MurphyA/hacker-news huggingface dataset:
Show HN: AlphaEvolve inspired evolution harness for Pokemon
by brianllamar | 2026-03-10 19:24:34+00:00
Last week I sat in the LLM Paper Club (hosted by the latent.space podcast). We shared a paper from DeepMind on "Discovering Multiagent Learning Algorithms with Large Language Models". Linked in the github repo.

This was my first time sitting in one of these and reading an LLM paper. I thought it was interesting that the AlphaEvolve agent in the paper essentially writes code, runs it, scores the output, and then writes better code, over and over. It's not discovering strategies through play. It's discovering algorithms through code mutation. The LLM proposes changes to how regret is accumulated or how policies are derived, a fitness function scores the result, and the best variants survive to the next generation.

The two algorithms it found (VAD-CFR and SHOR-PSRO) use mechanisms the authors describe as "non-intuitive," things like volatility-sensitive discounting and hard warm-start schedules that a human designer probably wouldn't have tried. That's the interesting part: the LLM isn't constrained by the same design intuitions we are.

To make it concrete for myself, I built a small version of this loop for a Pokemon game agent. The setup is simple: define a fitness function (turns survived, maps visited, stuck events), parameterize the strategy space (door cooldown, stuck threshold, skip distance), and let an LLM propose variants that get evaluated in parallel. Ten agents race through the game, the best parameters survive. I used tapes.dev to collect session telemetry and feed observational memory back into the fitness scoring.

The first run already surfaced something useful: shorter door cooldowns (4 vs 8) reduce stuck events from 16 to 9. Not a breakthrough, but the point is the system found it without me guessing. That's the same dynamic as the paper, just at toy scale.

What I took away from the paper club: the bottleneck in algorithm design isn't computation, it's the search process itself. If you can express your problem as "parameterized code + fitness function," an LLM evolution loop can explore the space faster than manual iteration. The paper proves it works for game theory. The link is in my startup's repo, I want to explore applying this technique for improving future general purpose and coding agent sessions.

Just pointing out Pokemon aren't the only thing evolving in that repo.
by 3abiton | 2026-03-10 19:24:42+00:00
Man, that was such an enjoyable read. I loved your story on the wild server hunt, back when it was posted on r/localllama. I think one thing that is missing from the whole AI "discussion" is this train of thought of how we go from abstract mathetmatical formulation to intuitive understanding of the underlying functionality, and you showcased it beautifully in this article. Similarly to 3blue1brown who also did an amazing series on transformers. Kudos!
by allenu | 2026-03-10 19:25:35+00:00
I definitely encountered this second-system effect recently. I have an app that works well because it was written to target a specific use case. User (and I) wanted some additional features, but the original architecture just couldn't handle these new features, so I had to do a rewrite from the ground up.

As I rewrote it, I started pulling in more "nice to haves" or else opening up the design for the potential to support more and more future features. I eventually got to a point where it became unwieldy as it had too many open-ended architectural decisions and a lot of bloat.

I ended up scrapping this v2 before releasing it and worked on a v3 but with a more focused architecture, having some things open-ended but choosing not to pursue them yet as I knew that would just introduce unneeded bloat.

I was quite aware of the second-system effect when doing all this, but I still succumbed to it. Thankfully, the v3 rewrite didn't take as long since I was able to incorporate a lot of the v2 design decisions but scaled some of them back.
by moritzwarhier | 2026-03-10 19:26:11+00:00
Coincidentally, I didn't want to mention this in my original comment to not appear as a know-it-all type or person (and I certainly am not very proficient in git details).

But exactly this was the point where I realized that even IntelliJ's pretty good VCS integration for git can be easily replaced with a simpler mental model.

Still, should even have included that because I do add and commit from the IDE out of convenience, too.

For adding selected hunks, I also use the CLI less often than IntelliJ I guess.

I didn't like that they've adopted a more aggressive stance on keeping in-memory changes for open tabs when it comes to modifying the file system using git CLI (or any other tool), similar to VSCode.

But they implemented this pretty well so that it's not as confusing as in VSCode.

