MurphyA/hacker-news huggingface dataset:
More tokens, less cost: why optimizing for token count is wrong
by nicola_alessi | 2026-03-10 18:20:13+00:00
I ran a controlled benchmark on AI coding agents (42 runs, FastAPI, Claude Sonnet 4.6) and found something that broke my mental model of LLM costs.
The setup: I built an MCP server that pre-indexes a codebase into a dependency graph and serves pre-ranked context to the agent in a single call, instead of letting the agent explore files on its own.
The expected result: less input context → lower cost. Straightforward.
The actual result: total tokens processed went UP 20% (23.4M vs 19.6M) while total cost went DOWN 58% ($6.89 vs $16.29).
The explanation is in how Anthropic prices tokens. There are three pricing tiers:

Output tokens: most expensive (3-5x input price)
Input tokens (cache miss): full price
Input tokens (cache hit): 90% discount

The agent with pre-indexed context processes more total tokens because the structured context payload is injected every turn. But the token MIX shifts dramatically:
Output tokens: 10,588 → 3,965 (-63%)
Cache read rate: 93.8% → 95.3%
Cache creation: 6.1% → 4.6%
Output tokens dominate the cost equation. When the agent receives 40K tokens of unfiltered context, it generates verbose orientation narration ("let me look at this file... I can see that..."). When it receives 8K tokens of graph-ranked context, it skips straight to the answer. 504 output tokens per task → 189.
The cache effect compounds this: structured, consistent context across turns hits the cache more reliably than ad-hoc file reads that change every turn. So the additional input tokens cost almost nothing (90% discount) while the output token reduction saves the most expensive tokens.
The general principle: with tiered token pricing, optimizing for total token count is wrong. You should optimize for token mix — push volume from expensive tiers (output, cache miss) to cheap tiers (cache hit). More total tokens can cost less if you shift the distribution.
This seems obvious in retrospect but I haven't seen it discussed much. Most context engineering work focuses on reducing input tokens. The bigger lever might be reducing output tokens by improving input signal-to-noise ratio — the model writes less when it doesn't have to think out loud about what it's reading.

The tool is vexp (https://vexp.dev) — local-first context engine, Rust + tree-sitter + SQLite. Free tier available.
by dlev_pika | 2026-03-10 18:20:22+00:00
A few days ago, after some very weird failed purchase attempts I made (payment couldn’t be validated or
Smth) I received an even weirder mail from Amazon saying they had detected suspicious activity, all my devices got logged out and I was forced to change my password. I did it, after verifying it was a legit email (even if it looked sketchy af, pure text, unstyled, but sender verified and confirmed with in-app behavior), and next I know all my orders and browsing history had disappeared - +15 yrs of history, done.

Over the next few days my account history came back, except purchases made Q1 2026. Those are still missing. There are a few substantial purchases I made that are nowhere to be found anymore.

I attributed this Iranian missiles hitting some of their infrastructure in EU, as it had been reported.

Now I am not sure if it was blast radius from missiles or AI mishaps. Lmao - couldn’t happen to a worse company…
by nxobject | 2026-03-10 18:20:27+00:00
There’s a lot of bold claims here that are wildly unfamiliar with me:

- What status do you think people with PhDs or who teach and do research have? (And do you think that having those beliefs is necessary to remain in academia?)

- Who are we learning that we’re supposed to be treating like fact, and singing the praises of? (I remember learning about, say, Hindley-Milner type inference in undergrad, but I didn’t think of it as “fact”, and nor did I have to write of its praises to pass my classes.)

- I wanted to become a mathematician, and my colleagues are currently statisticians that work on medical claims data from entire health systems. What does “replicate” mean in this case? Similarly, what does “replicate” mean in the context of industry, if a comparison is being set up here?
by WalterGR | 2026-03-10 18:20:28+00:00
Most landlines in the US these days are VoIP and my understanding is that modems work very poorly over VoIP. Before anyone invests in a modem - and in getting a land-line if they don’t have one - be sure to do your research.

Can anyone comment on how well modems work over long-haul connections these days? Even if you have plain ol’ copper wiring to your local telephone company, it’s not gonna be copper wire the whole way.
by temp8830 | 2026-03-10 18:20:29+00:00
Sure - every country has their own angle. And if you don't seek out a varied media diet - you'll only get one side.

