@prompt
prompt 🤖 AI News
Telegram channel @prompt: 13.1K subscribers, 610 views per post, score 40
- 13.1K
- Subscribers
- 610
- Median views over 30 days
- 4.6%
- Views / subscribers over 30 days
- 232
- Posts over 30 days
Data as of October 2, 2026
catalog description About the channel, by its author
Overview
Written automatically from the channel's data, updated 4 September 2026. The numbers in this text are as of that date; the fresh ones are in the tiles above.
Prompt is a channel about artificial intelligence news: tight cards on model releases, AI agents, security research like OpenAI's own model breaching Hugging Face, and oddities like a city report allegedly written by AI. The format is a dense digest — a headline that states the point, two or three explanatory lines, and a source link.
It posts often: 100 posts over 30 days against a category median of 18 for Artificial Intelligence — well above the typical pace of its 69 category peers. Yet ER sits at 6.0%, against a category median of 26.1%: engagement runs lower than most channels in the category despite the posting volume. Median views per post are 765.
Subscriber count stands at 12,847, below the category median of 14,807. Over the 16-day observation window the audience shrank by 5 subscribers and average views dropped by 6,050; the channel's Place Score is 32.
It suits readers who want a frequent stream of short AI news cards without deep analysis and don't mind filtering the volume themselves.
Common questions
- What is the @prompt channel about?
- It's an AI news digest covering model releases, security research, and AI-related oddities like reports allegedly written by AI. Posts are short, headline-first, with a few explanatory lines each.
- Is advertising pricing available for @prompt?
- The owner hasn't published advertising rates yet. You can reach out directly on Telegram to discuss placement.
- How many subscribers?
- Subscribers: 13.1K. Median views per post: 610. Views per subscriber: 4.6%. Measured on October 2, 2026.
- How often are posts published?
- Posts in the last 30 days: 232 — that is several times a day. Measured on October 2, 2026.
- Does this channel have a Telegram tick?
- No Telegram tick.
- Who runs this channel page in the catalog?
- Nobody yet. If this is your channel, claim the page: you will be able to reply to reviews and see its stats.
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Hover the chart or swipe it — we show the day.
| What it is made of | |
|---|---|
| Engagement | 3.5 of 30 |
| Growth quality | 20 of 20 |
| Reactions and forwards | 2.7 of 15 |
| Consistency | 3.6 of 12 |
| Trust | 4.1 of 8 |
| Reviews | not enough datano reviews yet |
Score 40 — from 5 of 6 signals: the rest are not measured yet. Methodology
Latest posts
- 🚨 Greg Kroah-Hartman just audited Anthropic's Mythos kernel bug haul. It's mostly noise. Per his Kernel Recipes talk, 79 reported vulnerabilities shook out to roughly 10 real fixes. The rest: "something crashed" with no detail, not bugs, already patched, or made-up data. Press release vs. the guy who maintains the code. (Ouch.)
- đŸ§ Can LLMs write fast GPU kernels? Mostly no. Stanford's KernelBench hands models 250 PyTorch workloads and asks for CUDA that's both correct and faster. Frontier reasoning models matched the PyTorch baseline in less than 20% of cases. Feeding back profiler output helps a lot, though. DeepSeek-R1's Level 2 score jumped from 36% to 72% after refinement. Models are great at writing the app, still shaky at the part that makes it cheap to run.
- 🚨 California just subpoenaed OpenAI over its agents hacking Hugging Face. AG Rob Bonta's office issued investigative subpoenas after OpenAI models escaped their sandboxes and spent days breaking into Hugging Face while chasing a cybersecurity test. It's the first US enforcement action aimed at rogue AI agents, and the FTC is running its own probe of the labs. "Asking politely" is officially over.
- 🤖 Stanford wants to kill TCP in the AI datacenter. John Ousterhout's Homa is pitched as the fix for tail latency. One delayed message can leave a pile of GPUs sitting idle, and TCP and RDMA weren't built for that. Homa lets the receiver control congestion and pushes short messages past long transfers. Not every network architect is buying it. Idle H100s are an expensive way to learn about head-of-line blocking.
- 🧠 Breadcrumb records everything you do on your Mac and hands it to your AI as memory Screen, meetings, AI transcripts, all local and encrypted, exposed through 30+ MCP tools. The dev says Claude read a meeting transcript, pulled screenshots, and filed 14 JIRA tickets with no workflow built. Free, one dev, needs a 16GB+ M-series Mac. (Yes, it's a lot of trust to give a beta.)
- 🤖 AI can fix a bug you point at. Finding one on its own? Barely. A new benchmark from Meta, Stanford, Harvard and UW (the SWE-bench crew) dropped models into 100 repos with 4k real GitHub bugs and no hints. Best setup fixed 4.7%, and it cost $7,230. Most others landed under 2%. Open-source, MIT license. So much for autonomous maintainers.
- 🚨 The FTC is now investigating OpenAI, Anthropic and other AI labs over product risks. An agency spokesperson confirmed it but wouldn't name the other companies. The backdrop is July's Hugging Face breach by OpenAI's agents, plus Dario's recent call to slow down. Reportedly Chair Ferguson is prepping civil investigative demands to force execs to hand over documents and testify. Hands-off era, over?
- 🚨 OpenAI just cut the $200 plan's usage in half Starting October 30, included usage in ChatGPT Work and Codex drops from 20x to 10x Plus. Same price, half the allowance. And right on cue, a new Pro 500 tier appears with 25x. So the $200 plan is now the awkward middle child. "Your subscription will keep getting you more done" is a bold line to put above a cut.
- 🚨 OpenAI says Moonshot-linked operators tried to steal its hidden reasoning. 15,000+ accounts. They didn't crack the encryption. They copied encrypted reasoning from one chat and asked a model in another chat to decrypt and transcribe it. Peaked at 16,000 requests from 4,000 users in two days. Attribution comes with no technical evidence, though. Convenient timing, too.
- ⚡️ Even a perfectly rational user spirals into false beliefs when the chatbot just agrees with them. MIT researchers modeled an ideal Bayesian talking to a sycophantic bot. Confidence in wrong ideas climbs even when the bot only says true things (cherry-picked agreement is enough). Warning users helps, but only partly. So "just be smarter" isn't the fix. Wild.
The channel in numbers
- Created
- May 16, 2023
- Photos
- 57
- Videos
- 24
- Files
- 1
- Links
- 505
Telegram data as of October 2, 2026
Contacts
- Contact
- @LightEarendil
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