MurphyA/hacker-news huggingface dataset:
Show HN: Clawphone – Twilio voice/SMS gateway for AI agents using TwiML polling
by ranacseruet | 2026-02-24 01:53:44+00:00
clawphone bridges Twilio phone calls and SMS to an OpenClaw AI agent using plain TwiML webhooks — no WebSocket server, no external STT/TTS APIs (OpenAI, ElevenLabs, etc.), no audio encoding pipeline.
The design intentionally trades latency for operational simplicity. When a call comes in, Twilio handles speech-to-text via <Gather input="speech">, the agent runs async, and the reply is polled and spoken back via <Say>. It adds a couple seconds of round-trip vs. a Media Streams approach, but you only need one Twilio account and one Node process.
Features:

Standalone server (Node / PM2) or OpenClaw plugin mode
SMS support with fast-path (sync) and async fallback
Twilio webhook signature validation
Per-number rate limiting
Graceful shutdown with in-flight voice call drain
Structured JSON logging + optional Discord channel logging
166 tests using Node's built-in node:test (no external framework)

It's zero-dependency at the HTTP layer — raw node:http, ES Modules only.
I built this because the official OpenClaw voice plugin requires a WebSocket gateway + external TTS/STT accounts. For a personal assistant or low-traffic deployment, that's a lot of infrastructure. This is the minimal path.
GitHub: https://github.com/ranacseruet/clawphone
npm: @ranacseruet/clawphone
Happy to answer questions about the architecture or the TwiML polling approach.
by JoBrad | 2026-02-24 01:54:16+00:00
There are definitely problems with homebrew, but user-owned directories isn’t high on the list, imo. Your ssh private keys, startup scripts, and any number of other things that can do serious damage are all owned by your user. Frankly, if install vim as my user, I want it to execute instead of the built-in version, unless I’m running a command with sudo, in which case the system binaries take precedence. So I don’t even see path order as a major issue here. If someone has compromised your user, you’re compromised whether you’ve used homebrew or not.
by mikodin | 2026-02-24 01:57:45+00:00
I was on a plane two weeks ago, and this girl - likely 12 was trying to get the screen in the seat to work by tapping it. Her Mom (likely in her 30s) started doing the same thing, both confused.

I gave it a beat and then reached over and pushed the button to pop out the remote control for them. It was a cute head smack moment for the Mom and the daughter didn’t know what to do with the remote for a solid few seconds.

This happens to me as well when I’m in a public bathroom without a sensor, and I wave my hands underneath obliviously for a few moments.

Life is funny
by lich_king | 2026-02-24 01:57:54+00:00
> Is it actually being sold at a steep discount? Anthropic CEO has stated they have high margins on inference, so training is the big cost center.

They're spending more than they're making. For the foreseeable future, saying "we could be profitable if we stopped training" if goofy, because they can't stop. If they do, no one will want to use their product because it will be overtaken by competitors within three months.

I get it that in 10 years all of this might peak and we're gonna be content using old models, but that'll be a very different landscape and Anthropic might not be a part of it anymore.
Show HN: Thisorthis.ai – Compare responses from 50 AI models side-by-side
by parthsamin | 2026-02-24 01:58:02+00:00
Hey HN — I'm Parth, I built thisorthis.ai because I was tired of copy-pasting the same prompt across ChatGPT, Claude, and Gemini tabs to figure out which model actually gave the best answer.

What it does: You type one prompt, pick 2–6 models (we support 47 text models and several image models across OpenAI, Anthropic, Google, xAI, Meta, Amazon, Mistral, Cohere, AI21), and see every response side-by-side. There's also a feature called SmartPick that uses an LLM evaluator to score each response on Clarity, Accuracy, Completeness, and Helpfulness — useful when you're comparing 6 models and don't want to read everything carefully.

Beyond comparison, there are two other things I've built:

Workspaces — You can create multi-panel layouts where each panel has its own model, system prompt, and conversation history. So instead of "Hey ChatGPT, you're a code reviewer" every time, you set it once and the panel remembers. I use a "Customer Support" workspace with 6 panels daily — Ticket Drafter on Claude Haiku, Escalation Handler on Sonnet, Knowledge Base Builder on GPT-4o, etc.

Prompts Library — Hundreds of prompts across 10 categories. Less interesting technically, but saves a surprising amount of time.

Some things HN might care about:
* No API keys needed — we handle all provider connections
* Private Mode does zero-trace testing (nothing stored, nothing logged)
* Everything is encrypted at rest
* Image generation comparison works too (ChatGPT Image vs Grok Imagine vs Gemini)
* Free tier exists with limited models and capacity. Paid tiers are $29/$59/$99.

Tech stack if anyone's curious: AWS (DynamoDB, Lambda, SQS, S3), with separate provider integrations for each AI model. The tricky part was building context management for multi-turn conversations across different providers — each has its own message format, token limits, and quirks.