I still hate it when the dialogue jumps at me after switching branches and having done something before on the CLI (such as `git stash push` etc).

But I have to say that they're doing a very good job, and I'm thankful not having to deal with VSCode git integrations that only seem to confuse people, who then cannot use git without VSCode.
Show HN: Zehrava Gate – an control plane that sits between AI agents and prod
by cgallic | 2026-03-10 19:26:13+00:00
Hey HN,

I built Zehrava Gate because I kept having the same problem: AI agents that could read anything worked great, but the moment I let one write — to a CRM, send an email, charge a card — I had no consistent answer to "who authorized that?"

What it is: A self-hosted policy engine + approval queue for agent actions. The agent submits an intent before executing. Gate evaluates a YAML policy (deterministically — no LLM), scores risk, and either auto-approves, holds for human review, or blocks. Every decision is logged with a signed execution token. The agent can't skip it.
V2 (SDK-based):
gate.propose() → policy decision in ~2ms
Human approval queue + dashboard
Signed execution tokens with 15-min TTL
Agent registry + role-based access
Webhook notifications on approve/reject
Full audit ledger by intent ID

V3 (proxy-based, all three phases shipped):
HTTP forward proxy — one env var, no code changes: HTTP_PROXY=http://gate:4001
TLS intercept for HTTPS destinations
Credential vault mode: agent submits intent only, Gate fetches the credential from 1Password/HashiCorp/AWS at execution time, runs the API call, discards. A compromised agent has nothing to exfiltrate.
LangChain/LangGraph integration: GateTool and gateNode() drop-ins

Honest scope: This protects against mistakes and enforces policy — not against a fully compromised agent that controls its own runtime. The proxy architecture closes that gap further, but there's no magic bullet for fully adversarial runtimes.

Stack: Node.js, SQLite (better-sqlite3), YAML policies, zero LLM in the eval path.

npm: npm install zehrava-gate
GitHub: https://github.com/cgallic/zehrava-gate
Live demo: https://zehrava.com/demo
by wat10000 | 2026-03-10 19:26:24+00:00
Are you talking about evidence that LLM contributions are harmful, or evidence that there are any? The former is unnecessary, as this is not an evangelism project, it's for people who already believe LLMs are bad. For the latter, I think the project is aimed at people who are already plugged into the issue, or suffers from the usual mistake of thinking everyone is plugged into a specific issue. In any case, it takes about five seconds to search for "claude" in the main vim repo's PRs and find that evidence.
by ramesh31 | 2026-03-10 19:26:38+00:00
>(Re: level 8) "...I honestly don't think the models are ready for this level of autonomy for most tasks. And even if they were smart enough, they're still too slow and too token-hungry for it to be economical outside of moonshot projects like compilers and browser builds (impressive, but far from clean)."

This is increasingly untrue with Opus 4.6. Claude Max gives you enough tokens to run ~5-10 agents continuously, and I'm doing all of my work with agent teams now. Token usage is up 10x or more, but the results are infinitely better and faster. Multi-agent team orchestration will be to 2026 what agents were to 2025. Much of the OP article feels 3-6 months behind the times.
by _wire_ | 2026-03-10 19:26:42+00:00
Doctorow begs questions in the manner typical of self-hosted and/or expatriated journalists, who must be evangelists, but religious work tends to disregard the labor of research as it's hard work that doesn't pay and it might uncover a contradiction of the orthodoxy.

Let religious voices like Doctorow indicate places where we may examine policy and why we should be interested to look there, but sermons aren't vehicles to carry meaningful analysis.

Sermons must have a righteous tone and term "fascist", used correctly by Doctorow, has a long-standing colloquial connotation of teutonic allegiances during WW2, which emotionally overloads his diatribe.

Yet, he's correct to invoke it, even as his rhetoric is misplaced for audiences whose forbearers were sacrificed to the trauma of WW2, and whose generational scar tissues suppress remembrance that the patterns of evil which exploded across the Axis did emerge within our sacred bastions of liberty and freedom, and that these evils are fomenting again right now.

