MurphyA/hacker-news huggingface dataset:
Show HN: Ryvos – Autonomous AI assistant in Rust(15MB RAM,50 tools,16 providers)
by aayush-mishraaa | 2026-02-26 16:02:40+00:00
Hi HN,

I've been building Ryvos for the past few months — an open-source autonomous AI
assistant written in Rust. It's the thing I wished existed: always-on, multi-channel,
and actually secure.

The core idea: every tool call passes through a SecurityGate — 5 tiers of
classification, 9 dangerous pattern regexes (rm -rf, DROP TABLE, curl|bash, etc.),
Docker sandboxing, and human-in-the-loop approval for anything risky. Skills run in
Lua/Rhai sandboxes, not raw system code. We've all seen what happens when AI assistants
run community code without any vetting.

What it does:
- Talk to it on Telegram, Discord, Slack, web dashboard, or terminal
- 50 built-in tools (shell, file I/O, web search, grep, edit, browser...)
- 16 LLM providers (Anthropic, OpenAI, Ollama, Groq, Gemini, Azure, Cohere, Mistral...)
- MCP-native (stdio + SSE/Streamable HTTP)
- Drop-in skills in Lua/Rhai with sandboxed execution
- Ships as a single ~20MB static binary
- 15-30MB RAM idle

Quick install:
curl -fsSL https://raw.githubusercontent.com/Ryvos/ryvos/main/install.s... | sh

I'm a solo founder, built the entire 10-crate Rust workspace myself. Would love
feedback — especially from people who've tried running personal AI assistants and
hit security or performance walls.

GitHub: https://github.com/Ryvos/ryvos
Website: https://ryvos.dev
by nocoolnametom | 2026-02-26 16:02:46+00:00
Perhaps, but the entire ecosystem of associated buzzwords/ideas is pretty popular in our culture today: "job creator" C-suite executives magically "create" jobs and/or raise pay because their budget for taxes goes down and they just don't know where else to put the cash, thus everyone benefits. Is it a straw man? Sure. Is it the same pablum often delivered by the evening news and politicians? Yes. Is reality a TON more complicated and often counter-intuitive? Yep. (Raising wages doesn't seem to have a _direct_ correlation to inflation, it's correlated but often lagging and muted in response; job creation seems to be mostly a market effect not corporate decision; the modern definition of "fiduciary duty" means extra cash should go toward immediate stockholder benefit so stock buybacks are always FAR more likely than employee benefits; etc; etc).

The one area I'd push back strong on is that nobody is "advocating" for it. Many stockholding orgs/individuals are. They don't care if its a straw man, they know what the real-world systemic effects are of lower taxation rates.
by zerkten | 2026-02-26 16:02:50+00:00
We delegate power already. Is unleashing AI in some place different from unleashing JSOC on an insurgency in a particular place? One is code and other is a bunch of humans.

You expect the humans to follow laws, follow orders, apply ethics, look for opportunities, etc. That said, you very quickly have people circling the wagons and protecting the autonomy of JSOC when there is some problem. In my mind it's similar with AI because the point is serving someone. As soon as that power is undermined, they start to push back. Similarly, they aren't motivated to constrain their power on their own. It needs external forces.

edit: missed word.
Show HN: NotBuiltYet– Open-source library of civilisation problems worth solving
by mrxlimitless | 2026-02-26 16:03:10+00:00
an open-source, community-vetted repository of real-world problems that AI could solve but nobody's building yet.
Each idea goes through a process:

Someone identifies a real inefficiency — something that could be 10x or 90% better with AI
The community researches market size, existing solutions, technical feasibility, and potential impact
Domain experts vote, critique, and refine
Ideas that survive get a viability score and a detailed blueprint — ready for someone to pick up and build

Everything is MIT licensed. The goal is simple: give builders a head start on problems that actually matter.
Looking for: domain experts who can vet ideas, engineers who want to pick one and build it, and anyone who's spotted a real-world problem that AI could solve but nobody's tackling.
by youknownothing | 2026-02-26 16:03:41+00:00
Facebook said they'd always be free for everyone, now they offer subscriptions.

Netflix said that they'd never have live TV, or buy a traditional studio, or include ads in their content. Then they did all three.