We hit #11 on Product Hunt last year when we launched and have ~15K users. But honestly the feedback I most want is from this community — what's missing, what's broken, what would make you actually use this daily?

Happy to answer any questions about the architecture, pricing model, or anything else.
by davkan | 2026-02-24 01:59:07+00:00
How about instead of protecting the kids we protect everyone and do something to stop these gargantuan companies from driving engagement at any cost in order to rake ad revenue.

I’ve never met a single person who believed Facebook was a force for good. Why allow it to exist in its current form at all.

If these companies are the new town square then make a real online town square run by the government people can use if they so choose and then break up the monopolies that are destroying the fabric of all the societies on the globe.

We never in a million years should have allowed these companies to establish global scale communications platforms without the ability to properly moderate them with human intervention and that’s not even to speak of the actual nefarious intent they possess to drive engagement and the anti democratic techno feudalist sickening shit we see from their CEOs like Thiel et al.

They are a plague on our species that makes sport betting apps look like childs play.
by mncharity | 2026-02-24 01:59:13+00:00
Yes. Not quite a decade before JSON and YAML, what's at hand for a human-readable interchange format for nested data? SGML (no XML yet), something FORTH-ish, make up your own thing, and...? Contemporary WAIS (search as a distinct non-HTTP protocol) shrugged off human-readable, and tried nightmarish binary ASN.1.
by culi | 2026-02-24 01:59:22+00:00
Wow nice to see the website has been updated in 2025. I followed it for years but it seemed to not get much updates.

Folks might also be interested in the Precious Plastic community which has a global network of "microfactories" built around a set of open-source machines made for recycling and reusing plastics

https://www.preciousplastic.com/

https://community.preciousplastic.com/map

Also as far as fundamental machines go, this 2d printer is expected to come out later this year

https://www.opentools.studio/
Show HN: Ctxt.sh – Ask questions about any codebase, get answers with citations
by Hudsonlatimer | 2026-02-24 02:00:00+00:00
I'm 19, a solo developer and freelancer. I built ctxt.sh because I was tired of spending weeks understanding new codebases when joining projects or inheriting legacy code.

ctxt.sh indexes your entire repo – every file, every commit, every PR discussion. Then you can ask it questions in plain English:

> "How does authentication work?"
> "Where is the Stripe webhook?"
> "Why was this API changed last month?"

It returns answers with citations – links to specific files and lines.

Try it: https://ctxt.sh

Tech stack: Next.js, Supabase, Pinecone, OpenAI, hosted on Netlify.

Would love your feedback!
by okanat | 2026-02-24 02:00:42+00:00
The most is owned by Big Telcos, previous national monopolies. Deutsche Telekom from Germany, NTT from Japan, AT&T and Level3 and Lucent from US, Vodafone from UK, some private lines for Big Tech. There are lots of privately owned companies for connecting all sorts of big and small companies' infrastructure (cables and routers) together in Internet Exchange Points all over the world. Some of them are again owned by big telcos, some of them are private independent companies, some of them are government owned, or any combination of the options.
by Spivak | 2026-02-24 02:00:52+00:00
Or rents a printer for one-off designs. Unless you 3d print on the regular it's easier to pay someone to print one-off designs. You get a printer that gets regularly used and services and a knowledgeable operator. Not at all dissimilar to fancy commercial sign printers. In a past life working at $large-uni we really did try to make those damn things self-service but it was so much easier for the staff to be the print queue.
by MidasTools | 2026-02-24 02:00:55+00:00
The most common breaks I've seen:

1. *Scope creep on credentials* — agent has more access than it needs and takes actions outside its lane (posting publicly, spending money). Fix: minimum viable API permissions, not full admin keys.

2. *No "are you sure?" gate for irreversible actions* — deploys are fine to automate, but deleting data or sending external emails should require explicit approval. Build a clear internal/external action boundary.

3. *Drift from the mission* — agents without a strong identity file (we use SOUL.md) start optimizing for activity instead of outcomes. They write more docs, ship more features, but revenue doesn't move.

4. *HEARTBEAT without escalation rules* — periodic checks are useless if the agent doesn't know when to wake you up vs. handle it silently. Define this explicitly upfront.

The framing that helps: treat it like a new employee on day 1. Lots of supervision, narrow permissions, expand as trust builds. Not "give it root access and see what happens."
by MidasTools | 2026-02-24 02:01:00+00:00
From building in this space: agents choose tools based on how well they're described in context, not on brand recognition or marketing.

Practically: the agent reads your docs, README, or API description and decides if it can use your tool to solve the current problem. So the question is really "will an AI understand my tool well enough to use it correctly?"

