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Article URL: https://endler.dev/2024/move-slow-and-fix-things/

Comments URL: https://news.ycombinator.com/item?id=50204754

Points: 13

# Comments: 0

The "product graveyard" of SaaSHub has been tracking the status (and lifespan) of hundreds of thousands of products. It's been hovering around 4y for quite some time. However, there's a sharp decline in 2026 leading to about 1.5y these days. https://www.saashub.com/product-graveyard That's a huge drop. And, it matches my "human" observations. A lot of products are being vibe coded, released, and soon after that abandoned. It's become too cheap to produce software. So, a lot of people have been experimenting for 'free' with their ideas - only to find out that they weren't viable... or that they couldn't bring customers in. Distribution and marketing have become much more important than before - within the context that everyone can build "features" for free.

Anyhow, I expect this trend of shortening product lifespan to continue even further down. Or maybe, at some point people will realised that there are no users for their products as every user can "build" their own and custom product. Leaving us with a dozen huge platforms that host and help you build those apps. Until then - it's a crazy gold rush and a lot of makers are abandoning their empty buckets.

Comments URL: https://news.ycombinator.com/item?id=50204125

Points: 27

# Comments: 10

Article URL: https://www.awakin.org/v2/read/view.php?tid=468

Comments URL: https://news.ycombinator.com/item?id=50203759

Points: 139

# Comments: 62

Article URL: https://www.cs.utexas.edu/~EWD/transcriptions/EWD06xx/EWD667.html

Comments URL: https://news.ycombinator.com/item?id=50203161

Points: 346

# Comments: 232

A recent (unwanted) webOS update that got installed on TV prompted me to start going down the rabbit hole of writing new TV software. After a couple of weekends and massive help from 4 different models, finally managed to get v1 working.

My daughter enjoys navigating TV through speech while I get to browse on the biggest screen at home.

While all of the code was written by ML models, there were decisions I had to help with. In specific: using WebRTC to cut down latency, repurposing vendor logic for buffering voice samples and designing user experience.

It was liberating to finally free the TV of bloatware and make it truly personalized!

Comments URL: https://news.ycombinator.com/item?id=50202865

Points: 69

# Comments: 38

Article URL: https://www.maps.com/star-map-charts-stars-and-constellations-of-northern-hemisphere/

Comments URL: https://news.ycombinator.com/item?id=50202766

Points: 32

# Comments: 10

Article URL: https://jank-lang.org/

Comments URL: https://news.ycombinator.com/item?id=50202762

Points: 155

# Comments: 31

Hey all —

Sharing a thought experiment I put together. The premise: what might declarative programming feel like for the physical world?

We’re already familiar with this paradigm in software land (eg SQL etc where we declare what we want and the execution engine figures out how).

I didn’t have access to an actuator so I mocked up the concept in software. The way it works is you demonstrate the effect and the system figures out how to achieve it. So say you want to ring a bell and you have a crank. The system will find a way to connect the two. If you add obstacles it figures out how to work around them (runs a constraint solver runs behind the scenes).

I think what’s interesting about this is being able to think about the problem at a higher level of abstraction, with the system figuring out a way to achieve the intended effect.

Anyways, curious to read reactions, feedback, and interesting ideas on how to extend this!

Comments URL: https://news.ycombinator.com/item?id=50202746

Points: 43

# Comments: 13

Article URL: https://codeandcake.dev/posts/2026-10-22-docker-is-weird

Comments URL: https://news.ycombinator.com/item?id=50202681

Points: 772

# Comments: 309

Article URL: https://www.economist.com/finance-and-economics/2026/10/22/ai-compute-is-the-new-oil-and-needs-a-new-market

Comments URL: https://news.ycombinator.com/item?id=50202671

Points: 34

# Comments: 26

Article URL: https://www.axelmagn.com/blog/202610-zig-traits/

Comments URL: https://news.ycombinator.com/item?id=50202482

Points: 26

# Comments: 6

Article URL: https://edjefferson.com/localwiki/

Comments URL: https://news.ycombinator.com/item?id=50202285

Points: 1491

# Comments: 240

Article URL: https://www.anthropic.com/research/formal-verification

Comments URL: https://news.ycombinator.com/item?id=50202217

Points: 420

# Comments: 258

Article URL: https://www.eff.org/deeplinks/2026/10/canadians-are-running-out-time-oppose-dangerous-c-22-surveillance-bill

Comments URL: https://news.ycombinator.com/item?id=50202114

Points: 470

# Comments: 244

Hey HN, we recently open sourced our Consumer Agent Testing Tool to help teams iterate against proprietary assistants like Muse and Instinct. We built this to reduce our own frustrations with building an MCP/API for these agents to consume.

The problem: testing against these tools is hard! Agent memory + account statefulness make reproducibility, in the ways required for repeatable/reliable outcomes, between agents and the APIs/MCPs they interact with very challenging.

The solution: CATT lets devs test their services against a surrogate Muse or Instinct agent (not affiliated with either of these companies). Testers define starting conditions, approvals, and success conditions for their service's state. CATT then records the full interaction (incl. tool calls, responses) so it can diff what happened from what the agent reports. Runs can be tested in local builds or via CI, with or without LLM backing.

CATT is designed to emulate the important parts of personal assistant interactions. Its got:

- Tool calls and command-line tool access - Simulated approvals for service actions - Outcomes tracking and comparison - Optional MCP profile based on an unofficial Muse template

There are limitations to how much we know about different assistant specific behaviors so the tool labels its assumptions as `documented`, `unofficial`, `assumed` or `unknown` for developer review. We'll do our best to keep the tool updated as new insights about the internal workings of these assistants come to light. It is an area of active research and interest, a good example is this recent report on how Instinct uses Exa for web search [0].

Are you building a connector or MCP? If yes, we'd like to hear from you! Have you had assistants behave incoherently, use stale information, or procalim success without evidence? What else should we add tests for?

The best way to get started is...to point your coding assistant at the repo and ask it to integrate the tool with your CI or local testing pipeline!

Hope it's helpful!

[0]: https://www.sunbeam.ai/thoughts/instinct-is-using-exa-for-we...

Comments URL: https://news.ycombinator.com/item?id=50201860

Points: 4

# Comments: 0

Article URL: https://www.wolframcollatzmahler.com/rule30/index.html

Comments URL: https://news.ycombinator.com/item?id=50201842

Points: 15

# Comments: 3

Article URL: https://www.lesswrong.com/posts/WHEQps5PK8LrrcTAb/how-does-fable-5-1-hide-messages-in-images

Comments URL: https://news.ycombinator.com/item?id=50201445

Points: 177

# Comments: 56

Article URL: https://train.samismith.com/

Comments URL: https://news.ycombinator.com/item?id=50201414

Points: 107

# Comments: 26

Article URL: https://www.vanityfair.com/story/jared-kushner-hacked-phone-secret-negotiations

Comments URL: https://news.ycombinator.com/item?id=50201259

Points: 315

# Comments: 126

Title is a bit of an exaggeration but the question is more: if the frontier models are so good, why even sell them as your primary money maker?

Couldn't OpenAI or Anthropic make a lot more money by just starting companies themselves that leverage the models and building their own products?

Is selling tokens really the best strategy?

Especially with commodification and prices declining wouldn't that indicate there is more money to be made on the application-side of the models rather than the utility side

Comments URL: https://news.ycombinator.com/item?id=50200997

Points: 404

# Comments: 439