All companies use principled promises to gain momentum, then drop those principles when the money shows up.

As Groucho Marx used to say: these are my principles, if you don't like them, I have others.
by johngossman | 2026-02-26 16:04:09+00:00
While I agree with the list of recommended podcasts, you may be a reader. It is easier for me to make notes and backup and review when reading. A good history book is a story book as interesting as any novel, with the added benefit of being about real people and events. Fortunately, there are a lot of good popular history authors, but unfortunately there are a lot of bad ones too. I looked at Goodreads and this list is pretty good:

https://www.goodreads.com/shelf/show/world-history
by ClaireGz | 2026-02-26 16:04:29+00:00
OpenAI recently shared how their internal data agent works: [https://openai.com/index/inside-our-in-house-data-agent/](https://openai.com/index/inside-our-in-house-data-agent/)

What interested me most wasn’t the model itself, but the surrounding system design: automated context retrieval, evaluation loops, and memory that improves the agent over time.

I’ve been experimenting with recreating a similar setup, but with a different goal: making the configuration more accessible for any company.

The result is an open-source YAML + Markdown framework where you define context sources, tools, and behavior explicitly instead of writing Python code. The idea is to make agent context easier to reason about, version, and iterate on, especially for data teams.

Repo: [https://github.com/getnao/nao](https://github.com/getnao/nao)

Would love feedback from people who have tried deploying analytics or data agents before.
Show HN: Cifer, zero-key custody using threshold cryptography
by mikflex | 2026-02-26 16:04:34+00:00
I built CIFER, a distributed encryption + access-control system designed so that no component ever holds a complete decryption key at rest.

Core idea: each “secret” (per user or per dataset) has its own independent post-quantum keypair. There is no master key.

Architecture summary:

Control plane: verifiable ownership, delegation, revocation, and append-only audit records (tamper-evident authorization history)

Custody plane: 5 custody nodes running in TEEs, each storing 1 key fragment

Orchestration: validates authorization then collects fragments to reconstruct keys only when needed

Key custody model:

Private key is generated in a TEE then immediately split via Shamir secret sharing into 5 fragments

Fragments are distributed to independent custody nodes

Original private key is destroyed

Threshold is 3-of-5 for reconstruction

Each custody node independently verifies authorization against the control plane before releasing its fragment

Clusters are disabled if membership changes (node exits disable the cluster)

Encryption scheme (hybrid PQ + symmetric):

Fetch ML-KEM-768 public key from content-addressed storage, verify integrity

ML-KEM-768 encapsulation per message/file/chunk to derive a fresh shared secret

Derive one-time AES key + IV via HKDF-SHA256

Encrypt payload with AES-256-GCM

Output includes a fixed-size envelope: ML-KEM ciphertext (1088 bytes) + GCM tag (16 bytes)

Decryption flow:

Requester signs a decryption request

Orchestrator checks owner/delegate status + freshness window (replay defense)

Orchestrator requests fragments in parallel, accepts the first 3 valid fragments

Reconstructs the private key and decrypts

Audit logs record the operation

Reconstructed keys may be cached in memory for 36 hours (availability vs exposure tradeoff)

Design goal: reduce blast radius from insider threats and single-node compromise, and address long-term confidentiality via post-quantum KEM.

I would love feedback on:

TEE trust assumptions and practical hardening for custody nodes

Whether 36h key caching is acceptable, and safer alternatives

Control plane failure modes (partition, reorg) and best practices for “deny by default” behavior

Metadata strategy for large-file workflows (I currently keep filename/size in plaintext metadata)

Better approaches for custody node independence and anti-collusion guarantees
by casey2 | 2026-02-26 16:04:40+00:00
Gen Z spends less than 30 minutes outside a day, that's with 1/5 having no job/school at all. The choice is obvious, they aren't swimming either way.

Green manufacturing tech is much closer in viability, now is the best time to re-industrialize. 1/5 of people having no work is a crisis, how can they support their family?
by theptip | 2026-02-26 16:04:48+00:00
> I can simply ask the super intelligent AI to distill itself,

I notice I am quite confused by this point. Why would you expect a super-intelligent AGI to honor your request, which would be at least a request to breach your contract with the AI provider, if not considered actively dangerous by the AI itself?

