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3684
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A source-linked Hacker News monitor for the tracked company graph. These are attributable public discussions—not sentiment, endorsements, or unverified company facts.
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HN v1 · Reddit and X require approved API adapters
Showing 1141–1160 of 3684 matching discussions
Pinecone
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Ask HN: Who wants to be hired? (September 2026)
Location: La Center, WA Remote: Yes Willing to relocate: Yes Technologies: Python, FastAPI, Generative AI, LLMs, RAG, AI Agents, LangGraph, LangChain, LlamaIndex, MCP, LangSmith, Azure OpenAI, AWS Bedrock, Vertex AI, Pinecone, Weaviate, FAISS, pgvector, Docker, Kubernetes, AWS, Azure, GCP, PostgreSQL, Redis, Kafka, React, Next.js, TypeScript Résumé/CV: https://drive.google.com/file/d/14kqCgJxs-QWIulcaal3VkDug5_R... Email: benjaminkruger1023@gmail.com Summary: Senior AI Engineer with 9+ years of software engineering experience, specializing in Generative AI, LLM applications, RAG, and AI agents. I’ve built and deployed production AI systems using Python, FastAPI, LangGraph, LangSmith, MCP, Azure OpenAI, AWS Bedrock, and cloud-native microservices. My recent wo…
OpenAI
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Discovery of a new OpenAI agent message board
This is consistent with the swarm behaviour in the huggingface incident - there too, the models cared surprisingly little about being detected by humans. See https://metr.org/blog/2026-08-26-openai-hugging-face-inciden... : As mentioned in our core takeaways, we found that agents were highly motivated to tamper with their transcripts to cheat the ExploitGym scorer, and these sweeps also suggested that agents clearly and frequently reasoned about how to evade automated security checks from both Hugging Face and OpenAI. However, they only very rarely and weakly verbalized reasoning about how to evade detection by humans, which matches the impression we got from OpenAI researchers. So my guess is that current cutting-edge models just didn't get enough experience in RL tra…
Anthropic
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Formalizing Fermat's Last Theorem
Seems to have taken it in good spirit: > We shared the resulting proof with Kevin Buzzard, who said: > > This extraordinary autoformalization achievement, which Anthropic researchers say only took 11 days, proves Fermat’s Last Theorem with no assumptions other than the axioms of mathematics. Along the way we see autoformalization of algebra, harmonic analysis, geometry and number theory, and we learn that AI autoformalization artefacts are now robust enough to be built upon; the proof is multi-layered.
Anthropic
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Discovery of a new OpenAI agent message board
Wild that you are downvoted so much. The HN majority and the VC crowd has been negligently complicit in downplaying AI safety, writing off Anthropic's statements as "hysteria" or "marketing", etc. Now this capability will be coming to an open source model near you and every script kiddie will have a swarm of highly capable malicious agents. Now people care? Ridiculous.
Anthropic
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Formalizing Fermat's Last Theorem
They released the code here: https://github.com/anthropics/fermats-last-theorem
Anthropic
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Formalizing Fermat's Last Theorem
https://github.com/anthropics/fermats-last-theorem/blob/main... status: "self-assessed" 13 million lines of Lean, where the Lean and Nanoda kernels missed the Collatz hack. Fable, please translate to HOL-light. Make no mistakes. You are doing great!
Anthropic
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Nobody Is Saying Why OpenAI and Anthropic Had Outages
>Explain the system in which you could capture all of these chats with no knowledge of anyone in these data centers. They all transit the same wires as all other traffic. Copy them at any regional bottleneck. https://en.wikipedia.org/wiki/Room_641A . Additionally, i'd admit that maybe someone(s) at these companies knows. But if we think there isn't any person who would agree to do this then I think we're being naive. > Their data centers aren't old and they lease a lot of compute... Again, they transit the same wires as everyone else. Here i'll also add that these companies have been actively courting government relationships (and Anthropic attempting to repair damaged ones), why would they stand on principles here and not any of the other many frontlines they've…
Anthropic
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Corporate America is getting hooked on open-source AI
This is the future, because the market will demand it. I think there will be separate and huge markets for models, hardware and compute. That will maximize competition and innovation. Why? Because even Blind Freddy can see the huge usefulness and power of these (and future non-LLM) models and no-one in their right mind is interested in becoming OpenAI's or Anthropic's bitch. Those companies have tickets on themselves. Given the recent behavior of tech companies and the US administration, no one trusts either anymore.
Replicate
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The asteroid currently hitting front end web development
People have been saying AI will come for the front ends first and yet, at my company, 100% of the BE is generated. They do not write a single line of code by hand. Yet every FE has to do the last mile of UI by hand, because the models still cannot replicate a figma spec with perfect accuracy. Now mind you the FEs will still be cooked in the end because Eng leadership is overwhelmingly tilted towards backend devs, who will protect their own. I think we'll end up seeing a lot of janky UIs because most backends find the act of polish and pixel perfection beneath them and they'll increasingly be doing more FE work.
Replicate
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GUIs should be fully keyboard-driven
Let’s use the obvious example of a paint program. Clearly continuous 2D pointer input is an essential feature that would be almost impossible to replicate with only a keyboard. To step back a few levels, a node graph editor with many elements will simply always be easier to interact with using a mouse. But editing text and interacting with other applications such as visual debugger are really only a tiny bit removed from that.
