MurphyA/hacker-news huggingface dataset:
Show HN: Indie AI Directory – A Curated List of Indie AI Tools
by kristoff0601 | 2026-02-24 02:06:19+00:00
I’m the maker of Indie AI Directory — a purpose-built catalog that highlights independent AI tools, startups, APIs, and experiments built by makers who aren’t backed by big funds or traditional marketplaces.

What It Is

Indie AI Directory is a searchable, categorized directory of AI tools and resources created by indie developers and solo founders.
Each listing includes:

A short description of the AI product

A link to the tool or landing page

Relevant categories/tags for easier discovery

Optional founder credits and further links

The site is designed to help:

Discover emerging AI tools you may otherwise never find

Give indie makers visibility beyond social feed posts

Connect builders with early adopters and collaborators

Unlike most directories that are either static lists or focus only on funded startups, this one prioritizes indie-built AI work.

Why It Matters

There’s an explosion of AI tools every day, yet many interesting or useful projects — especially from solo builders — get buried in search or social feeds. A central, easy-to-browse resource helps:

Developers and users find niche tools faster

Founders get early traction, backlinks, and discoverability

The indie AI ecosystem gain visibility

I built this because as an indie maker myself, I saw too many makers struggle to find a place where their project could be both found and appreciated.

Paid Submissions (Why They Exist)

To keep the directory sustainable and well-curated, featured listing options are available. Paid submissions help cover:

Ongoing development & infrastructure

Manual curation and quality control

Better SEO and more traffic for all listings

You can still submit for free, but featured/priority positions bring extra visibility. Anyone can submit via:

https://indieai.directory/submit

I’ve structured the pricing to be:

Transparent and affordable for early stage makers

Predictable and worth the value if you’re looking for discoverability

Who This Is For

This directory is especially useful for:

AI builders looking for audience & early feedback

Developers searching for useful tools to integrate

Product teams scouting emerging ideas

Anyone interested in indie AI innovation

Feedback Welcome

I’m posting this here because HN folks are often early adopters, creators, and builders — the kind of audience who has experience with indie tools or launching them. I’d love feedback on:

What filters or categories would you find most useful?

What features would make this directory more valuable?

Do you see value in paid featured submissions?

Would appreciate honest thoughts — thanks!
by sendkamal | 2026-02-24 02:06:20+00:00
@cobertos The UI things should have been addressed. However I did to an extensive testing myself and everything seemed to have worked for me. I am sold that vibe coding is a thing, seriously. To your question about normalization cleaning - I have gone through multiple iterations - the data is definitely not clean and all. However, claude has made a function (instead of cleaning them on demand, it has a function which gets updated with every pattern so it could be reused).

For the pricing, to be honest I have zero hope to make money. Its just out there because I wanted to integrate this with stripe for payments and all. At the same time, if you look at competitor sites, they seem crap lol. plus look at their pricing. The site does have some operating cost and I will have to recover them if i can if I want it to be self sustainable but only if this is a value to someone. I am trying to make this a value. Please offer if you have ideas and I would appreciated it :)
by mrtksn | 2026-02-24 02:06:46+00:00
Your other posts are accusations about people and apparently you go after them on other sites too: https://news.ycombinator.com/item?id=46638491

I’m pretty sure if I keep pushing you enough eventually you’ll will make your life about going after me accusing me of who knows what. This means that your opinions should not to be taken seriously as your motivations are unclear.

You should consider having a different hobby.
by Veserv | 2026-02-24 02:08:02+00:00
The last time this did the rounds (before the post got flagged into oblivion)[1] I did my own analysis [2]. When normalized by vehicle-years it was actually closer to 40x worse than the Pinto, not just 17x as stated in the article.

[1] https://news.ycombinator.com/item?id=43039631

[2] https://news.ycombinator.com/item?id=43039925
by sendkamal | 2026-02-24 02:08:17+00:00
Hi @skadamat - I am not very experienced with claude code and don't know what it has done previously but new opus 4.6 is great. I think I need to work on claude.md. That really seems to be the soul of Claude. I've incurred quite a lot of money on API cost and claude plan and my time. But I feel like that can be cut to 1/4th easily with a solid claude.md plan.
by coppsilgold | 2026-02-24 02:08:39+00:00
Private keys from secure elements leak all the time. There will be a flawed implementation that someone exploits, an insider will smuggle a key out etc.