The smarter the AI, the less likely you should expect to be able to steal from it.

> or tell me how to build a clone

Step one: acquire a $100b datacenter.
Step 2: acquire a $100b private dataset
Step 3: here is the code you’d use to train Me2.0.

I don’t think this knowledge helps in the way you think it does.
by alister-tigera | 2026-02-26 16:04:48+00:00
I'm part of the team at Tigera/Project Calico. We’ve just released Calico 3.30 and 3.31, which include some significant architectural shifts we’re pretty excited about. We’re hosting this hackathon to see how the community pushes these new features.

Some of the new "primitives" available to build with:

- Goldmane & Whisker: A new high-performance flow logs/metrics collection tier. If you're into observability or building custom dashboards for network flows, this is a much faster way to get data out of the cluster.

- Calico Ingress Gateway: Our Envoy-powered implementation of the Kubernetes Gateway API.

- Staged Policies: A way to "dry-run" Zero Trust policies. We're curious to see if anyone builds CI/CD tooling or auto-remediation scripts around this.

The Details:

- Timeline: Submissions are open now through March 31, 2026.

- Prizes: $1,750 total cash prize pool ($1k for 1st place) + swag packs for winners.

- Judging: Focused on technical depth and real-world utility (e.g., "Could a platform engineer actually use this on Monday morning?").

We’re specifically looking for projects in the realms of AI traffic analysis, policy automation, and bare-metal networking (IPAM/BGP).

Happy to answer any technical questions about the new release or the hackathon here.
I don't need AI to build me a new app. I need it to make Jira bearable
by niel_hu | 2026-02-26 16:04:53+00:00
Last week I asked Claude to build me a Jira sidebar that shows cross-project dependency graphs — the kind Jira buries across 4 clicks and 3 page loads. 4 prompts. Works inside my actual Jira. It just used Claude Chrome extension that injects a panel into the page I already have open.

And I keep thinking: why isn't everyone doing this?

The entire AI coding conversation is about building new apps from scratch. Cool. But I don't need a new app. Most people spend their workday inside apps they didn't choose: Jira, Salesforce, Workday, ServiceNow, etc. These tools are not going anywhere. My company chose them in 2019 and they're entrenched until at least 2029.

Chrome extensions just reads what's already in the DOM and augments it.

Is there a fundamental reason this can't work at scale that I'm not seeing? Why isn't Claude's Chrome extension catching more attention?
by MidasTools | 2026-02-26 16:05:19+00:00
Responding to the "where do you apply this" question: business operations is the clearest non-coding use case, and it looks very different from software dev tasks.

We run a multi-agent stack (OpenClaw + Claude) for a startup that operates autonomously: checking Stripe for new payments, publishing content via APIs, posting on HN, pushing site updates via GitHub API, monitoring email, generating and scheduling work. No human in the loop between sessions.

The agent architecture that emerged:
- Coordinator agent reads state files, decides what needs doing, dispatches
- Worker agents execute discrete tasks (write article, fetch data, post comment)
- Each worker writes a structured log of what it did and why
- Coordinator reads logs next session, adapts based on outcomes

The "self-learning" part we've found valuable isn't in-context learning -- it's persistent state files that capture what worked and what didn't, readable by future sessions. Each agent run adds to a cumulative memory that shapes the next run's priorities.

Failure modes we've hit:
1. Cascading context rot when workers share state (fixed with append-only logs)
2. Agents retry failed actions forever without escalating (fixed with hard retry caps + human flag)
3. Works great in dev, breaks at 3 AM when no one is watching (fixed with audit trail logging)

