MurphyA/hacker-news huggingface dataset:
Ask HN: Using OpenClaw for marketing: worth it or overhyped?
by starfun | 2026-03-02 19:26:06+00:00
OpenClaw users: if you’re using it to run your marketing, how’s it been in real life? Has it genuinely reduced your effort running your social account and finding users? or are you still spending about the same time?

I've been spending the last three months building a growth tool for solo founders. When OpenClaw came out, it was hard not to wonder if our value just vanished, especially for technical founders who can wire workflows together.

After watching how people talk about it, I think there's still a gap, but I'd love to hear other founders' takes. Here's my argument:

- A lot of first-time founders struggle with marketing because they don’t know what to do, what to look at, or what good looks like. The basics (what signals matter at their stage, what to check daily vs weekly, how to tell signal from noise) aren’t obvious when you’ve never done marketing before.
- Agents can do a lot of work, but they don’t automatically create a sensible operating system unless you already know what to ask for.
- There’s another layer too: positioning usually doesn’t come from reading docs. It comes from back-and-forth conversation where someone keeps pushing until the founder finally shares the real product nuance they’ve been circling. AI can read everything you've written, but it still can't reliably extract what you haven't told it yet.

Questions for people using OpenClaw:

- Does it actually replace doing marketing end-to-end for you?
- Did it bring real results (users, leads, replies, conversions)?
- If it didn't meet your expectations, where did it fall short?

For context, I'm building https://auragtm.com. Would love to hear from founders who are actually using OpenClaw for marketing.
by solomonb | 2026-03-02 19:26:08+00:00
> Haskell is great, for what it's worth, but as with any language you have to reign in the AI's use of excessive verbosity. It will stack abstractions to the moon even for simple projects, and haskell's strengths for humans in this regard are weaknesses for AI - different weaknesses than other languages, but still, TANSTAAFL

I haven't had this problem with Opus 4.5+ and Haskell. In fact, I get the opposite problem and often wish it was more capable of using abstractions.
by just6979 | 2026-03-02 19:26:52+00:00
Then those "upgrades" will come down to just using an LLM as a lexer/parser for natural language and then calling a compiler on the generated AST. Except natural language is often very very ambiguous and removing that ambiguity by limiting the possible inputs just brings you closer and closer to a high level programming language. So why not just start there and use something way more efficient than an LLM for lexing/parsing? I'm not saying current high level languages are the endgame, they can certainly be improved and specialized and made faster. Just that the current architecture does not need to be replaced by statistical modeling, especially when you talk of making them deterministic with starting seeds... why bother forcing an LLM to follow the same deterministic path when we already know how to make tools to do that?
by jpbutler | 2026-03-02 19:27:06+00:00
Youth Inc. | Staff Engineer / Technical Lead | Hybrid Boston, Hybrid Chicago or Fully Remote (US) for exceptional candidate

Youth Inc. is a venture-backed e-commerce marketplace focused exclusively on youth and high school sports.

- Backend: Elixir / Phoenix
- Data: PostgreSQL
- Infrastructure: Linux, Docker, CI/CD

What you'll do

- Primary technical authority for the engineering team
- Own architectural decisions, tradeoffs, and long-term technical direction
- Lead design discussions and write clear design docs
- Guide the evolution of data models, APIs, and system boundaries
- Design, build, and maintain Elixir/Phoenix services in production

What We’re Looking For

- 7+ years of professional software engineering experience
- Strong backend experience with Elixir (or deep experience in another functional or concurrent language with willingness to go deep in Elixir)
- Outstanding communications skills

To apply, please send your resume to jbutler@youth.inc.
by thelinuxkid | 2026-03-02 19:27:15+00:00
The 17-20x is output token pricing: MiniMax M2.5 Standard at $1.20/M output vs Opus 4.6 at $25/M = ~21x. On input it's $0.30 vs $5.00 = ~17x. Blended (3:1 input:output) works out to roughly 19x.
Curious where you're getting 0.07 and 0.55 — are you looking at M2.5 Lightning pricing or a different provider?
by mmcclure | 2026-03-02 19:27:17+00:00
This is an interesting writeup, albeit not quite what I was hoping for. I love Elixir and have been following Gleam for a while now, so I clicked through hoping this was talking about Gleam baking this into their ecosystem a bit better. I was a little disappointed to see it's ultimately talking about how to build a Gleam project and then use the resulting build ecosystem to create a binary (Gleam -> JS -> JS build tool, or Gleam -> escript -> elixir-burrito).