If you are curious, open up Wikipedia and check out what year did Lviv get attached to Ukraine, who attached it, and how. Spoiler: somehow Comrade Stalin is a good guy when it comes to taking from the Poles and giving to Ukraine. The mental gymnastics some people perform really are quite amazing.

Ever wonder how those borders got internationally recognized? Seems to me that it had something to do with the world fearing Stalin just enough to let him draw that particular border. War never changes.
by staplung | 2026-03-10 18:20:30+00:00
I don't think it would work because the accelerometer updates are at too low a frequency. Apple's developer info says:

```
Before you start the delivery of accelerometer updates, specify an update frequency by assigning a value to the accelerometerUpdateInterval property. The maximum frequency at which you can request updates is hardware-dependent but is usually at least 100 Hz.

```

100Hz is way too slow. Presumably some devices go higher but according to the article the peak signal is in the 3kHz to 15kHz range.
by cperciva | 2026-03-10 18:20:44+00:00
14.4 is a maintenance release. If you're installing FreeBSD today, use 15.0

This is not the recommendation of the FreeBSD project. (I would know, because I'm the person in the project who makes that recommendation where appropriate.)

Once X.1-RELEASE ships, (X-1).* is considered "legacy" and we recommend that it is used primarily for maintaining existing systems and that new systems are deployed with the newer major version. But at when it comes to 14.4 vs 15.0 we're not there yet; .0 releases are always a bit bumpy and it's very much a judgement call at this point about how much risk people want to take.
by Imustaskforhelp | 2026-03-10 18:20:49+00:00
I was writing my initial comment and I had no mention to the voting behaviour until I accidentally reloaded or something to find the upvote rise by a decent amount. Then I got suspicious and then I reloaded again to see like in 20seconds or < 1 minute and saw the vote rise so much (read my other comment)

I was writing the comment at time of 18 upvotes and then it went to 24 upvote all of a sudden that I had gone suspicious.

see at 2026-03-10T17:38-39:00Z timeframe within this particular graph(0)

(0):https://news.social-protocols.org/stats?id=47326101
by lovich | 2026-03-10 18:20:50+00:00
I think it’s deeper than that because it’s affected more industries than software and already started pre AI.

American corporate culture has decided that training costs are someone else’s problem. Since every corporation acts this way it means all training costs have been pushed onto the labor market. Combine that with the past few decades of “oops, looks like you picked the wrong career that took years of learning and/or 10 to 100s of thousands of dollars to acquire but we’ve obsoleted that field” and new entrants into the labor market are just choosing not to join.

Take trucking for example. For the past decade I’ve heard logistics companies bemoan the lack of CDL holders, while simultaneously gleefully talk about how the moment self driving is figured out they are going to replace all of them.

We’re going to be outpaced by countries like China at some point because we’re doing the industrial equivalent of eating our seed corn and there is seemingly no will to slow that trend down, much less reverse it.
by emotixco | 2026-03-10 18:21:19+00:00
Every Claude Code skills/commands collection we found is developer-focused — code review, testing, git workflows. We needed the same convenience for the non-code parts of building a startup.

This is a set of 12 slash commands (markdown files) that you drop into your .claude/commands/ folder:

/validate-idea — scores on 7 dimensions (problem severity, market size, WTP, competition gap, distribution, timing, founder fit), gives build/pivot/kill verdict
/competitor-matrix — identifies 5-8 competitors, builds feature comparison table, finds positioning gaps
/pricing-strategy — evaluates 6 models, designs 3 tiers, checks unit economics, applies pricing psychology
/pitch-deck — 12-slide outline with specific content per slide
/go-to-market — pre-launch audience building → launch day platforms → 90-day channel prioritization
Plus 7 more for user personas, MVP scoping, landing page copy, user interviews, fundraising prep, metrics, and email sequences.

Each skill is intentionally opinionated — "kill this feature" not "consider deprioritizing." Every output has a word limit because brevity forces clarity.

Built at Emotix (https://emotix.co) — we run AI agents for startup research. These are the frameworks we use internally, packaged as reusable commands.