So I appreciate Doctorow's polemics even as I too regard the details of his claims with skepticism.
by hinkley | 2026-03-10 19:26:45+00:00
One of my biggest accomplishments was shipping a suite of 5 apps from four divisions where three of them resented each other’s existence and seemed bound and determined to build rules in the system that made sure the other two couldn’t function. Which made no goddamn sense because it was a pipeline and you can’t get anything out one end if it gets jammed in the middle.

I was brought in to finish building the interchange format. The previous guy was not up to snuff. The architect I worked for was (with love) a sarcastic bastard who eventually abdicated about 2 rings of the circus to me. He basically took some of the high level meetings and tapped in when one of us thought I might strangle someone.

Their initial impression was that I was a prize to be fought over like a child in a divorce. But the guy who gives you your data has you by the balls, if he is smart enough to realize it, so it went my way nine times out of ten. It was a lot of work threading that needle, (I’ve never changed the semantics of a library so hard without changing the syntax), but it worked out for everyone. By the time we were done the way things worked vs the way they each wanted it to work was on the order of twenty lines of code on their end, which I essentially spoonfed them so they didn’t have a lot of standing to complain. And our three teams always delivered within 15% of estimates, which was about half of anyone else’s error bar so we lowly accreted responsibilities.

I ended up as principal on that project (during a hiring/promotional freeze on that title. I felt bad for leaving within a year because someone pulled strings for that, but I stayed until I was sure the house wouldn’t burn down after I left, and I didn’t have to do that). I must have said, “compromise means nobody gets their way.” About twenty times in or between meetings.
by merlindru | 2026-03-10 19:26:52+00:00
they are doing exactly that now, but at some point, there's no discernible difference between a gaussian blur and a complex shader like liquid glass.

taken to an extreme, the heaviest possible blur results in just one solid color (at which point there is no visible difference between a gaussian blur and LG at all).

so the more blurry the shelf is, the less important liquid glass gets. therein lies the dilemma: you can't have interesting, complex backgrounds AND legibility. it's either one or the other.

the current design is good. or becoming good, finally. but it's also not worth the, what, 2 hour reduction in battery usage, the lags and visual glitches, the major changes many apps see themselves forced to undergo, ... because it looks almost like a gaussian blur now.
by rectang | 2026-03-10 19:27:47+00:00
Fair point. I have definitely caught myself taking longer to revise a prompt repeatedly after the AI gets things wrong several times than it would have taken to write the code myself.

I'd like to think that I have this under control because the methodology of working in small increments helps me to recognize when I've gotten stuck in an eddy, but I'll have to watch out for it.

I still maintain that the LLM is saving me time overall. Besides helping in unfamiliar domains, it's also faster than me at leaf-node tasks like writing unit tests.
by dybber | 2026-03-10 19:28:05+00:00
I have been trying this as well, and you can quickly come very far.

However, I fear that agents will always work better on programming languages they have been heavily trained on, so for an agent-based development inventing a new domain specific language (e.g. for use internally in a company) might not be as efficient as using a generic programming language that models are already trained on and then just live with the extra boilerplate necessary.
by pixl97 | 2026-03-10 19:28:27+00:00
> Where can I go?

Off the internet. Maybe it's just time we all face the public internet is dead.

Maybe a trusted private internet, though that comes with it's own risks and tradeoffs.

Maybe we start doing PRs over mailed USB keys. Anyone with enough interest will do it, but it will cut out the bots. We're back to a 90's sneakernet. Any internet presence may become a read only site telling others how to reach you offline.

The information superhighway died a long time ago. 4chan enlightened me on the power of intelligent stupidity. The machinations of a few smart people could embolden countless stupid people to cause nearly unlimited damage. Social media gathering up the smart and dumb alike allowed bullshit asymmetry to explode onto the scene and burned out anyone with a modicum of intelligence.
by dmd | 2026-03-10 19:28:56+00:00
It's wild to me the disconnect between people who actually use these tools every day and people who don't.

I have done exactly the above with great success. I work with a weird proprietary esolang sometimes that I like, and the only documentation - or code - that exists for it is on my computer. I load that documentation in, and it works just fine and writes pretty decent code in my esolang.

"But that can't possibly work [based on my misunderstanding of how LLMs work]!" you say.