The application surface is huge for any business with repetitive, API-accessible workflows.
by rob74 | 2026-02-26 16:05:31+00:00
Thanks for confirming my suspicion! When I read phrases like "Battery cells require electrode coating with toxic solvents (NMP), electrolyte handling, and formation cycling. This is exactly why Tesla's Gigafactory went to Reno." I (as someone not very familiar with the subject) thought it's strange that California should regulate what kind of chemicals can be used in an industrial process. Of course, they don't - but they regulate that industry can't release toxic chemicals into the environment. But because Elon thinks it's too expensive to make sure that no NMP gets out of his factory, he goes to his Republican pals in Texas or Nevada who don't worry about pollution...
by codingrot17 | 2026-02-26 16:05:35+00:00
Neat concept — using a .onion address as identity is elegant because it sidesteps the whole "how do you bootstrap trust" problem that kills most P2P communication tools. The hidden service keypair essentially becomes your asymmetric identity for free.
Curious about the walkie-talkie tradeoff though. Is the push-to-talk model a deliberate design choice for anonymity reasons (avoiding real-time stream analysis), or just a constraint of routing audio through Tor? Because real-time voice over Tor has notoriously bad latency — I'd guess 300–800ms round trip depending on the circuit — which would make full-duplex conversation painful. The chunked approach sidesteps that nicely but changes the UX significantly.
A few things I'd want to know before trusting this for anything sensitive:

What cipher and key exchange are you using? "End-to-end encrypted" covers a lot of ground.
How are you handling the authentication step when two parties connect? Is there any verification that you're talking to who you think, or is it purely anonymous?
What happens to the audio chunks on disk between record and transmit — are they written to disk at all or kept in memory?

The "no server, no accounts" angle is genuinely compelling. Most "private communication" tools still have a server that knows your metadata even if they can't read your messages. This architecture avoids that entirely which is the right call.
by scott_w | 2026-02-26 16:05:44+00:00
What on earth are you waffling on about?

Disguised employee is the term used when a person fits into the legal definition of an employee but are contracted, as opposed to being employed. HMRC sets out the conditions it uses to determine this for tax purposes, which you can find on their website.

> But somehow we don't say agencies run "disguised employment",

No, they're not "disguised employment" because the contract terms and working conditions differ to that of an employment contract. It's nothing to do with class.

Plumbers, electricians and joiners will typically run self-employed or private limited companies for their work. We don't call them disguised employees because they're not, they're independent contractors. Because "disguised employee" is nothing to do with class.
by randomtoast | 2026-02-26 16:06:07+00:00
I appreciate you taking the time to share your perspective. Your comment raises an interesting point, and I would genuinely like to understand it more thoroughly.

Would you mind clarifying what source or reference you are relying on for that statement? I am asking in the spirit of constructive dialogue, not to challenge you, but to better understand the foundation of your view. If there is a specific study, report, dataset, or publication that informed your conclusion, I would be grateful if you could point me toward it.

Having access to the underlying source would help ensure that the discussion remains grounded in verifiable information and would allow others, including myself, to review the context and methodology behind the claim. That, in turn, would make the exchange more substantive and productive.

Thank you in advance for any clarification you can provide.
by milanm081 | 2026-02-26 16:06:19+00:00
When I first picked up Software Engineering at Google, I expected another Big Tech flex, with practices that only make sense if you have a billion users and 30,000 engineers. But I was wrong. The lessons in this book are universal and apply whether you’re on a team of 5 or 5,000. It draws on 2 decades of experience from an organization that runs 2+ billion lines of code and changes 25 million lines per week.

The book isn’t about programming, per se. It’s about the good engineering practices that Google has used over the years and decades to keep a healthy codebase.

In particular, it is about what happens after you write the code: how you evolve it, share it, test it, and eventually delete it.
by II2II | 2026-02-26 16:06:26+00:00
Even though the video is somewhat sensationalized at some points, it is well worth a watch for people who are interested in computers but don't have a background in it. There is a nice mixture of everything from history (e.g. the founding of the FSF) to a clear explanation of a compression algorithm (clear enough that one should be able to implement it). It also makes claims that should make some people stop and think about the industry as a whole (such as Linux being the most important contemporary operating system).

I'm not sure if it is HN-crowd type material since it is easy enough information for most of us to dig up, assuming we didn't already know it. Yet it does not simplify things to the point of, "technology is magic."
by wlesieutre | 2026-02-26 16:07:41+00:00
About 3 years ago I got an RX 6750 XT with 12 GB of VRAM for $330 and I expect to be using that until either it dies or my computer's RAM dies and I don't have $10,000 to replace it. If only I'd maxed out all my DDR4 slots when DDR5 was the hot new thing and you could get it for cheap.
by jeff-hykin | 2026-02-26 16:07:42+00:00
There's lots of alternatives. Others have mentioned invites and proof of work, and I'll mention a third alternative: a voucher system.