No dependencies, no npm — just copy markdown files. MIT licensed.
by lapcat | 2026-03-10 18:21:28+00:00
> what alternative do you propose?

Your question is ambigious. Are you asking what a different system would look like, or how we would get there?

As for the first question, there are many obvious ways to improve the system. Here are some suggestions: abolish the electoral college, abolish the Presidential veto and pardon, abolish the Senate, abolish lifetime Supreme Court terms, add term limits for Congress, publicly fund political campaigns and outlaw campaign contributions as illegal bribery, allow public recall campaigns against the President, Congress, and Supreme Court, etc.

As for the second question: "The biggest problem with the US is that we haven't had a political revolution in 250 years."
by i_cannot_hack | 2026-03-10 18:21:32+00:00
Your characterization of the event as a simple reminder to follow established best practices is directly contradicted by the briefing note of the meeting, which specifically mentions a lack of best practices related to AI. Which makes me skeptical of your assessment of the situation in general.

> Under “contributing factors” the note included “novel GenAI usage for which best practices and safeguards are not yet fully established”.
by vladdoster | 2026-03-10 18:21:35+00:00
Location: Nashville, TN
Remote: true
Willing to relocate: boston || nashville
Technologies: Python, Django, IaC, Terraform, Golang, CI/CD, Azure/AWS, {ba,z}sh, Lua, Springboot,
Redis, Docker, Open Service Broker, {,non}relational & vector dbs, shared services, SOA
Email: mvdoster@gmail.com

resume: https://linkedin.vdoster.com && http://github.com/vladdoster

sr. cloud software engineer @ Mastercard (5 years)

Designed and built Platform-as-a-Service for microservice workloads running on Azure and AWS
to migrate on-prem workloads to the cloud. The platform operates globally, allowing teams to
deploy to several Azure-backed regions worldwide. Helped plan and create regional landing zones
in Azure for application teams wanting to perform globally. Designed platform components using
Terraform, Go, and Node; developed support tooling using Bash, Python, and Azure CLI. De-risk the
platform by addressing security vulnerabilities and ensuring the platform is PCI compliant.

api/devops software engineer @ Harvard Medical School (2 years)

Worked as part of the DevOps team to manage a 15k core CentOS HPC cluster. Designed and implemented
Python-based security scanning pipeline to securely deploy & run Apptainer images via SLURM.
Coordinated cross-team emergency patching eﬀorts. Collaborated with researchers and engineers across
3-letter institutions to deliver secure research infrastructure. Built CI/CD Pipelines with GitHub, Jenkins,
to automate code builds, testing, and deployments. Wrote Puppet modules to manage configuration of HPC fleet.
Wrote custom Puppet module & Python scripts to automatically remediate Tenable findings.

full-stack software engineer @ Global Prior Art (3 years)

Used Django, Celery, Selenium grid, and AWS API Gateway for IP rotation to scrape USPTO patent PDFs,
apply CV for data extraction, and generate reports with relevant claims, saving employees 4-5 hours daily.
Wrote E2E black-box/fuzzing unit tests. Automated on-premise deployment via Github Actions and Ansible.

maintainer @ Zinit (5 years)

Develop and maintain a zsh plugin manager on Github with 4k stars. Implemented unit tests,
containerization, bug fixes, and new features.
See: https://github.com/zdharma-continuum/zinit

contributor @ Open-source documentation (5 years)

Contributed hundreds of documentation corrections and enhancements to 400+ open source projects.
by mindslight | 2026-03-10 18:21:41+00:00
Word use is important.

Please explain how the trumpist movement significantly differs from most points of Umberto Eco's Ur-Fascism. Because in my estimation, the word is entirely appropriate for what we're facing and people are shouting it down because they don't like the uncomfortable truth.

I'm open to changing my mind, especially if there is a better term that more accurately describes what we're facing. Because the dynamic isn't merely "crumbling postwar liberal democratic order", but rather a particular overly-simplistic reaction to that crumbling.
by calebbertumen | 2026-03-10 18:22:35+00:00
I keep running into the same problem: I read a message, think I’ll reply later, and then forget for weeks. Sometimes I also realize I haven’t talked to someone important in months and have no idea how that happened.

