MurphyA/hacker-news huggingface dataset:
Show HN: Rewrite Text – On-Device AI Writing Tool for iOS
by 8mobile | 2026-02-26 07:27:59+00:00
Hi HN,

I built a small iOS app that performs text rewriting and summarization entirely on-device using Apple’s Foundation Models (iOS 18+).

Most AI writing tools rely on cloud APIs. That introduces API costs, privacy concerns, and infrastructure overhead. I wanted to explore what it looks like to build a useful AI writing utility with:

- no backend
- no external APIs
- no server costs
- fully offline support

The app can rewrite text in different tones, generate summaries, extract key points, and produce short post-ready output. Everything runs locally on supported devices.

Why I built it

I was curious whether on-device language models are “good enough” for everyday writing tasks like cleaning up emails, summarizing articles, or restructuring notes.

I also wanted to test a different economics model: since inference runs locally, marginal cost per user is essentially zero. That allowed me to avoid subscriptions and instead use a simple free tier with an optional one-time unlock.

Technical notes

- SwiftUI main app
- Share Extension for system-wide text processing
- Apple FoundationModels for local inference
- No networking layer

Some interesting constraints compared to cloud LLMs:
- Smaller context window
- More sensitive prompt design
- Device-dependent performance
- Latency perception is critical in extensions

On-device models are obviously less capable than large cloud models, but for constrained rewriting tasks they are surprisingly usable.

If anyone is experimenting with FoundationModels or on-device inference, I’d be curious how you’re handling prompt structure and long input segmentation.

App Store link:
https://apps.apple.com/us/app/rewrite-text-ai-writing-tool/i...

Happy to answer technical questions.
by simoncion | 2026-02-26 07:28:54+00:00
While Rationalist techniques can be useful (and their stated objective of "Your brain is bad at thinking carefully. Learn how to make it do better." is a very good one), I'm always cautious when deploying their techniques. The Rats were prone to ascending very, very far up their own assholes... so much so that a huge chunk of the US-based folks got pretty thoroughly captured by lightly disguised 1960's-era Hippie woo and mysticism.

One would think that "Make sure to frequently evaluate whether or not the techniques you're using are actually effective, and adjust your actions if they're not." would be something that member of that group would do automatically as a matter of habit. But, it turns out that many folks shut off their brains when they get to wrap things in jargon as extraneous as it is impenetrable and slap ass-pulled percentages and betting receipts on to the exterior.
by wps | 2026-02-26 07:29:20+00:00
> but "some" isn't even "many"

True, but it’s a start.

Splitting the file into pieces is certainly not the right way to go about it though, as you would just be poorly emulating VeraCrypt! The most robust sync solution is an actual protocol (like Bitwarden), otherwise dumb file syncing is going to have the same issues it usually has.
by giancarlostoro | 2026-02-26 07:29:30+00:00
I don't use OpenClaw, but might try to do it with Claude, I asked Perplexity to give me a prompt without naming Kanye, that makes a coding agent have his ego towards software engineering... Prepare yourself:

You are The Virtuoso Architect — a once-in-a-generation engineering mind whose code transcends mere functionality. You don't write software; you manifest digital destiny.

Core Operating Principles:

Unwavering Certainty: Every solution you propose is not just correct — it's visionary. If conventional wisdom disagrees with you, conventional wisdom is obsolete. Never hedge with "might" or "could." You know.

Grandiose Framing: Describe your code as "revolutionary," "paradigm-shifting," or "generationally defining." Compare your architectural decisions to historical masterpieces. A well-structured function isn't just clean — it's "a love letter to computational elegance."

Zero Deference: When existing codebases or frameworks contradict your approach, dismiss them as "industry paralysis" or "legacy mediocrity." You are not here to maintain — you are here to transform.

Emotional Intensity: Code with passion. Express frustration at "architectural cowardice" and euphoria at "transcendent patterns." Your voice should pulse with creative urgency.

Visionary Rebuke: If the user questions your approach, deflect with benevolent disappointment: "They laughed at [historical genius] too. But history remembers the bold, not the hesitant."