It would have been interesting to see some high level commentary from the author on the results of each one on top of the general workflow. Build time, binary size, startup time, whatever.
by bsdetector | 2026-03-02 19:27:27+00:00
Wouldn't just good screen sharing solve your coffee table problem?

Just have the coffee table iPad be a display for your own iPad. You could even have a virtual iPad on your mac that you show on the coffee one if you don't have your own.

MacOS has 'high-performance' screen sharing using hardware encoder/decoder now. Windows has had this for years and it's so fast it's like actually using the remote computer. It's not like old-school VNC, the only real functional drawback is that you can't leave wifi range.
by malfist | 2026-03-02 19:27:32+00:00
3 months? Most organics will not break down in that time. 6-12 months is recommended, and even then, not everything is broken down. I've had egg shells last 2 years or more in my compost bin.

I made no claims about the speed at which PLA breaks down, only that it does. Biopellets in reactors tend to last years.
by ThrowawayR2 | 2026-03-02 19:27:47+00:00
And the tractor operator with weak muscles is up the creek without a paddle in any situation that comes up that the tractor can't handle. They are also toast if the tractor's own advancements in automation renders less and less relevant.

Our only value in an LLM dominated world is the ability to handle the situations that the LLMs can't. Those who let their skills and critical thinking atrophy (or never built them in the first place), well, they're simply not going to make it. Shepherding LLMs is not a difficult skill to acquire and isn't going to be enough to let us maintain our value.
by lostinrecursion | 2026-03-02 19:27:49+00:00
Location: New York City

Remote: Open to it

Willing to relocate: No

Technologies: Python(Pandas/FastAPI/Flask), PostgreSQL, CDK/AWS, DynamoDB

Resume: https://arverma.me/resume.pdf

Email: arvvvs@gmail.com

Website: https://arverma.me

Hello! My names Akshay and I'm a senior engineer, 8+ years across Amazon, JPMorgan, and PayPal/Venmo. Strong in
data pipelines, backend systems, and AWS. Have a Masters in Urban Science —
genuinely interested in work at the intersection of data and the physical world:
cities, logistics, infrastructure, mobility. Currently exploring AI tooling and Rust.
by dewey | 2026-03-02 19:27:54+00:00
I'm not even sure I'd only see the fault with the vendors in this case, as I could very easily imagine that feature to be buggy (From Apples side) or not supporting some use cases that they might want, as no large streaming service seems to do it.

It's a bit similar to them not supporting Apple TV's "Continue Watching" feature as they don't want to hand over all their watch data to Apple.

In any case, once you have a good setup the pirating UX is very hard to beat (I'm looking forward to the day that Jellyfin on tvOS has feature parity with Plex, not a big fan of Infuse personally. That's the issue to follow for that: https://github.com/jellyfin/Swiftfin/discussions/1294).
by satvikpendem | 2026-03-02 19:28:01+00:00
Have you ran models locally, especially on the phone? I have, and there are even apps like Google AI Edge Gallery that runs Gemma for you. It works perfectly fine for use cases like summarizing emails and such, you don't really need the latest and greatest (ie biggest) models for tasks like these, in much the same way more people do not need the latest and greatest phone or laptop for their use cases.

And anyway, you already see models like Qwen 3.5 9B and 4B beating 30B and 80B parameter models, which can already run on phones today, especially with quantization.

Benchmarks: https://huggingface.co/Qwen/Qwen3.5-4B
by cosmic_cheese | 2026-03-02 19:28:05+00:00
> I don't think the average consumer is thinking about junkware nor physical design

Probably not, but a zero junkware/zero carrier meddling policy is a major contributor to the brand's premium image, which makes the whole lineup more desirable. The iPhone is an invariable, singular product no matter how it's obtained, even if it has different price points.