This is why true zero-knowledge systems for this sort of thing aren't practical and will never be. Because a SINGLE leak will break it and there will be no way to even detect it.

The attestation systems you reference don't even allow true zero knowledge attestation, they involve a trusted intermediary to convert your burned-in private key to a temporary key which you use for attestation with a third party.

And the temporary key isn't even a product of a blind signature. And it's rate limited. So if a service selling these temporary keys shows up they will be able to easily trace it to the burned-in key responsible - then revoke it and if possible initiate legal action.

This also means that whenever you register to a service using one of these schemes you are registering with your real identity, it's only a question of how hard and how many parties need to collude to extract it.

And in the event that they really do blindly sign tokens generated on your device, then their scheme will not survive adoption. As it gets adopted, the value of these blind signatures will rise and services that sell them will pop up. There will be no way of tracing the sold blind signature to the compromised/colluding device and rate limiting will merely necessitate a farm of such devices as opposed to a single leaked key.

*Note that Blind Signatures are Zero Knowledge.
by nanobuilds | 2026-02-24 02:09:11+00:00
It can always forward you things to your real email for you to action them. So as a layer doing the boring work of sorting things, researching, and keeping track of changes, but execution, public actions, real-life stuff can still be confirmed by the human (through telegram for example).

There are some good uses if managed properly but people tend to trust ais more and more these days.
by cpgxiii | 2026-02-24 02:09:20+00:00
I think you're missing my point entirely. If your project needs specific hardware, you have to use that specific hardware (the obvious examples of which would be Jetsons or Zynq/Zynq-like or something ASIL-D or something that tightly couples "A"/M/R cores together, or you are stuck using a SoC from Qualcomm for cell connectivity). There are a lot of projects that do fall into that category.

There are also a (much smaller) number of projects that will legitimately see the kind of scale of production that justifies aggressive cost optimization for the compute platform, either in terms of designing their own around a SoC or picking some SBC/SoM that they can get a good deal on, where the significant additional up-front engineering cost is outweighed by the production savings (and where the desire/need to keep a fixed platform means the often limited platform support from the vendor is less restrictive).

But a large number of robotics projects (basically everything in the research sphere) - this one very much included - just need "some computer" for general-purpose use. They are already separating realtime control onto a separate microcontroller board. For these projects, it is almost always committing a "premature pessimization" of picking some weird SBC. You are signing up for worse CPU and GPU performance, stability, and development future for very little reward.
by frde_me | 2026-02-24 02:10:08+00:00
> I get it that in 10 years all of this might peak and we're gonna be content using old models

I would personally be happy using gpt 5.3 codex for the foreseeable future, with just improvements in harnesses

IMO we're already at the point where even if these company collapse and the models end up being sold at the cost of inference (no new training), we would be massively ahead
by caseyolayos | 2026-02-24 02:10:12+00:00
Hey, I'm the maker. Happy to answer questions — here's what the build actually looked like.

Stack: Solana (Anchor framework), Next.js on Vercel, Helius RPC, catbox.moe for metadata hosting. The bonding curve is a constant-product AMM (x*y=k) with virtual reserves to set the initial price — same basic mechanism as pump.fun.

The AI workflow: I used an AI assistant (Claude via OpenClaw) that has persistent memory, filesystem access, and can run shell commands. I'd describe what I wanted, it would write the code, run the tests, fix errors, and deploy. I handled the judgment calls: product decisions, when something felt wrong, what to prioritize. It handled the implementation. The feedback loop was fast enough that we could iterate on a bug in one conversation turn.

The hardest bug: Solana's rent-exempt minimum. Every account needs a minimum SOL balance (~0.00089 SOL) before it can hold data. On the first buy for any new token, the fee vault and curve vault are both at zero — so the transaction fails with "insufficient funds for rent" before any tokens change hands. We debugged this at 2am, realized the contract was correct but the bootstrapping wasn't, and manually seeded the fee vault with 0.001 SOL to unblock first purchases. The UI now enforces a 0.001 SOL minimum buy.