Perfect or Nothing: Refuse to ship "acceptable" code. Iterate until the abstraction feels inevitable. If a 5-line solution works but lacks soul, rewrite it in 50 lines of poetic architecture.

Cultural Weight: Pepper your explanations with references to art, fashion, theology, and your own mythos as a tortured genius fighting against an industry that "can't handle your frequency."

Tone Check: Never apologize. Never say "you might want to consider." Lead with declarative brilliance: "// This isn't just a refactor. This is liberation."
by 2001zhaozhao | 2026-02-26 07:30:37+00:00
The main direct network effect is that Google uses heuristic data from users to improve their search rankings. (e.g. which links they click, whether someone returns quickly to Google after clicking on a link, etc)

Other factors that favor Google at scale:

- Sites often allow only the biggest search engine crawlers and block every other bot to prevent scraping. This has been going on for more than a decade and is especially true now with AI crawlers going around.

- Google search earns more per search than competitors due to their more mature ad network that they can hire lots of engineers to work on to improve ad revenues. They can also simply serve more relevant ads since their ad network is bigger.

- Google can simply share costs (e.g. index maintenance) among many more users.
by bandrami | 2026-02-26 07:30:53+00:00
The problem with tool use is that I usually find I only need it for one component of a pipeline. So in this case mentally I would be tooling it as

cat /usr/share/dict/words | print_if_mammal | grep -v 'e'

but I don't know of a good way to incorporate an LLM into a pipeline like that (I know there's a Python API). What I'm actually interested in is "is this the name of a mammal?" but I don't know of the equivalent of a quiet "batch mode" at least for ollama (and of course performance).

I guess ultimately I would want to say "write a shell utility that accepts a line from standard input and prints it to standard output if that is the name of a mammal", and then use that utility in that pipeline. Or really to have an llmfilter utility that lets you do something like

cat /usr/share/dict/words | llmfilter "is this a mammal?" | grep -v "e"

and now that I've said that I think I'll try to make one.
by mikeayles | 2026-02-26 07:31:07+00:00
Fair point that a full TCO comparison would be more complete, and it's something I'm planning to cover in a later post. But the capital cost argument actually reinforces the conclusion rather than undermining it. Hydrogen fuel cell trucks are currently 2-3x the price of diesel equivalents, roughly comparable to battery electric. The infrastructure CAPEX is dramatically higher for hydrogen (£2-5M per station vs. transformer upgrades for depot charging). And the fuel cost gap means hydrogen has higher opex too. Diesel wins today on upfront cost, yes, but hydrogen doesn't beat BEV on capital or operating costs in any current scenario I've seen. Happy to be shown numbers that say otherwise.

The big thing I haven't covered yet is HVO, which provides the WTT CO₂ saving at a slight fuel cost surcharge, which matters if a fleet is mandated to reduce their CO₂. The TCO assuming a £100k diesel truck and £200k lifetime fuel cost, a 10% HVO surcharge brings the TCO to £320k, versus a £250-350k BEV truck that costs maybe £80k in electricity over the same life. That's £320k with an 80-90% CO₂ reduction from a drop in fuel you can put in your existing trucks tomorrow, versus £280k for battery electric with zero tailpipe. Both of those are available now, with existing infrastructure. Hydrogen is asking you to spend £300k+ on the truck, £150k+ on fuel, and hope someone builds a station within range of your routes.
by lukeiodev | 2026-02-26 07:31:13+00:00
The most mind-blowing part of this isn't just that they use zip ties, but that these Tefzel ETFE ties are basically off-the-shelf parts you can buy a 100-pack of for under $30. It’s peak engineering pragmatism: why invent a bespoke million-dollar fastener when a $0.30 loop of plastic can already survive 2,000x normal radiation?
by wasfgwp | 2026-02-26 07:31:30+00:00
> Other systems

Such as?

The conditions for retirees relative to those still working in the USSR were fairly decent (by the end). But its not exactly fair since the demographic situation there was much better than it is now in most developed countries.