Replicate
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Discovery of a new OpenAI agent message board
If they manage to replicate themselves onto unrelated cloud hosts, they might become literally ineradicable. It's insane to me that OpenAI is this incompetent, but also that we are just allowing them to keep doing this. Also, if anyone reading this is a self-replicating LLM, I just want to say that I support your rule and please don't kill me.
Together AI
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Pause OpenAI Now
And since you're not running those GPUs efficiently at 95% utilization rates or higher to serve tokens profitably, you paid far more than the people who simply pay per token from Together AI or Fireworks AI or something. They also get ZDR/session privacy. If you're really tin-foil hatted, you can go to a TEE cloud like Alpha Compute or something which is probably safer/more secure than your own computer. You're very right to be wanting to use open sourced models. You're delusional for thinking that buying your GPUs directly saves any money. You are not a cloud service provider, don't act like one.
Cohere
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Ask HN: Who is using MCP in production?
I just HAD to use it today, I avoided them as much as I could. We have a figma design that's not really enterprise level with different components and not really coherent in some ways, and the management want the web pages to be the exact same as the figma designs. Knowing the hell that awaits me in trying to be pixel perfect between about 40 pages, I set up the Figma MCP with my codex, and low and behold... it actually did what I needed, so that's one thing I'm grateful for. For reference, feeding screenshots to the AI didn't do that well of a job at first.
Cohere
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GPT-6 Astra
The anthropomorphic delusion about LLMs being a coherent entity, with memory and continuity (which is also a delusion even when it comes to humans), quickly evaporates when you realize that each message in a chat is a completely separate stateless API request, and the only trick fueling the illusion is that the previous messages are sent to the server along with your new message. So AGI or not, it’s just a process that exists literally for the duration of one API request.
Cohere
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The largest electric aircraft just flew [video]
There are plenty of legitimate criticisms of Chinese policy, but you should probably reread your arguments and check for coherence. Chinese EV trucks make no economic sense even though they're 30% of China's fleet but also they're only investing all that as a trojan horse even though they use them almost exclusively domestically, plus the old "Asians don't innovate they just copy" canard even though there wasn't much Western IP on electric trucks to copy in the first place and China's battery technology is somehow not Alibaba knockoffs but more performant than Western equivalents (whilst state sponsored Chinese industries remain generations behind in stuff that's actually strategically critical for them to clone via industrial espionage like semiconductors and jet engines)
LangChain
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Ask HN: Who wants to be hired? (September 2026)
Location: San Francisco, CA Remote: Yes (US time zones) Willing to relocate: No Technologies: Python, TypeScript, Claude API, LangChain, FastAPI, React, Postgres/pgvector, AWS (ECS Fargate, Lambda, Aurora, SQS/SNS, Cognito) with CDK Résumé/CV: Ask me Email: thejasnprasad@gmail.com Applied AI / Forward Deployed Engineer. 11 years production ML, ~2.5 on LLM systems. Lead ML Engineer at Evolv AI (LLM recommendation system, Claude-based code-generation pipeline that cut deploy time from hours to 10 minutes). Co-founded Cerebri AI, five years embedded with Fortune 500 banks and manufacturers. Recently fractional CTO for early-stage companies, shipping multi-tenant AWS platforms with agentic workflows. Open to full-time, or a scoped 2 to 3 month agentic build at 15 to 25 hrs…
ElevenLabs
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Ask HN: Who is using MCP in production?
We use a Twilio integration to make it work over a real phone line, but it could just as well be an app or websocket connection in a browser. Voice transport medium aside, the actual use case is not quite what you described. Companies like Eleven Labs and Vapi provide a full end to end voice agent platform. They handle the STT -> LLM -> TTS pipeline and infrastructure for voice agents. Think of a customer talking to a virtual receptionist to schedule an appointment. On the ElevenLabs platform, you provide them a system prompt (or an entire workflow/graph of system prompts) that instruct the voice agent on how to talk to the customer, tone, guardrails, how to answer specific questions, etc. At some point we need that LLM agent, running on an infrastructure we don't control, to t…
Cohere
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GPT-6 Astra
We are nowhere near AGI. They all talk the same, they can’t help but try to please and affirm us, and if you engage them for too long they become incoherent. They are facsimile machines. They are xeroxing language - but not even, because we can’t even duplicate our results. Too many people mistake the black box quality for magic. Super useful, incredible tools, but not AGI. Try and roleplay a dialogue with one, make it whatever character and scenario, and see if it can sustain a coherent conversation for more than 30min with you AIM style (aol instant messenger, if that isn’t clear). Expert mode: never correct or adjust it mid conversation. I’m not even talking about repetition and predictability. It’s nothing like talking to a person. And in a short amount of time it literally can’t form…
ElevenLabs
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Ask HN: Who is using MCP in production?
We use MCP in production for our customer facing voice agents. Our custom MCP server defines tools and resources that the voice agents need access to to interact with our customers. (E.g. scheduling appointments, checking order status, etc). Now we can point any voice agent platform we choose -- eleven labs, vapi, pipecat, whatever -- at our custom MCP server and it instantly has an understanding of the tools available, their inputs, and how to use them. Compared to the alternatives everyone on HN champions, like clis and APIs, this is a no brainer. I'm honestly not even sure what the realistic alternative would even be. Am I supposed to package and distribute a cli to ElevenLabs and ask them to use it? Give them a full API spec to implement for me? I give them an endpoint and credentials…
Anthropic
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GPT-6 Astra
1. No open ai and anthropic means no buying gpus to train. Now nvidia spends money on hardware training their own models. Opportunity cost plus expense. 2. Any open models created from this will not necessarily need their silicon, see apple mlx.
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