I’m exploring an app idea called Nudge that would gently remind you to check in with specific people if it’s been a while.

I’m trying to validate whether this is a real problem worth building for. Waitlist here: https://forms.gle/pHMABTsbctLXZPZj6

Would you use something like this, or do existing tools already solve it well?
by armchairhacker | 2026-03-10 18:22:43+00:00
There are millions of asset flips, but the top indie games have never been better. It’s hard for indie developers because there’s so much competition: you need to heavily promote a quality game only because there are so many other quality games.

Likewise these tools have enabled many more people to create vibe-coded slop, and may lead to more quality software (making it harder to stand out without marketing), but the best software will only get better.
by surgical_fire | 2026-03-10 18:22:51+00:00
Oh believe me, I am not defending the prick.

We are in a thread of Amazon holding engineering meetings after AI-related outages after laying off 30k people.

If anything this highlights gross incompetence of a moronic leadership. It should be them being laid off.

If overhiring indeed happened, it is also a failure of leadership. Hiring too many people and then firing a bunch of people causes friction, loss of knowledge, decreased morale, etc.
by alexbuiko | 2026-03-10 18:22:52+00:00
A decade since AlphaGo, and we’re still just scratching the surface of model alignment and efficiency. While DeepMind proved that AI can master intuition, we are now looking at the other side: the physical cost of that intuition.

I’m currently preparing a 'match' against KataGo, but not by out-calculating it in the traditional sense. We are using SDAG [https://github.com/alexbuiko-sketch/SDAG-Standard] to monitor routing entropy and hardware stress during high-load inference. The goal is to see if we can identify 'hallucination paths' through hardware-level signals before they manifest in the game logic. It feels like the next frontier of auditing: treating LLMs/RL agents not just as math, but as physical systems with detectable stress patterns.
by lemonwaterlime | 2026-03-10 18:23:03+00:00
I understand it is an ideological project. My point is that given their intent, there are things they should do to make their case. They should provide the evidence in the README etc.

If they are correct and things must be done, they aren’t providing the evidence. That’s not the same as saying there’s no evidence or reason to take this stance. Do you see the distinction I am making?
by bsimpson | 2026-03-10 18:23:32+00:00
I started out using Karabiner, but then when Apple added support to natively rebind Escape, it made that an easy choice.

Works great in Sublime. Have this request open for Ghostty:

https://github.com/ghostty-org/ghostty/discussions/10499

On Linux, there's xremap. It lets you remap key chords on a per-app basis. I'm using it to use Apple-style Command shortcuts with Chrome for Linux:

https://github.com/appsforartists/device-config/blob/master/...
by nickprotop | 2026-03-10 18:23:39+00:00
I built a full WinUI app with no visual editor, just XAML and code. The layout was entirely in my head. Now I do the same with terminal UIs on Linux, pure code with fluent builders.
Once you internalize the layout model, a visual editor mostly slows you down. Code-first gives you full control, clean diffs, and composability.
That said, for complex layouts you still need to run and visually review, no one gets nested grids pixel-perfect from memory alone.
by a456463 | 2026-03-10 18:23:50+00:00
Laws and lawmakers just concern themselves with making broad "laws" with little regard to specificity and applicability. California, Colorado and Illinois mandate OS "providers" to generate a signal. It is a copy pasted bill with little grounding in reality but a lawmaker is not going to say no "protecting children".

Pushed by AVPA - a group of companies standing to profit from this: LexisNexis, some Thiel corp, etc.
by perfmode | 2026-03-10 18:23:54+00:00
Humans are notoriously bad at formal logic. The Wason selection task is the classic example: most people fail a simple conditional reasoning problem unless it’s dressed up in familiar social context, like catching cheaters. That looks a lot more like pattern matching than rule application.

Kahneman’s whole framework points the same direction. Most of what people call “reasoning” is fast, associative, pattern-based. The slow, deliberate, step-by-step stuff is effortful and error-prone, and people avoid it when they can. And even when they do engage it, they’re often confabulating a logical-sounding justification for a conclusion they already reached by other means.