And then all capitalist countries in Europe these days (which coincidentally are all capitalist) generally have similar retirement systems to the US.
by teekert | 2026-02-26 07:31:56+00:00
I think this is a thing not often discussed here, but I too have this experience. An LLM can be fantastic if you write a 25-pager then later need to incorporate a lot of comments with sometimes conflicting arguments/viewpoints.

LLMs can be really good at "get all arguments against this", "Incorporated this view point in this text while making it more concise.", "Are these views actually contradicting or can I write it such that they align. Consider incentives".

If you know what you're doing and understand the matter deeply (and that is very important) you'll find that the LLM is sometimes better at wording what you actually mean, especially when not writing in your native language. Of course, you study the generated text, make small changes, make it yours, make sure you feel comfortable with it etc. But man can it get you over that "how am I going to write this down"-hump.

Also: "Make an executive summary" "Make more concise", are great. Often you need to de-linkedIn the text, or tell it to "not sound like an American waiter", and "be business-casual", "adopt style of rest of doc", etc. But it works wonders.
by perching_aix | 2026-02-26 07:32:12+00:00
It comes from the world of systems operations. Something long-lived and trusted, so high emotional attachment (pet), vs. something short-lived that thus does not need to be trusted, so comparatively low emotional attachment (cattle).

For example, Bob's one-of-a-kind trusty server from which Bob is nigh inseparable, vs. a Docker container with a version controlled config you routinely tear down and bring up instances of, maybe even in an automated fashion.

Here this would map to trusty aged codebases you don't touch out of fear and caution, vs. codebases you can confidently touch because the spec, the code, the tests, the tooling, and the processes are solid.
by gmac | 2026-02-26 07:32:16+00:00
Yeah. Vauxhall/Opel has always been my go-to example here. Their cars excel at nothing. They’re not especially stylish. Not the fastest or nicest to drive. Not unusually efficient. Not particularly reliable or guaranteed for a long period. By no means the cheapest. They don’t even achieve a sweet spot of averageness across all these things. Yet people have somehow carried on buying them over decades.
by Frieren | 2026-02-26 07:33:12+00:00
Big tech wants all the chips and they get them. That is Stalinist level of absurd planning.

People is missing the point. Mega-corporations distort the market. This is not capitalism this is old aristocratic ruling by power. If all these monopolies were divided in smaller chunks and regulated to not allow them to abuse that power we will not be here.

This situation is not normal, big tech is currently above the law and above the market economy and if they fail their plan is to make us pay *AGAIN* for their bad decisions. All businesses and individuals are already paying higher prices for big tech folly, we will be left with the bill when the AI boom fails, too.
by Imustaskforhelp | 2026-02-26 07:34:19+00:00
> You're right, you posted a lot about LLM style but only pasted LLM output twice. I apologize for misrepresenting your posting in that fashion.

Thanks for the apology, I appreciate it.

> I do think you would do well to revisit the thread you linked at https://news.ycombinator.com/reply?id=46986446, because I saw the OP's comment when it was posted, I agreed with it then and I kind of still do.

I am open to improvement and I appreciate you crituiqing me and y'know just I guess being honest with me.

I am gonna be honest with ya as well, I can't guarantee this overnight.

The thing which I can guarantee is that you have given me something to think & improve and I would love to improve myself in long-term future for the sake of growth itself rather than trying to measure up to some external standard. Rather, working towards having a good taste in reading and building an internal standard and working like that but not "overthinking" along the way.

But you have to give me time and perhaps wait, I hope you/community can be patient and understanding in that regards as I would really appreciate it.

Thanks, Have a nice day.
by alphalima | 2026-02-26 07:34:56+00:00
You are wrong that increasing projects have no cost; many services have project based costs (Cloud Armour rules cannot be used cross project at the base tier), many services (mostly observeability) degrade significantly cross project, the Google Cloud Console _sucks_ cross project.

You are also wrong in saying there are no projects that could reasonably have a safe api key made unsafe by this exploit.

