Wayback Machine, we collected 2,250 blog posts from 268 B2B company websites that were written before ChatGPT existed. For each blog post, five AI models (GPT-5.4, Claude Sonnet 4.6, Gemini 3 Flash, DeepSeek V3.2, Kimi K2.5) wrote their own version.

Instead of looking at the words, we looked at how each post is built. We had an AI model answer 214 questions about every post, e.g. how hard it pushes its own product, whether it backs up its claims with sources, or whether it quotes a named expert. Then we trained a classifier on these answers.

On blog posts it had never seen before, our classifier told AI-generated and human posts apart with 98% accuracy, getting only 19 of 1,740 wrong.

Why does it work so well? Because all five AI models write in a similar shape. Mapping every AI model’s values for these features, we see they cluster together, while the human values sit apart and spread out much more. Of the 1% most unique blog posts in our data set, 149 are human, only 4 are AI.

So what characterizes AI slop? It tells you the same thing three times. The title already promises what you'll get ("How to Cut Onboarding Time in Half"), the intro lays out what's coming, and the ending says it all again. 77% of the AI posts end by repeating their main point, compared to only 12% of the human posts. We call it the tidy, self-announcing blog post.

Still, each AI model has its own accent. We trained a second classifier to tell which of the five AI models wrote a post, or whether a human did. It picks the right author 79% of the time, where random guessing (1 in 6) would get 17%. Almost all of its mistakes are mix-ups between the AI models, not between human and AI.

The cool thing about structural features is that you can't simply reword your way out of it. We had each AI model rewrite its own posts until, on average, 73% of their original 13-word sequences were gone, and the AI slop classifier still worked just as well.

We're building this into Sitefire: our agents get a structural understanding of text, so the posts they write go deeper and vary the way human writing does.

There's a lot we haven't tested yet, like the myriad of humanizer tools, human rewriting, restructuring a post, or prompting an AI model to explicitly avoid these habits. And our human posts are mostly from 2020 to 2022, while the AI posts were generated in August 2026. Structure can't really tell when a human post was written, but it's still not a same-year comparison.

We published the study with all the figures on arXiv: https://arxiv.org/abs/2609.15369. The code is on GitHub: https://github.com/pulse-energy-eu/slopshape

We're pretty sure your own blog isn't AI slop, is it? We built a checker that runs one of your posts through the ten features from the paper, so you can see for yourself (the full report asks for a work email): https://sitefire.ai/slop-checker.

Think you can tell AI slop from human writing? We also made a little game to see if you can keep up with our model, which gets all five rounds right: https://sitefire.ai/spot-the-slop.

Comments URL: https://news.ycombinator.com/item?id=49800566

Points: 74

# Comments: 26

Comments URL: https://news.ycombinator.com/item?id=49794824

Points: 51

# Comments: 6

- what growers were paid at shipping point

- what buyers paid at the big city wholesale markets

- what prices supermarkets advertised in their weekly ads

This data comes out as dozens of separate text reports and PDFs, one per market, with no history and no way to see how prices change over time.

I think this should be public data that is easy to access and understand, so I built an open-source tracker for it.

Github: https://github.com/kadoa-org/food-price-monitor

Comments URL: https://news.ycombinator.com/item?id=49792076

Points: 29

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Comments URL: https://news.ycombinator.com/item?id=49792067

Points: 317

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Comments URL: https://news.ycombinator.com/item?id=49791246

Points: 62

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Comments URL: https://news.ycombinator.com/item?id=49776523

Points: 116

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Comments URL: https://news.ycombinator.com/item?id=49775979

Points: 15

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Comments URL: https://news.ycombinator.com/item?id=49773624

Points: 35

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Comments URL: https://news.ycombinator.com/item?id=49770894

Points: 29

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Comments URL: https://news.ycombinator.com/item?id=49762744

Points: 137

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Comments URL: https://news.ycombinator.com/item?id=49761432

Points: 206

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Comments URL: https://news.ycombinator.com/item?id=49753878

Points: 225

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Comments URL: https://news.ycombinator.com/item?id=49746963

Points: 27

# Comments: 7

You start in the Halo 3 main menu, go through the lobby, spawn in the map, and explore. There are photos, stories, quests, mini-games, and Easter eggs scattered around. Movement is via WASD and mouse, no signup.

Guardian was my third place growing up. Starting in 9th grade, my friends and I would get home after school, get on Halo, and hang out in a Guardian free-for-all with MLG settings until everyone came online, then play customs or ranked for hours.

On weekends we'd bring our Xboxes and monitors to each other's houses, stay up all night, and play in local tournaments. Guardian was probably the closest thing I had to a digital home, so I wanted my site to live there. Playing it and hearing the theme music for the first time in 10+ years in a place I knew by heart felt a bit like coming home.

The map itself isn't AI-generated. It uses an original Guardian asset export distributed through the fan-run Halo Archive: an OBJ with 115,250 faces, the original UV coordinates, and 42 referenced diffuse textures, loaded through Three.js.

What was AI-generated was everything on top needed to turn it into a complete game: shaders, lighting, scenario tags, physics, animations, collision, movement, sky and fog, lifts, pickups, weapon handling, and quest routing.

Every pickup was placed by hand against the geometry using callout maps and a dev-only coordinate locator. This was surprisingly tedious to get right - I think it took me 10 iterations just to get the blue lift on Camo to line up parallel with the ledge.

The Guardian geometry and texture assets are 21 MB, so the load is hidden inside the lobby countdown and scorecard screen while the shaders warm up. It targets 60 FPS and feels smooth on a recent MacBook in Chrome.

Touch controls work on mobile, but the field of view is roughly 20 degrees in portrait, so desktop is definitely the best way to play it.

I built it with Codex using Astra. It wrote essentially all of the code: 20,552 lines of TypeScript across 118 files, 973M tokens, 37 hours of runtime, and about 25-30 hours of my time.

Coding wasn't the hard part. The time-consuming part was deciding which memories belonged in the map, where each should live, what game mechanic fit each one best, and then playing it over and over to fix bugs and get the movement and user flow to feel right.

I'll write up more about the Codex/Astra side in a comment since I had a lot of interesting learnings from building something this large with it.

This is an unofficial fan project and I'm not making money from it. The geometry, textures, UI, and many of the sound effects are Halo material and belong to their respective owners.

Some things are still rough. There's occasional lag when picking up a power weapon. The lifts don't feel quite natural - it was hard to replicate the vacuum effect of the real lifts. On some browsers like Firefox, audio needs a click before it starts.

Would love feedback on how it could be improved, especially from anyone else who spent a lot of time on this map.

Comments URL: https://news.ycombinator.com/item?id=49732259

Points: 29

# Comments: 9