Well, it does, so clearly you misunderstand how they work.
by rapatel0 | 2026-03-10 19:29:09+00:00
Clarification. Duplicating multiple groups of layers in a "reasoning" loop

Normal:

L1 -> L2 -> L3 -> L4 -> out

Unrolled (current framing):

L1 -> [L2->L3] -> [L2->L3] -> L4 -> out

Looped (proposed):

--<--loop----
| |

L1 -> [L2->L3] x N --> L4 -> out

"reasoning loop"

Note: ascii rendering HN is not trivial
by begemotz | 2026-03-10 19:29:58+00:00
I am not a professional coder. However, I have typically seen people respond more favorably to Code compared to other systems including Codex (percentage-wise). I'm curious to know what exactly you feel is inferior?

On the other hand, recently for me, the usage limits in Claude have been inconsistent and frustrating. I seem to get a lot less out of it than I have in the past and am considering trying one of the other big 3 sub plans to see whether it suits my use case more.
by heavyset_go | 2026-03-10 19:30:17+00:00
> At least in the US, society has been well on it's way to collapse before the LLM came out. "Fake news" is a great example of this.

IMO you can blame this on ML and the ability to microtarget[1] constituencies with propaganda that's been optimized, workshopped, focus grouped, etc to death.

Proto-AI got us there, LLMs are an accelerator in the same direction.

[1] https://en.wikipedia.org/wiki/Microtargeting
by Izkata | 2026-03-10 19:30:26+00:00
Semicolons start a new thought, they don't mark an aside that lets you return to the original line of thought. Like in their example:

> For example: When you read this sentence (in your mind) it should feel complete and correct. Perhaps you read in your own voice — something I don’t normally do — or without one at all.

I would have used parentheses in both places, and semicolons don't work in either one:

> For example: When you read this sentence (in your mind) it should feel complete and correct. Perhaps you read in your own voice (something I don’t normally do) or without one at all.
by QuiEgo | 2026-03-10 19:31:13+00:00
No, it’s Amazon. If a senior blocks the slop they will be told they are not disagreeing and committing enough. If bugs get through they will be told they didn’t dive deep enough. It’s classic Amazon blame game. Someone gets left holding the bag for impossible asks (hint: it’s never the person doing the ask), and then gets piped and fired.
by radarsat1 | 2026-03-10 19:31:13+00:00
it also reminds me a bit of this diffusion paper [1] which proposes having an encoding layer and a decoding layer but repeats the middle layers until a fixed point is reached. but really there is a whole field of "deep equilibrium models" that is similar. it wouldn't be surprising if large models develop similar circuits naturally when faced with enough data.

finding them on the other hand is not easy! as you've shown, i guess brute force is one way.. it would be nice to find a short cut but unfortunately as your diagrams show, the landscape isn't exactly smooth.

I would also hypothesize that different circuits likely exist for different "problems" and that these are messy and overlapping so the repeated layers that improve math for example may not line up with the repeated layers that improve poetry or whatever, meaning the basic layer repetition is too "simple" to be very general. that said you've obviously shown that there is some amount of generalizing at work, which is definitely interesting.

[1] https://arxiv.org/abs/2401.08741
Ask HN: How are you reviewing code at work these days?
by curiousgal | 2026-03-10 19:31:47+00:00
With everyone using AI coding assistants, I am curious to know what policies people have implemented to deal with the influx of AI generated code? I am maintaining an internal library at work and as more people on the team gain access to Claude Code, I am wondering whether we should be highlighting/labelling AI code or not.
by simlevesque | 2026-03-10 19:31:58+00:00
I use devcontainers in all the projects I use claude code on. [1] With it you can have claude running inside a container with just the project's code in write access and also mount a test folder with just read permissions, or do the opposite. You can even have both devcontainers and run them at the same time.

[1] https://code.claude.com/docs/en/devcontainer
by gibspaulding | 2026-03-10 19:32:00+00:00
You’re overestimating how old a pc has to be not to support Windows 11. My parents have a Latitude 5470 (I think?) with a 7th gen i5, 16gb memory, 1tb ssd, and most definitely USB 3. It’s a perfectly adequate machine for running a browser + office suite, but according to Microsoft it’s e-waste because of Windows 11’s TPM-2 requirement.