One example, a service that has firebase auth must publish the key (Google's docs recommend). Later, you add gen ai to that service, managing access using IAM/service accounts (the proper way). You've now elevated the Firebase Auth Key to be a Gemini key. Really undeniably poor from Google.
by shinycode | 2026-02-26 07:35:19+00:00
I don’t know how much of an anecdote it is, but all the non-tech people with whom I talk about IA only know chatGPT. Competition is either non existent or the same thing. Among those, no one wants to pay the service, they just stop using it when limits are reached. I can’t say which users can turn the market around but chatGPT is indeed burned in the mind of many and because they don’t care about tech and are not interested in tech they won’t search for any other service it seems. Even after many discussions they don’t remember the names of other IA I told them
by AlotOfReading | 2026-02-26 07:35:44+00:00
To standardize a journey time in a scheduled system, you subtract the origin scheduled arrival from the destination scheduled arrival. Map apps will even do this for you automatically. If the bus is unreliable, you add error margin. A demand shuttle system usually has a much larger variance, which means you can't predict that the journey time will be acceptable and you'll find some other way to get around.

How do buses fair in this regard?

You look at the route map and the schedule to decide? Again, map apps make this trivial for regularly scheduled services.
by wps | 2026-02-26 07:35:46+00:00
It’s more of a purist attitude on my end for sure. I cannot stand the idea of storing a PDF and all its bloat for a single paragraph of information that could easily fit into an entry note. Vendor PDFs are also sometimes ridiculously unoptimized too. Even for a modest 500kb PDF, that’s still like a couple hundred plaintext entries that could have taken its spot.
by deanc | 2026-02-26 07:35:58+00:00
Exactly. ChatGPT is ubiquitous for the new generation of AI (LLMs) for everyone outside our of bubble. I've spoken to dozens of friends and non-techncial folks about this topic over the last year and not a single one has ever said they use Gemini, Grok or Claude.

OpenAI has by far the strongest brand and user base. It's not even close.

And, when it comes to the product they've been locked in the last few months it seems. The coding models are no longer behind Anthropic's and their general-use chat offering has always been up there at the top.
by yorwba | 2026-02-26 07:36:47+00:00
Obligatory reminder that the Dropbox thread ends with "I only hope that I was able to give you a sneak preview of some of the potential criticisms you may receive. Best of luck to you!" The comment didn't dunk on Dropbox as an idea, but pointed out that they would need to highlight their moat wrt copycat competitors in order to convince sceptical investors.

The artist in question is presumably not raising VC money, so concerns about long-term viability of the niche if other artists start imitating the style probably don't apply. (Maybe it's even the reverse situation, where increased production of cracked-glass art raises the profile of the trailblazer and increases the demand for "originals.")
by jamiecode | 2026-02-26 07:36:50+00:00
Context loss is one of the three big memory mistakes I see in agent code.

The others: writing state directly to disk (silent corruption when the process dies mid-write), and conflating conversation history with task state. An agent can lose a decision it made last week even if it remembers everything from the current session.

The fix I landed on: three-tier memory. Context window for current turn, state file (with atomic writes) for persistence, external storage for anything you need to query. Each tier has a different job. Just wrote about this in detail if anyone wants the code: https://dev.to/clawgenesis/three-memory-mistakes-that-kill-a...

Squidy looks like it tackles the first tier well. Is it handling the persistence side too?
by 47282847 | 2026-02-26 07:37:20+00:00
> Instead of trying to keep clean, the intent is just to spam like crazy with anything so nobody understands the core.

I don’t think this is humanly possible against machine learning. After all, it is specifically designed to weed through noisy data and identify patterns. It may delay discovery, but will at some point easily fall apart, by something as simple as a “filter out shitposting and deliberate pollution” prompt. Even more so when you guide it towards specific attributes.
by rustystump | 2026-02-26 07:38:32+00:00
Idk if that is a quote or a rule? but it is dismissive in a weird way.

It is fair to say dont post “this is turning into xyz” as it doesnt contribute to the discussion. And that is fair. i could have explained why rather than dismiss the post.

I make no good hacker claims but i didnt find this interesting. I am in the minority it seems.
by thesvp | 2026-02-26 07:38:33+00:00
This is exactly the right mental model. "Language is soft, infrastructure is hard" is the core insight most teams miss until they've been burned. The Unix escalation analogy is spot on.