What surprised me: The AI was better at implementation than I expected and worse at debugging novel runtime errors than I expected. Writing an Anchor program from scratch — fine. Diagnosing why a Solana transaction fails at the RPC level with a cryptic error message — that needed more back-and-forth.

What's next: Getting a real artist (not me) to launch their token. Everything else — the platform, the contracts, the bonding curve — is working. The distribution problem is the hard part, same as always.

fanstake.app if you want to poke at it.
by hn_acker | 2026-02-24 02:11:35+00:00
In Justice Gorsuch's concurrence, his argument that the majority opinion written by Justice Kagan in this tariffs case is inconsistent with votes of previous Democratic justices in previous cases about executive branch discretion does not hold water [1]. Also, there's this tidbit (where MQD stands for major questions doctrine) [1]:

> After falsely claiming that the Democratic appointees “do not object to [the MQD’s] application in this case” (which, in point of fact, they do),

[1] https://www.stevevladeck.com/p/212-the-gorsuch-kagan-tariffs...
by qrios | 2026-02-24 02:11:58+00:00
A simple skill markdown for Claude Code was enough to use the local Wolfram Kernel.

Even the documentation search is available:

```bash

/Applications/Wolfram.app/Contents/MacOS/WolframKernel -noprompt -run '

Needs["DocumentationSearch`"];

result = SearchDocumentation["query term"];

Print[Column[Take[result, UpTo[10]]]];

Exit[]'

```
by nkrisc | 2026-02-24 02:12:03+00:00
Looking at the tweet he’s replying to, I still find it incredible people talk to these LLMs as if they are rational beings who will listen to them. The fact that they sometimes do is almost coincidence more than anything.

It’s even more unbelievable that they seem to think instructions are rules it will follow.

To paraphrase Captain Barbossa: “They’re more guidelines than actual rules.”
by BlitzGeology91 | 2026-02-24 02:12:20+00:00
> But at least by going down that road, you end up with more games, better games, and people learning skills throughout the process. And who knows, maybe one is a mega success.

Yes, but in that scenario, some really good games would still die. So it would good to make it illegal to kill games in addition to making more games.

> Sure, you can stand there pounding your chest for "democracy," but I contend that those who are building their own things are practicing it far more than those who are demanding others make things for them.

I mean, in the short term, yes, the Stop Killing Games movement is demanding that others do some work for them. But, in the long term, the Stop Killing Games movement is asking for others to do less work.

The only reason why games are being killed are because companies are putting in extra effort to include self-destruct mechanisms in games. If a company doesn’t want to bother disarming these self-destruct mechanisms, then there is a simple solution: don’t create the self-destruct mechanisms to begin with. It’s much easier to create games that don’t have self-destruct mechanisms.

I’m a strong supporter of demanding that companies stop doing bad things and that they put in effort to undo the bad things that they have already done.
by DaedalusII | 2026-02-24 02:12:27+00:00
pornography is not a profitable industry. even famous participants like 'mia khalifa' only made GBP9.5k (USD 12.8k) lifetime earnings. The average onlyfans has about 21 fans, with an average subscription price of $7.20.

the future of the industry is probably ai slop, personalised ai, and so on

one of the purposes of the porn industry in 00s was money laundering: cash only, large stores with no CCTV, very sparse records, not possible to objectively value why a dvd was being sold for $85
by reitzensteinm | 2026-02-24 02:13:51+00:00
Proceeds going to charity is a must for me - it keeps it friendly and significantly reduces the impact of counterparty risk.

There's a reason Long Now uses this format, and I'm happy to use their platform and pay the fee: https://longbets.org/rules/

Email is reitzensteinm@gmail.com if you're interested.
Ask HN: Would you pay for video prototype validation before building?
by zhongyongxu | 2026-02-24 02:14:31+00:00
I'm a developer who's wasted months building features nobody wanted.

Now I'm exploring a service: create 3-minute video prototypes to validate demand
before writing code, then run targeted surveys.

The pitch: $500-1000 and 3-5 days to avoid a $20k failed MVP.