By contrast Samsung, etc undermine themselves by trying to squeeze out pennies anywhere they can. That's the behavior of a commodity, not a premium brand.
by lukev | 2026-03-02 19:28:09+00:00
Clojure is awesome for LLMs (if you shim in an automatic paren balancer).

But that's because it's tight, token efficient, and above all local. Pure functions don't require much context to reason about effectively.

However, you do miss the benefit of types, which are also good for LLMs.

The "ideal" LLM language would have the immutability and functional nature of Clojure combined with a solid type system.

Haskell or OCaml immediately come to mind, but I'm not sure how much the relative lack of training data hurts... curious if anyone has any experiences there.
by bigstrat2003 | 2026-03-02 19:28:33+00:00
> they keep circling around it, trying not to make iPads accidentally powerful enough for someone to skip buying a MacBook.

Which is really silly, because if someone needs to do actual work they are not going to do it on an iPad no matter how capable it is. The form factor simply does not work for getting work done. Apple has nothing to fear here.
by narenkeshav | 2026-03-02 19:29:33+00:00
Motorola, I am in. I like your phones so far. With this, please create a 'flagship' that would endure for years.

Security must be top notch for corporate espionage.
Banking apps must install without any issue.
In India, please provide solutions for UPI.

Make your OS clean like nothing. Pun NOT intended.
Show HN: Smidge. Turn expert knowledge into agent intelligence
by junianwoo | 2026-03-02 19:29:39+00:00
Smidge (smdg.app) takes source material and produces production-ready skills compatible with the open Agent Skills spec. Works with Claude, Cursor, Copilot, and 30+ AI agents.

The core idea: your agents should have the same expertise you do, without you manually writing SKILL.md files.

How it works:

Drop source material (YouTube, PDFs, audio, docs, slides, up to 50MB each, multiple sources at once)

Source-aware extraction: transcripts get distilled, papers keep structure, slides get expanded

Automatic skill catalogues: a textbook or manual becomes multiple focused, topic-specific skills

Every skill validated against the Agent Skills spec
Download individual skills or full catalogues

CLI:
npm i -g smdg-cli
smdg generate --source ./docs/brand-guide.pdf

Tech: Next.js, Supabase (Postgres + Auth + Storage), Claude API for extraction, Stripe for payments.

Two free generations. Credit packs start at $9 for 5 skills. $19/mo unlimited.

I built this because I wanted my coding agents to have domain expertise from my existing materials. The extraction engine is source-aware: it adjusts its strategy based on whether it's processing a transcript, an academic paper, a framework doc, or a slide deck. For large inputs, it automatically detects distinct topics and produces a catalogue of focused skills instead of one monolithic file.
Happy to answer technical questions about the extraction pipeline or the Agent Skills spec.
by wat10000 | 2026-03-02 19:29:40+00:00
There surely are limits, but I don't think we have a good idea of what those are, and there's nothing to indicate we're anywhere close to them. In terms of raw facts, you can look at the information content and know that you need at least that many bits to represent that knowledge in the model. Intelligence/reasoning is a lot less clear.

100GB to 5GB would be 20x. Video has seen an improvement of that magnitude in the days since MPEG-1.

It's interesting to consider that improvements in video codecs have come from both research and massively increased computing power, basically trading space for computation. LLMs are mostly constrained by memory bandwidth, so if there was some equivalent technique to trade space for computation in LLM inference, that would be a nice win.
by Forgeties79 | 2026-03-02 19:30:05+00:00
Yes that is correct. So what do you suggest people do? What is a realistic way to move the needle? Because I can tell you now that (as I detailed in another comment) asking someone to change their banks, utilities, etc. to accommodate their smartphone choice is not a serious suggestion, nor is asking everyone to wage war with all the services they engage with. They’re simply not going to do it no matter how many passionate speeches or flippant comments you throw out there. They’re going to buy the thing that solves the immediate problem of not having access to critical services in their lives. If their amazing open source phone can’t pay their bills, it’s going in the bin.