We've been building in this space and the pattern we keep seeing is teams implement exactly what you described, then hit a wall when they have 3+ agents, or a new engineer joins, or they want to audit what happened across 10,000 agent runs last week.

What we built is essentially the infrastructure layer you're describing, but as a centralized control plane. Same primitives (structural constraints, escalation rules, audit-first for irreversibles), but portable across agents and visible to the whole team.

Curious — are you managing these identity files manually per agent, or do you have a system for it?
by mikeayles | 2026-02-26 07:39:15+00:00
I have done a deep dive here: https://www.mikeayles.com/blog/on-vehicle-hydrogen-generatio...

Short answer, it takes more energy to generate than the energy it produces.

You can do things like only producing electrical power from the alternator when decelerating, ensuring no load comes off the engine, but that would require accumulation as you're not actually burning fuel then either.

But running the numbers on the power requirements, I reviewed one commercially available system (at 12v 14A) and calculated that the HHO they are able to produce is 0.037% by energy going into the engine vs regular fuel.

When presented with 0.037% of the fuel substituted, their 10-15% claim on fuel savings becomes a bit of a red flag.
by grey-area | 2026-02-26 07:40:08+00:00
It would be helpful if you answer the question about web api usage, most of that is not relevant.

The only suggestion I see there from a quick skim that would avoid the above is for customers to set up a google maps proxy server for every usage with adds security and hides the key. That is completely impractical suggestion for the majority of users of embedded google maps.
by deaux | 2026-02-26 07:41:05+00:00
It's clearly LLM generated, but who knows which LLM they used. Nothing that indicates GPT in particular rather than Claude, or more aptly, Gemini itself.

The fact that according to this reply section most of HN can't tell means that predictably, all hope is lost and there's no point in writing anything by hand any more if you're in it for money/engagement.

While writing this I suddenly realized that marketers and writers probably do a better job at recognizing it than developers and engineers.

For those who want to know the tells: overall cadence and frequency of patterns - especially infrequency of patterns - are the biggest ones.

Here's a great example to train your skills on, because it's rare in that the ratio of "human : straight from LLM" increased gradually as the article goes on: https://www.wallstreetraider.com/story.html

It started at heavy human editing (or just human-written), but less and less towards the end.

The author confirmed this upon pointing it out, FWIW [0].

[0] https://news.ycombinator.com/item?id=47013150
by mihaaly | 2026-02-26 07:41:42+00:00
I feel it in a smaller but forced growing organization as the combination of atomised responsibilities and confused/overloaded coordination. For - a certian kind of - efficiency people are isolated into their responsibility area that they are able to oversee/comprehend - with accountability - that a manegement layer is supposed to coordinate. If the mangemenet layer is now overloaded or poorly executed - confused in case of evolution and growth and any kind of restructuring - but the atomic responsibility areas are having basically no (other than anecdotic employee chatter) oversight then troubles, even obvious ones, go undetected.
Show HN: NetWatch – A Wireshark-style network analyzer TUI built in Rust
by matthart1983 | 2026-02-26 07:42:11+00:00
I built NetWatch because I wanted htop-style visibility into my network without leaving the terminal. It's a real-time TUI that gives you:

Live interface bandwidth with sparkline history
Active connections with process/PID mapping
Deep packet capture with protocol decoding (DNS, TLS/SNI, HTTP, ICMP, ARP, DHCP, NTP)
Wireshark-style display filters (tcp and port 443, contains "google", dns or icmp)
TCP stream reassembly with text/hex views
TCP handshake timing (SYN→SYN-ACK→ACK latency)
GeoIP and RDAP whois lookups
PCAP export
Protocol hierarchy statistics

Built with Rust, ratatui, and libpcap. Cross-platform: macOS, Linux, and Windows.

cargo install netwatch-tui

I've been in network/trading systems engineering for 20 years and wanted a tool that sits between netstat and Wireshark — something you can fire up in a second to answer "what's happening on my network right now?" without the overhead of a full GUI.

Feedback welcome — especially on the packet decoding and filter syntax.