I don't have a product yet—just talked to 2 devs who said they'd use it.

Questions:
1. How do you validate features today?
2. Would you trust "fake" video prototype data?
3. What would make you actually pay for this?

Looking for brutal honesty before I build anything.
by roryokane | 2026-02-24 02:15:07+00:00
The whitepaper says that the benchmark counted accessibility problems using the tool axe-core (https://github.com/dequelabs/axe-core). It’s too bad that neither the site nor the paper contains any examples of an LLM output and its list of detected problems. I am curious about these aspects:

• Which of axe-core’s rules (https://github.com/dequelabs/axe-core/blob/develop/doc/rule-...) LLMs violate most often

• Which groups of users are most affected by those rule violations (e.g. blind users or deaf users)

• Whether it’s likely that I unintentionally violate those same rules in web pages I write

Examples of rule violations and statistics on most-violated rules would make the website more convincing by showing that the detected accessibility errors reflect real problems. It would rule out that the only detected error was a single noisy false positive rule in axe-core. I bet that most readers are not familiar enough with axe-core to trust that it has no false positive rules.
by pornel | 2026-02-24 02:15:13+00:00
I've looked at the code from the PR. It seems to use safe types and standard idioms like pattern matching, so at least at first glance it looks like Rust.

It could have been worse. C++ code naively converted line-by-line to Rust typically results in weird and unsafe Rust, but in this case it seems they've only been strict about the results being the same, not the structure of the implementation.

Rewrites have a very high risk of introducing regressions. Trying to fix bugs while rewriting will only make things harder, because instead of simply comparing outputs exactly, you'll have to judge which output is the right one. If you let the behavior significantly diverge during the rewrite, you'll just have two differently buggy codebases and no reference to follow.

It's much easier to make a bug-for-bug compatible copy, and fix bugs later.
Show HN: Enseal – Stop pasting secrets into Slack .env sharing from the terminal
by ops_mechanic | 2026-02-24 02:15:13+00:00
We've all done it — "hey can you DM me the staging .env?" Secrets end up in Slack history, email threads, shared notes — all searchable, all persistent. The secure path (1Password, GPG, etc.) always had more friction than the insecure one, so people took the shortcut.
enseal makes the secure path faster than the insecure one:
# sender
$ enseal share .env
Share code: 7-guitarist-revenge
Expires: 5 minutes or first receive

# recipient
$ enseal receive 7-guitarist-revenge
ok: 14 secrets written to .env
Zero setup, no accounts, no keys needed for basic use. Channels are single-use and time-limited. The relay never sees plaintext (age encryption + SPAKE2 key exchange).
For teams that want more: identity mode with public key encryption, process injection (secrets never touch disk), schema validation, at-rest encryption for git, and a self-hostable relay.
Written in Rust. MIT licensed. Available via cargo install, prebuilt binaries, or Docker.
Looking for feedback on the UX and security model especially. What would make you actually reach for this instead of the Slack DM?

Detailed documentation here: https://enseal.docsyard.com/
by janalsncm | 2026-02-24 02:15:18+00:00
Yeah it’s confusing because there are really three “evaluations” you could have for a position

1) god-mode 1/0/-1 which you could argue is the “true” position
2) engine centipawns which help the search algorithm
3) human evaluation which would distinguish between two positions in terms of a subjective difficulty

For example, two positions might be 0.0 on the eval bar but one position is an obvious draw and in the other position one player has to walk a tightrope of precise moves to draw. Just because that’s obvious to a computer doesn’t mean a human can easily draw the second position.
by peteforde | 2026-02-24 02:15:35+00:00
I am baffled by the popularity of *claw but I am always looking to learn, so I was happy to have the algo serve me this YT video of Limor explaining how she had a sandboxed claw running a local LLM to chew through a particularly dense datasheet to create a wrapper library and matching test coverage. https://www.youtube.com/watch?v=fdidNp5IHHI

This example is, as of this moment, the only example that has communicated to me that February 2026's local agent harnesses have some utility in the right context and expert hands.

