wenbin

It’s a great way for developers or ai agents to test drive an API without creating and account and getting an API key from the api provider.

This could also make abusing use / DDoS attack very costly

If contents are generated instantly via llm and packaged as books, videos, podcasts, pull requests etc, then they don’t deserve human attention.

At listennotes.com , we have to delete tons of fake podcasts submitted to our site [1]

why do people create fake podcasts? they want to get backlinks from all podcast directories

podcasts are distributed via rss feed. and spammers/"growth hackers" put tons of links in the rss feed.

and podcast hosting services (especially those allow free trials, e.g., rss.com, ) could help them one-click to distribute to a bunch of podcast apps / websites. this is like one-click large scale spamming automation

any examples? here you go -

* https://podcasts.apple.com/us/search?term=UU88%20

* https://podcasts.apple.com/us/search?term=%E6%B6%A8%E7%B2%89

* https://open.spotify.com/search/%E6%B6%A8%E7%B2%89/podcasts

most podcast websites / apps don't delete fake podcasts like we do at listennotes.com . so i guess the backlink hack w/ fake podcasts works. real human podcast listeners might suffer with spammy fake shows even on Apple Podcasts and Spotify.

[1] https://www.listennotes.com/podcast-stats/#growth

From our experience at listennotes.com over past ~10 years - people do click share buttons. For us, it's still worth the screen real estate to place share buttons.

It’s basically bullshit jobs — https://en.wikipedia.org/wiki/Bullshit_Jobs

The compensation can be high, but the psychological cost is real. Over time, that tradeoff isn’t always worth it: someone might earn more in the short term, yet pay for it with chronic stress, declining mental health, and even a shorter lifespan compared to a lower-paid role that’s more meaningful and less draining.

This is awesome!

Maybe google web search should automatically label ai-generated articles

dataset for ~40,000 ai slop podcasts - https://www.kaggle.com/datasets/listennotes/ai-generated-fak...

And Listen Notes is removing 4000 to 8000 ai slop podcasts per month - https://www.listennotes.com/podcast-stats/#growth

Similar stats for podcasts - https://www.listennotes.com/podcast-stats/#growth

I’m building CurateKit.com - a lightweight content curation tool.

I always have growing lists of short texts, facts, and links that I wanted to host on a standalone site rather than burying them in a notes app. The workflow is simple: a browser extension to clip links with remarks, which then feeds into a public-facing list.

I’ve also added a "Substack-lite" feature. Instead of long-form writing, it lets you send simple roundup email digests (e.g., "Top 5 links this week") to opt-in subscribers.

My personal blog (wenbin.org) is currently powered by the tool.

CurateKit.com is in private beta while I'm fine-tuning a few things now, but I’m opening up invites to the waitlist over the next few days if anyone wants to give it a try.

“pessimists sound smart , but optimists make money”

Does this mean AWS's #1 position is safe?

Every big cloud provider has its share of UX/stability/customer support issues.

At this point, it feels less like AWS is the 'least bad' option because alternatives are even worse.

Curious - in this situation, does delve return money to YC? Or YC simply writes off the investment

I guess vibe coding can't solve such problem for now...

Yea, good old days :)

The catch was that old boxed software eventually breaks on new OS versions or devices.

However, SaaS has the potential to "freeze" features while remaining functional 20+ years down the road. Behind the scenes, developers can update server dependencies and push minor fixes to ensure compatibility with new browsers and screen sizes.

From the end-user's perspective, the product remains unchanged and reliable. To me, that’s very good!

We should normalize "finished" software products that stop feature creep and focus strictly on bug fixes and security updates.

It takes real courage for a builder to say, "It’s good enough. It’s complete. It serves the core use cases well." If people want more features? Great, make it a separate product under a new brand.

Evernote and Dropbox were perfect in 2012. Adding more features just to chase new user growth often comes at the expense of confusing the existing user base. Not good

HN is full of tech savvy people. Yet an llm slop article is upvoted to the front page of HN...

Imagine how deceptive llm slop contents are to the general population.

Same for podcasts (and other types of online contents) -

Here's a dataset of 26,000+ ai-generated "podcasts"

https://www.kaggle.com/datasets/listennotes/ai-generated-fak...

if you use microfeed.org , you can use jsonfeed , eg, https://www.microfeed.org/json/

It's similarly insulting to listen to your AI-generated fake podcasts[0]. Ten minutes spent on them is ten minutes wasted.

[0] AI-generated fake podcasts (mostly via NotebookLM) https://www.kaggle.com/datasets/listennotes/ai-generated-fak...

Maybe some of them already embed some simple, secret marker to identify their own generated content. But people outside the organization wouldn’t know. And this still can’t prevent other companies from training models on synthetic data.

Once synthetic data becomes pervasive, it’s inevitable that some of it will end up in the training process. Then it’ll be interesting to see how the information world evolves: AI-generated content built on synthetic data produced by other AIs. Over time, people may trust AI-generated content less and less.

AI will create ever more AI-generated synthetic content because current systems still can't determine with 100% certainty whether a piece of content was produced by AI. And AIs will, intentionally or unintentionally, train on synthetic content produced by other AIs.

AI generators don't have a strong incentive to add watermarks to synthetic content. They also don't provide reliable AI-detection tools (or any tools at all) to help others detect content generated by them.

I really hope SynthID becomes a widely adopted standard - at the very least, Google should implement it across its own products like NotebookLM.

The problem is becoming urgent: more and more so-called “podcasts” are entirely fake, generated by NotebookLM and pushed to every major platform purely to farm backlinks and run blackhat SEO campaigns.

Beyond SynthID or similar watermarking standards, we also need models trained specifically [0] to detect AI-generated audio. Otherwise, the damage compounds - people might waste 30 minutes listening to a meaningless AI-generated podcast, or worse, absorb and believe misleading or outright harmful information.

[0] 15,000+ ai generated fake podcasts https://www.kaggle.com/datasets/listennotes/ai-generated-fak...

missed the good old days of telnet bbs & newsgroup :)

Earlier this year, we at Listen Notes switched to Better Stack [0], replacing both Datadog and PagerDuty, and we couldn’t be happier :) Datadog offers a rich set of features, and as a public company, it makes sense for them to keep expanding their product and pushing larger contracts. But as a small team, we don't have a strong demand for constant new features. By switching to Better Stack, we were able to cut our monitoring and alerting costs by 90%, with basically the same things that we used from Datadog previously.

[0] https://www.listennotes.com/blog/use-betterstack-to-replace-...

https://Transcript.New

Let me guess - the keyword here is "Section 174", just from the title alone :)

Dealing with Section 174 amortization in those first one to three years is a real headache (and your tax bill ends up higher than if it didn’t apply). Once your startup survives that the first few years of doing Section 174, things do get easier... but, sadly, most don't make it that far.

There could be a better system (for me): a read-it-later app with a strict limit—say, 3 or 5 slots. If it's full and you add a new article, the oldest one gets automatically deleted to make room. That way, you always have something to read, but never feel overwhelmed by an endless backlog.

One issue I've had with read-it-later apps is that I end up accumulating far too many articles and never actually reading them. Now my approach is simple: if I see something I want to read, I either read it immediately or never.

Congrats on the launch.

This reminds me of https://www.heavy.ai/ (previously MapD back in 2015/16?)