Obviously for the HN crowd there are workarounds (my mom has actually been getting along with PopOS pretty well), but this could probably have met her needs just as well.
by keeda | 2026-03-10 19:32:32+00:00
> Did none of the layoffs in 2023 on do the job?

No, because the calculus of layoffs shifted. Briefly, there is always a natural attrition rate A%, but whenever companies do an X% layoff they expect a smaller Y% additional attrition (due to morale etc.) So they expect an overall (A + X + Y)% reduction in headcount within a few months of the layoffs.

However, the job market swung so rapidly from pro-employee to pro-employer in that timeframe that the Y% never happened, and in fact there was even a drop in A%. And so companies still ended up with more employees than planned and had to scramble to achieve their headcount goals using other means (RTO mandates, shifting headcount offshore, further layoffs with AI washing, etc.)

A bit more detail on the calculus in this comment: https://news.ycombinator.com/item?id=46142948
by jacquesm | 2026-03-10 19:33:09+00:00
Well, I've been working with a number of these devices, different brands but the same or slightly more functionality and they all have little controllers in them. Some are documented and you can talk to them directly (usually I^2C) others are 'back boxes', you can tell there is something living on the other side of the nominally 'NC' pin but not what and you don't have control over it.

I also have a couple of very fancy ones that you can compensate and whose NV memory you can write to directly. Those are pretty expensive, $100 or thereabouts but the precision is unreal for a non-governed device.
by gus_massa | 2026-03-10 19:34:10+00:00
Hi from Argentina! We use a lot of loaned words while programming and related stuff. I usually prefer to read the English version, because in the Spanish version I have to untranslate. It's more common in es-es localized docs, they like to translate every single word.

A translated version may be useful for first year students, but somewhere in the middle of the degree every book is in English, the variables must be named in English, the API must use English names, and when you talk you use 95%Spanish+5%English.

The only exception I make is for some real world objects. I work in the first year of the University of Buenos Aires. I made a custom program that must handle the 10 "sedes" where the classrooms are. How do I translate "sede"? It's usually a "building", but sometimes a "sede" has two "buildings", or half a "building". Do I call them "campus", we used to have to "sedes" that were nearby "buildings" inside the same big park that everyone would call "campus". Now each "sede" is like 5 miles away form the nearest one, so they are pretty discrete. So I made an exception and the variable names in the code say "sede".
by skyberrys | 2026-03-10 19:34:34+00:00
I do appreciate how Gemini seems to be consistently getting better at delivering assistance and information on a broad range of topics beyond code. You are touching onto a topic that holds a lot of weight for the future, which is what do we really mean by General. Does it do everything? Does it communicate with everyone? How will the world really look and notice once AGI exists? If it does will we still only strive to monetize it?
by decimalenough | 2026-03-10 19:35:00+00:00
This is.. not huge news? Google is discontinuing its own Widevine server, but Widevine is not going anywhere, you can still run your own server or use any of a number of third-party hosts offering it:

https://widevine.com/solutions/widevine-providers

And surprise surprise, the blog post in question appears to be very thinly disguised marketing for one of those third parties.

Also, the Google service was free and came with no SLA or support, meaning anybody remotely serious about DRM was not relying it on in the first place.
by Havoc | 2026-03-10 19:35:48+00:00
They're definitely inferior to proper tests, but even weak CC tests on top of CC code is an improvement over no tests. If CC does make a change that shifts something dramatically even a weak test may flag enough to get CC to investigate.

Even better though - external test suits. Recently made a S3 server of which the LLM made quick work for MVP. Then I found a Ceph S3 test suite that I could run against it and oh boy. Ended up working really good as TDD though.
by hinkley | 2026-03-10 19:35:58+00:00
My adaptation of the Version 2 Problem is “any idiot can ship version 1 of a product, but it takes skill to ship version 2”.

Usually levied at people who are so hyper focused on shipping a so-called MVP that is really demoware that they are driving us at a brick wall and commenting the entire way about what good time we are making.