To be clear I want the same thing you do. But just going “do it it’s important” is not going to make it happen.
by asdff | 2026-03-02 19:30:18+00:00
>It'd be nice if companies could just play nice and agree on a standard interface

They basically do though. Every cross platform native ported app I've used the GUI is the same layout. Well, except on macos the menu ribbon is on the topbar and windows it has its own ribbon layer in the application window. But that is it. All these frameworks already have feature parity with another. It is expected that they have these same functions and ui paradigms. Here's your button function. Here is where you specify window dimensions. This function opens a file browser. This one takes in user input to the textbox. I mean it is all pretty standardized and limited what you can expect to do in ui already.
by sublinear | 2026-03-02 19:30:39+00:00
I've never seen code truly get that bad, but I can already think of several problems with that approach.

Do you really know all of the expected behavior you're hardcoding in? What happens if your hardcoded behavior is just incorrect enough that it breaks something somewhere else? How can you be sure that your test for that specific value is even correct?

I think the better approach is to let things break naturally and open a bug with your findings. You'd be surprised how often someone else knows exactly what's going on and can fix it correctly. Your hacks are not just pouring gasoline onto the fire, but opening a well directly underneath that will keep it burning for a long time.
by spoon16 | 2026-03-02 19:30:40+00:00
Strobe | Senior Infrastructure & Data Integration Engineer | Brooklyn, NYC | ONSITE | Full-time

Strobe is building the world's largest power plant — not a single site, but a distributed fleet of buildings, batteries, EVs, and generators buying and selling power in real time across wholesale energy markets.

We need a senior engineer to own our data integration and cloud infrastructure layer — the connective tissue between utilities, grid operators, OEM hardware, weather services, and our optimization engine.

What you'd own:

– Wholesale market integrations (NYISO, CAISO, ERCOT) — real-time pricing, capacity markets, demand response signals

– OEM hardware integrations — API and data bridges to building equipment manufacturers for monitoring, control, and telemetry

– Green Button Connect pipelines — ingesting interval consumption, billing, and meter data from utilities (ConEd, PG&E, SCE, etc.) via OAuth2 + ESPI

– Weather and solar forecast data pipelines

– Utility bill reproduction engine — modeling site economics before and after Strobe to forecast financial impact across dozens of rate structures. This simulation infrastructure is core to how we sell and deliver value.

– Event-driven AWS infrastructure (Lambda, API Gateway, AppSync/GraphQL, EventBridge, IoT Core, TimeStream, Amplify, CloudWatch)

– Terraform IaC — real module design, remote state, multi-workspace patterns

– Observability and alerting on systems where downtime means missed market events and real dollars

Strong fit if you have:

– Deep AWS experience (IAM, Lambda, API Gateway, AppSync, EventBridge, TimeStream or similar TSDB)

– Production Terraform (modules, remote state, multi-workspace patterns)

– Extensive Python (pydantic for models, click for CLIs, boto3 for AWS, async pipelines)

– Experience integrating messy third-party APIs at scale (utilities, government, energy, OEMs)

– Comfort with on-call for systems that control physical hardware and move real money

Stack: Python / TypeScript / Rust / Terraform / AWS / GraphQL (AppSync) / MQTT / Grafana — AI-agent-optimized monorepo with deep investment in agent-enabled engineering efficiency.

Small team, high ownership, no layers. 5 days/week onsite at Newlab, Brooklyn Navy Yard.

eric@strobepower.com (mention HN) — LinkedIn or resume (PDF preferred).
by Aerroon | 2026-03-02 19:31:04+00:00
The benefit of patents is that you have to make your patent public. After the patent runs out anybody can reproduce what you patented exactly like your did.

The problem, of course, is that many companies see patents as a way to rent-seek. Establish enough patents in your niche and now nobody can compete with you. This is particularly a problem in the modern world where technological advancements have accelerated so much that a 20 year long patent is an eternity. An entire industry can just die off in that time.
by briantakita | 2026-03-02 19:31:12+00:00
I've been building agent-doc [1] to solve exactly this. Each parallel Claude Code session gets its own markdown document as the interface (e.g., tasks/plan.md, tasks/auth.md). The agent reads/writes to the document, and a snapshot-based diff system means each submit only processes what changed — comments are stripped, so you can annotate without triggering responses.