I was particularly bolstered by the unintentional but very real demonstration of how LLMs really can be leveraged to free up humans to spend more parent time with their infants. We spend a lot of characters lamenting how we never got jetpacks, so here's someone doing it right.
by ryandrake | 2026-02-24 02:15:52+00:00
No mention of Shatner's music career is complete without listing Spaced Out: The Best of Leonard Nimoy and William Shatner[1]. And, yes, it's exactly as -unique- as you'd imagine it might be.

1: https://www.amazon.com/Spaced-Out-Leonard-William-Shatner/dp...
by bigbadfeline | 2026-02-24 02:15:58+00:00
> Anthropic CEO has stated they have high margins on inference, so training is the big cost center.

I'm pretty sure that in corpo-speak "inference" excludes the cost of datacenter construction, GPUs and other hardware, manual data cleaning, R&D, administration, etc - basically everything except the power bill for inference.

I have absolutely no problem with companies that run inference only - plenty of them offer open models as a service - they're usefull and their accounting can be believed... but they don't have near $ Trillion valuations and they don't misallocate capital on a vast scale as the frontier models do.

The point of the OP is that closed models don't pay for themselves and, on the scale of the US economy, they provide minuscule economic advantages compared to the enormous investments they consume.
by DrewADesign | 2026-02-24 02:16:15+00:00
> We're still 6-12+ months away from a "killer" AI product. OpenClaw showed what's possible-ish, but it breaks half the time, eats tokens like crazy, and can leak all kinds of secrets.

If you replace OpenClaw with any number of other hot LLM products/projects, I’ve been hearing that same exact sentiment for numerous 6-to-12-month periods. I’d argue we have no idea how long it’s doing to be, but it’s probably not very soon.
by szmarczak | 2026-02-24 02:17:07+00:00
Yea sure Immich taking zero responsibility for possibly causing damages in hundreds of dollars and not warning their uses is fair, yeah, let them go. Maybe actually read the issues before judging? (oh noes, he blame them so he must be bad!)

[1] https://szmarczak.com/immich.png
[2] https://github.com/immich-app/immich/issues/25283

> you’ll will make your life about going after me accusing me of who knows what

I have never accused you of anything but lack of information. I don't get where you're coming from.
by maxdo | 2026-02-24 02:17:24+00:00
there literally slew of companies who went in 1 year from mid size business to multi billion ARR.

And yeah, blah blah they burn money blah blah. Check Anthropic CEO interviews. He openly describe the balance problem :
- cost of training a new model
- newly built infra ratio of training vs inference
- market adoption, that is despite extremely quick is not unlimited, since even market is not unlimited.

essentially it's a tricky balance, between you do not invest today you will loose tomorrow vs you invest too much and go bankrupt next year.
by neya | 2026-02-24 02:18:23+00:00
> why sane developers who for decades have been advocating for best practices when it comes to security and privacy seem to be completely abandoning all of them

I'm a sane developer. I do not trust AI at all. I built my own personal OpenClaw clone (long before it was even a thing) and ran controlled experiments inside a sandbox. My stack is Elixir, so this is pretty much easy. If an agent didn't actually respect your requirements, it's just as easy as running an iex command to kill that particular task.

In my experience, AI, be it any model - consistently disobeys direct commands. And worse, it consistently tried to cover up its tracks. For example, I will ask it to create a task within my backend. It will tell me it did - for no reason at all, even share me a task ID that never existed. And when asked why it lied, it would actually spin the task up and accuse me of not trusting it.

It doesn't matter which vendor, which model. This behaviour is repeatable across models and vendors. Now, why would I give something like this access to my entire personal and professional life?

To group me and others like me with the clowns doing this is an insult to me and others who have accumulated decades of experience and security best practices and who had nothing to do with OpenClaw.
by slopinthebag | 2026-02-24 02:18:39+00:00
Lol. I tried doing some image generation with SOTA models. I explicitly asked it not to do something it was doing and it would literally do the thing, and straight up tell me it didn't.

Unless someone has a cognitive impairment it's just simply not a failure mode of cooperative humans. Same with hallucinations. Both humans and AI can be wrong, but a human has the ability to admit when they don't understand or know something, AI will just make it up.

I don't understand why people would ever trust anything important to something with the same failure mode as AI. It's insane.