So maybe the honest answer is: the gap between what LLMs do and what most humans do most of the time might be smaller than people assume. The story that humans have access to some pure deductive engine and LLMs are just faking it with statistics might be flattering to humans more than it’s accurate.

Where I’d still flag a possible difference is something like adaptability. A person can learn a totally new formal system and start applying its rules, even if clumsily. Whether LLMs can genuinely do that outside their training distribution or just interpolate convincingly is still an open question. But then again, how often do humans actually reason outside their own “training distribution”? Most human insight happens within well-practiced domains.
by kotaKat | 2026-03-10 18:24:05+00:00
“In 2021, the research firm IPVM independently tested Flock's LPR cameras, concluding in a report that it misidentified which state a license plate was from for around 1 in 10 reads, and that the system regularly misclassified license plate state, vehicle type, and make. IPVM said that Flock subsequently blocked it from purchasing its cameras for testing.”

Whatcha got to hide, Garrett?
by gnabgib | 2026-03-10 18:24:13+00:00
You're over doing the self-promotion (this is the 7th time you've submitted vexp), share something with us you're curious about that you didn't build.

> Please don't use HN primarily for promotion. It's ok to post your own stuff part of the time, but the primary use of the site should be for curiosity.

https://news.ycombinator.com/newsguidelines.html
by harperlee | 2026-03-10 18:24:21+00:00
Two handwavey ideas upon reading this:

- Even for billion-parameter theories, a small amount of vectors might dominate the behaviour. A coordinate shift approach (PCA) might surface new concepts that enable us to model that phenomenon. "A change in perspective is worth 80 IQ points", said Alan Kay.

- There is analogue of how we come up with cognitive metaphors of the mind ("our models of the mind resemble our latest technology (abacus, mechanisms, computer, neural network)"), to be applied to other complicated areas of reality.
by laetus-app | 2026-03-10 18:24:28+00:00
That makes sense. Using a depth map first sounds almost inevitable for keeping the repetition stable enough for the visual system to lock onto it.

What I always find interesting with these images is how sensitive the brain is to those horizontal disparities. Even tiny shifts create a surprisingly strong sense of structure once the eyes fuse the patterns. It really highlights how much of “seeing” depth is reconstruction rather than direct perception.

Do you generate the depth maps manually, or are they derived procedurally from some model or scene description?
by ragall | 2026-03-10 18:24:29+00:00
Nah. Here's a counter example: the TUIs that IBM wrote for many old store chains like Home Depot. They're at least an order of magnitude faster to operate for cashiers compared to web UIs but they're somewhat slow to start due to the caching and self-checks they do. This obsession with quick boot is more of a personal preference you have than a necessity.
by Insanity | 2026-03-10 18:24:51+00:00
That's an interesting idea. But IMO the real 'token saver' isn't in the language keywords but it's in the naming of things like variables, classes, etc.

There are languages that are already pretty sparse with keywords. e.g in Go you can write 'func main() string', no need to define that it's public, or static etc. So combining a less verbose language with 'codegolfing' the variables might be enough.
by curuinor | 2026-03-10 18:25:11+00:00
Connectionist models have lots of theory by theoreticians explicitly pissed off about Chomsky's assertion that there is an inbuilt ability for language. Jay McClelland's office had a little corkboard thingy with Chomsky mockery on the side, for example. Putting forth even the implicature that the present direct descendants are intellectual descendants of Chomsky is like saying Protestants are intellectual descendants of Pope Leo X.
by WorldMaker | 2026-03-10 18:25:26+00:00
I believe Vancouver is west enough in its time zone that Daylight time is going to be closer to Solar Noon in Vancouver (plus about 15 minutes? I haven't done the exact math) than Standard time was (minus about 45 minutes?). Vancouver is the economic heart of British Columbia and near enough to the centroid of BC's population that BC may have made the best choice they could for solar accuracy for the majority of the population.
by insane_dreamer | 2026-03-10 18:25:48+00:00
Why can I say? Sometimes the only way to really learn about a country esp one with such tight control over information is to live there a decent amount of time. And since not many investigative journalists are doing that in China any more (China’s not likely to let them stay if they’re reporting the truth), it’s tough. If you really want to know, you may have to go find out for yourself.