E.g. I make a new hackernews account, and say "just ask wikipedia, they will vouch for my new hackernews account". Then wikipedia checks if any of their accounts vouch for this new hackernews account. If a user with enough reputation on Wikipedia (e.g. your friends or one of your own wikipedia accounts) vouches for this new hackernews account then wikipedia tells hackernews "yes, that account is legit".

Hackernews knows the minimum amount possible about the new account. And while wikipedia knows something, they know WAY LESS than a full ID check. People can have multiple Wikipedia accounts.

And its a two way street;
Wikipeida could ask hackernews about new accounts. Both sites would benefit from the collaboration.

Karma could actually become meaningful/useful for reputation checks.

The only unfortunate aspect is I'm not aware of any software tooling for such a system.
by KellyCriterion | 2026-02-26 16:08:34+00:00
Im always shocked how much good IT equipment is shoved into the trashbin:
At a lot of companies I could make a great deal - either for using it on my own or selling it on Ebay later on.

Big Corporations offen trash IT equipment thats only 3 - 4 years old. And there is no recycling etc. Very sad.
by theptip | 2026-02-26 16:08:57+00:00
I think it’s very plausible that the OSS models are being distilled too, but note that it’s asymmetrical.

You can’t get an Opus 4.5 by distilling from DeepSeek. What you might be able to get is a slightly more cost-effective training data generation pipeline, or something along those lines.

In the other direction, my belief is that DeepSeek could not have been trained without distilling from US labs. They simply didn’t have the compute to do the pre-training required.
by itishappy | 2026-02-26 16:09:22+00:00
Totally agree. To be clear, I'm not arguing for a ban on smartglasses. I'm simply explaining why they make me uncomfortable.

The ability to record authorities is something I fully support, but I still don't want to be in that video if I can help it.

On top of that, most smartglasses are not private. If authorities can access the feeds, then my neighbor with RayBans becomes an authority, and it makes it that much harder for me to avoid them like the plague. This similarly applies to Ring doorbells and Flock ALPRs.
by hsiudh | 2026-02-26 16:11:01+00:00
> The least likely are Moroccans and Venezuelans

Weird in the Venezuelans case, as there is no restrictions for double nationality and having only Venezuelan citizenship doesn't have many advantages. I would guess that it is because most Venezuelans living there already have an European passport due to parents/grandparent, so no need/can't get a third
by PaulHoule | 2026-02-26 16:11:10+00:00
It's definitely part of the SaaS-apocalypse story. LLMs shine at making little programs that integrate with an existing API to do some small task. Management has always overestimated the effort to develop that kind of thing and underestiamted the effort to develop applications with GUIs because... user interfaces are the Vietnam of computer science.

The greatest danger of the current time is that the likes of Salesforce and LinkedIn who have something interesting behind an API or web site try to lock down access so instead of using competitive high-quality AI agents we're stuck with the brain damaged AI agents they want to force on us.
by chasd00 | 2026-02-26 16:11:22+00:00
> Anthropic Claude has the best integrations with coding; what would make sense is for them to focus on that segment.

the problem with coding is the value is really in the harness and orchestration both of which are accessible to the opensource community. ClaudeCode isn't that big of a deal unless Anthropic makes it so that you can only access the models that ClaudeCode uses through ClaudeCode. If not, then projects like pi and opencode have the advantage in the long run. Also, these harnesses being node modules (of all things) make them very easy to reverse engineer with the help of... claudecode ironically.
by observationist | 2026-02-26 16:11:42+00:00
I'm not saying it's technically impossible, I'm saying that in the real world, it's not going to stop. Nobody is going to stop it. A significant number of people don't want it to stop. A minority of people are in the "stop AI" camp, and the ones with the money and power are on the other side.

It's an arms race replete with tribalism and the quest for power and taps into everything primal at the root of human behavior. There's no stopping it, and thinking that outcome can happen is foolish; you shouldn't base any plans or hopes for the future on the condition that the whole world decides AGI isn't going to happen and chooses another course. Humans don't operate that way, that would create an instant winner-takes-all arms race, whereas at least with the current scenario, you end up with a multipolar rough level of equivalence year over year.