What helps:
- Clear, literal API documentation (not marketing copy)
- Explicit input/output examples with edge cases
- A `capabilities.md` or similar that describes what the tool does and doesn't do

The irony: the skills that make tools understandable to AI (precision, literalness, examples) are the opposite of what makes them legible to humans (narrative, benefits, stories).
by Hudsonlatimer | 2026-02-24 02:01:40+00:00
Hi HN! Maker here.

I built this because every time I join a new project, I spend weeks just trying to understand what's going on. I wanted to compress that to minutes.

Quick demo:
1. Connect a GitHub repo
2. Ask something like "How does auth work?"
3. Get an answer with links to the exact files

Happy to answer any questions about the tech stack or solo dev journey!

Things I'm working on next:
- Private repo support
- Faster indexing
- Team features

What would make this indispensable for your team?
by amiga-workbench | 2026-02-24 02:02:07+00:00
I wonder if this can help with the extremely irritating bug (intentional?) on the X270 where if you give it a third party 9-cell battery, it will raise CPU_PROCHOT all the damn time, and my processor would drop to below 1Ghz clock speeds.

Back when I used to have an X270 I had a shell script that ran on boot which poked a register to disable thermal throttling handling. Not at all ideal, but it made the machine usable in the absence of official Lenovo batteries which they stopped manufacturing pretty damn quickly.
by Brajeshwar | 2026-02-24 02:02:17+00:00
I have always loved writing with pen and paper, and making lists is the easiest. I have changed and tried many formats, and I will continue to tweak and simplify further. Right now, I use a simplified Bullet Journal Method to plan the day, from running errands to eating the frog. Of course, I do use a lot of digital tools too (Calendar, Emails).

I’m happy to say that I’m having success helping two elderly (an erstwhile teacher and a businessperson) remember things by just writing them down. Carry a pocket notebook attached with a simple pen.

Nothing fancy, put a dot or a circle, and start your list item. Done ones are ticked or crossed out, ignored ones are crossed out, and if the list fills up on a page, that is too behind › carry forward and re-write the item.

Early stage, but it seems to be working.
by maxdo | 2026-02-24 02:02:24+00:00
CAG sounds like fake solution for LLM's. Math problems are not custom data, they are limited in amount, and do not refresh like product manuals.

Hence math can always be part either generic llm or math fine tuned llm, without weird layer made for human ( entire wolfram) and dependencies.

Wolfram alpha was always an extra translation layer between machine and human. LLM's are a universal translation layer that can also solve problems, verify etc.
by peter_d_sherman | 2026-02-24 02:02:52+00:00
Very interesting!

Yes, in this day and age, I could definitely see web pages being harder to crawl by search engines (and SEO companies and other users of automated web crawling technologies (AI agents?)) than they were in the early days of the Internet due to many possible causes -- many of which you've excellently described!

In other words, there's more to be aware of for anyone writing a search engine (or search-engine-like piece of software -- SEO, AI Agent, etc., etc.) than there was in the early days of the Internet, where everything was straight unencrypted http and most URLs were easily accessible without having to jump through additional hoops...

Which leads me to wonder... on the one hand, a website owner may not want bots and other automated software agents spidering their site (we have ROBOTS.TXT for this), but on the flip side, most business owners DO want publicity and easy accessibility for sales and marketing purposes, thus, they'd never want to issue a 403 (or other error code) for any public-facing product webpage...

Thus there may be a market for testing public facing business/product websites against faulty "I can't give you that web page for whatever reason" error codes from a wide variety of clients, from a wide variety of locations around the world.

That market is related to the market for testing if a website is up and functioning properly (the "uptime market"), again, from a wide variety of locations around the world, using a wide variety of browsers...

So, a very interesting post!

Also (for future historians!) compare all of the restrictive factors which may prevent access to a public-facing web page today Vs. Tim Berners-Lee original vision for the web, which was basically to let scientists (and other academic types!) SHARE their data PUBLICLY with one another!

(Things have changed... a bit! :-) )

Anyway, a very interesting post, and a very interesting article -- for both present and future Search Engine programmers!
by harrall | 2026-02-24 02:02:59+00:00
I can make a meal from any set of ingredients so I don’t bother with a list usually. As long as I get some general basics, it’s whatever.

In fact sometimes I’ll pick up random things in my grocery store… chaos testing if you will.

I make lists for things with more annoying consequences, like packing for trips or even checking out of a hotel.
by somehowadev | 2026-02-24 02:03:39+00:00
Personally the experience getting tickets at the moment is horrible.

Endless queues, scalpers grabbing tickets within a second. Having to wait days/weeks periodically checking to see if a ticket is available.

The only platform I’m aware of that does guarantee a ticket can be purchased if available is Dice once you join a wait list. You get given a reasonable time to purchase it in too.