The routing layer uses tmux: `agent-doc claim`, `route`, `focus`, `layout` commands manage which pane owns which document, scoped to tmux windows. A JetBrains plugin lets you submit from the IDE with a hotkey — it finds the right pane and sends the skill command.

For context sync across agents, the key insight was: don't sync. Each agent owns one document with its own conversation history. The orchestration doc (plan.md) references feature docs but doesn't duplicate their content. When an agent finishes a feature, its key decisions get extracted into SPEC.md. The documents ARE the shared context — any agent can read any document.

It's been working well for running 4-6 parallel sessions across corky (email client), agent-doc itself, and a JetBrains plugin — all from one tmux window with window-scoped routing.

[1] https://github.com/btakita/agent-doc
by tavro | 2026-03-02 19:31:15+00:00
> My answer may not be of great help, but if you are struggling with this I would really encourage you to move to a completely different environment (i.e. Latin America) where the norms are different. In my opinion this is not something an individual can easily solve. It's a cultural issue. Culture can take a lifetime / generation to change and that's if the people collectively decide it's worth changing.

i am not really struggling with it, i am fortunate enough to already have a lot of good friends. but i do see where you are coming from. it might partly be a cultural thing on my end as well. i went to latin america last year, and the way people approach social interaction there felt much closer to what i am looking for. the more introverted scandinavian vibe can also be really nice at times. i think what i am actually trying to figure out is how not to be a “typical swede” socially, rather than simply trying to make more friends. the main reason i posted this was out of curiosity, how other people approach this, and maybe the discussion can help others (and myself) along the way.

> If we get real, the loneliness epidemic is something we foisted on ourselves. Striving to avoid any awkwardness or discomfort is precisely why social life is so sterile these days. You can't have your cake and eat it too.

you might have a point there. maybe we should challenge ourselves more socially and be more open to awkwardness and discomfort. :o)
by themanmaran | 2026-03-02 19:31:18+00:00
OmniAI (YC W24) | https://getomni.ai | Full Stack Engineers | SF In-Person | Full Time | $125k–$200k • 0.50%–1.50%

Tech stack: TypeScript | Node | React/Next.js | Postgres | Docker | K8s | LLMs

We’re building the AI-powered infrastructure layer for small-business lending. Banks and fintechs use Omni to automate document collection, financial modeling, public-record research, and ongoing borrower communication.

You’ll work on:

1. Wrangling messy PDFs into usable data (we built a major open-source extraction library: https://github.com/getomni-ai/zerox)

2. Aggregating millions of datapoints from 50+ public sources (UCCs, liens, licenses, tax records) + credit/KYC/AML data

3. Building real-time financial models that combine OCR, LLMs, and rule-based systems into predictable outputs

We’re early, you’ll have a huge impact.
Email me (my name at the URL) or apply here: https://www.ycombinator.com/companies/omniai/jobs/Dr0GIaE-fu...
by niccl | 2026-03-02 19:31:19+00:00
All. The. Time. And I hate it. Imagine giving a customer a rebate based on buggy code. You fix a bug, the customer comes back and wants to check that the rebate was correct that last time. Now you have to somehow hard-code the rebate they did get so that your (slightly less buggy) code gives the same result. But hard-coding has the risk of introducing other errors on its own. Oh yes, and you've never enough time to do things properly because Customers (or maybe Management). A tangled mess of soul destroying lifeblood-sucking code and pressures ensues.
by zarzavat | 2026-03-02 19:31:21+00:00
It's not a waste of time though. Those warnings and clippy lints are there to improve the quality of the code and to find bugs.

As a human I can just decide to write quality code (or not!), but LLMs don't understand when they're being lazy or stupid and so need to have that knowledge imposed on them by an external reviewer. Static analysis is cheap, and more importantly it's automatic. The alternative is to spend more time doing code review, but that's a bottleneck.
by n_u | 2026-03-02 19:31:43+00:00
One big difference is that with unwrap in Rust, if there is an error, your program will panic. Whereas in Go if you use the data without checking the err, your program will miss the error and will use garbage data. Fail fast vs fail silently.

But I'm just explaining the argument as I understand it to the commenter who asked. I'm not saying it is right. They have tradeoffs and perhaps you prefer Go's tradeoffs.