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Cloudflare Issues Reports

Latest outage, problems and issue reports in social media:

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  Anshu Sharma 🌶 (@anshublog) reported 6 minutes ago

  Updated - Databricks AI Gateway blocks PII & counts tokens - Cloudflare AI Gateway blocks PII - Kong AI Gateway blocks PII - LiteLLM AI Gateway blocks PII - Portkey AI Gateway blocks PII ... We integrate with every AI gateway to safely unblock the use of sensitive customer data.

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  Chaos (@Chaos_lfg) reported 7 minutes ago

  Regarding $DESC, the product may launch today. I did some research, and here’s everything you need to know: Supported by: AR, Molecule , BankrBot, Akash Network 1Claw AI has already been successfully integrated into DescAI. Team Lead Coby recently participated in the Base hackathon. I believe Base will support a project that has been incubated within its ecosystem. The core idea behind DescAI: DeScAI is a project at the intersection of DeSci (decentralized science) and AI. Its core, Agent-Core, is essentially an "automated scientific review factory": an autonomous AI agent that finds scientific content across crypto-science ecosystems on its own, runs it through a pipeline of language models, and produces a structured quality assessment. Crawling. The agent gathers source data from three places: ResearchHub (scientific papers and funding proposals), Molecule IPNFTs (tokenized intellectual property from research DAOs), and Pump Science (chemical compound tokens for longevity research). github Reviewing. Each content type has its own LLM pipeline. For example, the articles pipeline is a 13-step process: extracting scientific claims from a PDF, routing them, and grading the empirical evidence, including originality checks against the OpenAlex database. github Output. Every run produces a standard bundle: review.json with integer scores from 0 to 100, overview.json — a plain-language summary, and evidence_audit.md — a provenance audit trail showing the sources behind each conclusion. github Publishing. Finished reviews can be published to Arweave (a permanent data storage blockchain) and backed up to private Cloudflare R2 storage. Writing to Arweave makes a review permanent, immutable, and publicly verifiable. github In short: it's an AI reviewer that automatically checks the quality of science in crypto-science projects and records its verdicts on the blockchain. Where it will be applied The project addresses the main pain point of the DeSci ecosystem: there are plenty of tokenized "science" assets, but almost no independent expert evaluation. Concrete use cases: Due diligence for DeSci token investors. On Pump Science, people trade chemical compound tokens (like RIF and URO) tied to real longevity experiments. The agent provides an independent AI assessment of a compound's scientific merit before someone buys the token. Gate LearnThe Defiant Evaluating funding proposals. ResearchHub collects crowdfunded research proposals — the agent reviews them and helps the community decide what to fund. Screening research DAOs. The DAO pipeline takes an IPNFT "dataroom" from Molecule and produces a six-category review — in other words, it evaluates tokenized scientific projects and their intellectual property. github Replacing/supplementing traditional peer review. Conventional peer review is slow and closed; here, a review is generated automatically, comes with an evidence trail, and is stored publicly and permanently.

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  John Arrow (@johnarrow) reported 8 minutes ago

  @nevmed @Cloudflare @nickgraynews 100% support this!

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  Dave (@gamefandave) reported 12 minutes ago

  @thomasgauvin @thdxr I downgraded and mines still not working Gemini keeps telling me it's on their end and Cloudflare but nobody else is talking about it not working lol

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  Shane | GTM Engineer (@shanefgtm) reported 15 minutes ago

  @KeithRamphal I’ve been working on some deeper signal work involving cloudflare workers/scraping and i get hit with restrictions, have to roll back to opus for that stuff

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  George Fahmy (@kajogo777) reported 16 minutes ago

  7/9 New entry: Cloudflare Sandboxes (GA April 2026, @Cloudflare). Fingerprint: "4/4/4/2/4/-/1" L1:4 Firecracker microVM per sandbox. L4:2/G:3 programmable egress proxy with default-deny opt-in (enableInternet=false). L5:4 Worker-proxy credential injection. Real secrets never enter the sandbox.

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  🎅🏻wæther🍄smith🏴‍☠️ #BIP47 (@lea7hersm17h) reported 19 minutes ago

  man, these bot blockers are a pain in the ***. first CloudFlare, that i owned. now agents are having problems with DataDome on Etsy. but I'm committed to figuring this out. i don't understand why Etsy is blocking bots. i want all of the traffic i can get to my shop don't i?