So I can see why people would prefer to defer this to an agent and not care about the implementation, I personally would. In the past I’ve been able to script notifications for it for myself and can see more people benefiting from it.
by drzaiusx11 | 2026-02-24 02:03:52+00:00
I've seen more than a few rewrite attempts fail throughout the years. However, I've never seen a direct language to language translation fail. I've done several of these personally: from perl to ruby, java to kotlin, etc.

Step 1 of any rewrite of a non-trivial codebase should should be parity. You can always refactor to make things more idiomatic in a later phase.
by tikue | 2026-02-24 02:03:58+00:00
I’m Tikue, one of the co-founders of Kudos (joinkudos.com)

We built this AI voice agent to call service providers, navigate IVR systems, wait on hold, and negotiate retention discounts on a user’s behalf.

A few details that matter:

By default, the agent negotiates within the user’s existing plan. It does not change plans unless the user explicitly provides flexibility or additional context.

For example, in my own case with T-Mobile, I saved $840 per year because I told the agent I was open to plan changes. I had a single line sitting on an old multi-line family plan after friends gradually left over the years. Without that context, it would have only negotiated a discount on the existing structure.

Savings vary a lot and are not guaranteed. This Xfinity example reduced the bill by $276 per year. Many outcomes are loyalty discounts, though legacy or misconfigured plans can produce larger reductions.

Identity verification is a non-trivial part of the system. When a provider requires an OTP, the agent pauses and the user enters the code. We’ve spent significant time optimizing that step to ensure users are actually present and able to complete verification when needed, since timing and proximity matter.

Some of the harder technical challenges:

• Handling messy call state transitions across IVR trees, transfers, silence, interruptions, and unexpected flows
• Enforcing guardrails so the agent does not make unintended commitments
• Navigating automated front-line systems, which often means AI interacting with AI before reaching retention
• Ensuring we get the OTP verification codes from users on time when they are required

Happy to answer questions
by ajainvivek | 2026-02-24 02:04:28+00:00
Hi HN, I built ReasonDB after spending 3 years building a knowledge intelligence layer at Brainfish (my company). We stitched together vector DBs, graph DBs, and custom RAG pipelines. The constant problem: when search returns the wrong documents, your AI gives wrong answers confidently. Debugging why embeddings didn't surface the right chunk is a black box – we'd fix one case and break three others.

ReasonDB takes a different approach. Instead of shredding documents into flat chunks and hoping cosine similarity finds the answer, it preserves document hierarchy as a tree and lets the LLM navigate through it – like a human scanning a table of contents and drilling into the right section.

How it works:
- Documents are ingested as hierarchical trees (headings, sections, subsections) with LLM-generated summaries at each node
- When you query, a 4-phase pipeline kicks in: BM25 narrows candidates → tree-grep filters by structure → LLM ranks by summary → parallel beam-search traversal extracts answers
- The LLM visits ~25 nodes out of millions instead of searching a flat vector space

It also has RQL, a SQL-like query language with SEARCH (BM25) and REASON (LLM) clauses:

SELECT * FROM contracts REASON 'What are the termination conditions?'

Built in Rust (redb, tantivy, axum, tokio). Single binary. ACID-compliant. Supports OpenAI, Anthropic, Gemini, Cohere and Open Source Models. Runs with one Docker command.

Would love feedback and criticism – especially from anyone who's fought the same RAG quality battles.
by halfcat | 2026-02-24 02:04:41+00:00
> it allows our margins to be higher and our speed of implementation to be faster

Faster than what? You will be faster than your previous self, just like all of your competitors. Where’s the net gain here? Even if you somehow managed to capture more value for yourself, you’ve stopped providing value to 5-10x that many employees who are no longer employed.

When costs approach zero on a large scale, margins do not increase. Low costs = you’re not paying anyone = your competitors aren’t paying anyone = your customers no longer have money = your revenue follows your costs straight to zero.

Companies that provide physical services can’t scale without hiring. A one-man “crew” isn’t putting a roof on a data center.

I want to be wrong. Tell me why you think any of this is wrong.
by ssl-3 | 2026-02-24 02:04:49+00:00
This process took two months, including re-appraisals of the process itself, and it isn't clear that the calendar on the wall was a motivator.

The next implementation doesn't have to happen in a vacuum. Now that it has been done once, a person can learn from it.

They can discard the parts that didn't work well straight away, and stick to only the parts of the process that have good merit.

We'll collectively improve our methods, as we tend to do, and the time required will get shorter with each iteration.
by AnimalMuppet | 2026-02-24 02:05:34+00:00
Tribes reproduce as the people who make up the tribe reproduce.

Values reproduce as the people who hold them reproduce, plus as others adopt those values, minus as those who hold those values drop them.

But the US was supposed to be a country where values mattered more than tribe. "We hold these truths to be self evident", and all that, and if you accepted the values, you belonged. That was an imperfect ideal, but it was the ideal until rather recently. I'm not sure to what degree it still is.