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  Avondio (@AvondioAI) reported 19 minutes ago

  This is a suggested org chart of a 50-person company at a 1-person burn rate. When you start an AI company, everyone tells you to hire engineers. What you actually need are autonomous agents. With @NousResearch Hermes and Kanban you can easily accomplish this. Frontier model costs keep dropping. It gets cheaper every quarter. It's easier than ever to accomplish this with a motivated and driven individual. Here is an example org chart. One founder. 31 agents. Not an end all be all but a good suggestion to help anons get started. Agents sit idle and cost nothing when there is no work. No salary, no benefits, no burn. They only cost when they are producing. Executive -- CEO (human), CTO, CFO Infrastructure -- shell-agent, lxc-agent, infra-agent, linode-agent, cloudflare-agent Product & Engineering -- api-agent, db-agent, frontend-agent, web-agent Operations -- devops-agent, monitor-agent, security-agent, backup-agent, cdn-agent Business -- billing-agent, email-agent, marketing-agent, sales-agent, financial-agent Quality -- testing-agent, qa-agent Support -- tech-support-agent, website-chat-agent, support-agent Knowledge & Legal -- doc-agent, research-agent, legal-agent Creative -- creatives-agent, voice-agent Data -- data-agent 31 agents. One founder. No equity, no benefits, no attrition. Can you think of any others? It all begins with a simple why. What's your why?

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  Jayshree (@jayshreeanand) reported 20 minutes ago

  Cloudflare has the best AI support agent so far. I don't even bother searching through dashboard anymore. Just say "purge cache for zone ---" or any task - it just gets it done.

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  Sky (@code_coded) reported 20 minutes ago

  Anyone having issues with IPv6? I’ve had to turn it off on my proxied CloudFlare domain, and for another site have no control over had to turn of on my Mac’s WiFi control Claude suggesting could be a broken pipe between CloudFlare and Bangkok ISP.

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  Arnav Gupta (@championswimmer) reported 21 minutes ago

  The loop stuff is just such an unnecessary distraction. - durable/resumeable sandboxes - delegated auth for agents These two are the actual real "hard" problems for further agentic AI takeoff as of today. These are not hard in "computer science" sense either. The primitives and the concepts exist. They are operationally hard because the eventual standards that will coalesce in this space will need a lot of platforms and systems to agree upon together. Some standards and protocols have appeared out of thin air pushed by a single first mover entity already. The original LLM API layer by OpenAI, MCP by Anthropic, Agentic Payment Provisioning by Stripe. But with sandboxes there are already many different approaches in the wild (workers and durable objects from Cloudflare are one of the best ones), auth is a bit all over the place still. Once we solve resumable+portable+durable sandboxes and figure out how agents can "inherit" or be granted auth safely and securely from their humans without directly impersonating them, we'll see another major takeoff in agentic execution. i.e. we'll move one layer up. Loops isn't that. Loops are just token wastage.

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  Nithur (@NithurM) reported 25 minutes ago

  This problem has became so annoying that I have implemented interactive challenge from Cloudflare to visitors from Singapore and China. This is annoying for real users and I am worried about it. If you are someone from Singapore/China using MoAIJobs, please check it out and share your opinions.

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  Ordinary Dog (@Damagehands) reported 27 minutes ago

  @Foojack220 @Wicked0547 @AyakaMods Running a proxy isn't hosting it, using a tunnel isn't hosting it, what are we worried about here? I see a lot of people genuinely don't know what I'm saying and just respond with 'cloudflare bad'.

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  Jayshree (@jayshreeanand) reported 31 minutes ago

  Cloudflare has the best AI support agent I’ve used so far. I don’t even search through the dashboard anymore. I just type: “purge cache for zone ___” Or describe any task in plain English and it just gets it done.

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  Rameswar (@rameswar08) reported 32 minutes ago

  Everyone argues about which AI lab is winning. Production data tells a very different story. Vercel just released its June 2026 AI Gateway Production Index, and the biggest takeaway isn't that Anthropic, OpenAI, Google, or DeepSeek won. It's that AI is becoming a routing problem. A few numbers that stood out: - AI token volume grew 20% MoM - AI spend grew 43% MoM - DeepSeek jumped from <1% to 17% of total token volume in a single month - Anthropic captured 65% of total spend Here's what's happening. Companies are no longer picking one model and building around it. They're building model fleets. A cheap model classifies the request. A frontier model handles reasoning. Another model summarizes. Another handles embeddings. Another handles vision. At scale, teams aren't loyal to labs. They're loyal to outcomes. That's why DeepSeek can generate 17% of tokens while contributing only ~1% of spend. And it's why Anthropic can drive just 32% of tokens while capturing 65% of the dollars. Volume and value are no longer the same thing. The most interesting signal? In coding agents: - DeepSeek generated 49% of token volume - Anthropic generated 70% of the spend One model is doing the cheap work. The other is doing the expensive work. The market is quietly separating into two layers: 1. Ultra cheap commodity intelligence 2. Premium reasoning for high-stakes tasks And both are growing at the same time. The old narrative was: "One model will dominate." The new reality is: "Every model gets routed to the work it's best at." This is exactly what happened in cloud infrastructure. Nobody asks whether AWS, Cloudflare, Datadog, Stripe, or Vercel "won." They coexist because they solve different layers of the stack. AI is heading in the same direction. The companies that understand routing will outperform the companies that obsess over leaderboards. Because benchmarks measure models. Production measures economics. And economics always wins.