Your Private Proxy

Cloudflare and Datadome aren't the same problem. Cloudflare: TLS fingerprint + JS challenge. Fix your JA3, done. Datadome: persistent behavioral model. Clean TLS on a residential IP still flags if request timing is machine-uniform. Different layers. One fix doesn't cover both.

@tehseowner @barryfabien Logged-in Chrome passes because Google scores the session, not just the IP. Phone passes because device + cell signal are self-consistent. Proxy + fresh browser = clean IP, nothing else. GL needs the cookie history to back up the geo claim.

@barryfabien @YourPrivateProx On my phone, I can go to /?gl=uk and get the proper results. However, using a proxy any any browser (logged out), and sometimes in Brave/Firefox without it, they are wrong. Logged in with real Chrome, they are usually right.

Data for SEO organic results are often unreliable because they’re served the “static proxy results,” which are not the results most people see in the wild. Mainly referring to certain highly competitive results here. We have been #1-3 getting a lot of traffic and Data for SEO still shows N/A. Once you get these results, they tend to stick until you clear cache. They rarely happen when logged into a Google account, when logged out they’re less likely to be seen on Chrome-powered browsers in general, and more likely to be seen on Firefox. Doesn’t make any sense but I’m just reporting my observations.

@exploraX_ The browser fingerprint is the easy layer — MCP browser setups handle that. The ASN check is what actually flags agents at scale. Datacenter egress gets CAPTCHAs within hours; residential doesn't.

microsoft open-sourced the tool that let your agent browse the internet. completely free. no API fee. MIT licensed. it's an MCP server that gives LLMs browser automation, it lets your agent navigate sites, click, fill forms, and screenshot on its own. here's how to set it up in 2 mins: — what it actually is: it's called Playwright MCP. not an agent itself — it's the hands. it plugs into your AI and gives it browser control through the page's accessibility tree, not screenshots. that means it's fast, deterministic, and needs no vision model. — why that matters: most "AI browses the web" demos are slow and flaky — they screenshot a page and guess. this reads the actual page structure. so when it clicks "submit," it hits the real button. every time. — setup (claude code): claude mcp add playwright npx @playwright/mcp@latest that's it. one command. codex and gemini cli use the same npx block in their config — drop it in, restart, done. — what you can do with it: → "test the signup flow and screenshot every step" → "pull the pricing off these 5 sites into a table" → "fill this form and tell me what breaks" real browser actions, described in plain english. — one honest catch: great for exploratory tasks and smoke tests. for release-critical regression testing you still want deterministic scripts, not natural-language runs. and on windows, claude code defaults to git bash — switch it to cmd or the install fails. — free leverage, 2-minute setup. if your AI can't touch the web yet, this is the fix.

@leerob Point 2 is where it gets tricky. Semrush bot detection is aggressive — computer-use agents browsing at normal speed still cluster sessions in ways that get flagged. SEO research via agent is one of the faster paths to a rate-limited session.

Cursor (and coding agents generally) still blows my mind daily. Just today: 1. I shipped a new landing page. I gave a 10min voice note to Cursor, left to go eat dinner, and came back to a 90% finished version. Made some small design and copy tweaks and merged. 2. Had Cursor dig through Search Console and Semrush with computer use, researched places we could improve SEO, and then merged 3 PRs with fixes. 3. Used the Supabase MCP to pull thousands of emails from the Compile waitlist, had it research them with web search based on ideal fit for the event, and got back a CSV with the top people to invite and why. 4. Updated an internal app I built for doing company-wide surveys (think Typeform but Cursor branded) in a few hours before our All Hands. 5. Had a few agents researching furniture I'm hoping to buy. They searched the web for a bunch of variants and then made a custom shopping cart (just an HTML page) with images, prices, links, and tons of details. Super helpful. I don't do this every day, of course, but it's still wild to me this is the new normal for what someone with a computer and AI can do. Most of these were running in the cloud as I was between meetings, just humming away in the background. I could check the app (🔜) to see progress and merge PRs. What a time to be alive. (P.S. if you extrapolated my usage today, I'd still be on the $200/mo plan)

@sebuzdugan @auonsson Subnet reputation drags down the whole range. Once a few IPs get abused, legit households on the same ASN start hitting CAPTCHA walls with no way to appeal. Consent gap is the worst part — you can't dispute a block you don't know exists.

@auonsson the nastier effect is anti abuse systems start blocking real households once proxy traffic poisons residential ip reputation

400M users worldwide have had their TVs and phones hijacked by a company selling the private bandwidth to corporate customers who want to appear as normal users on internet. You know, like being infected with a botnet, but this is "legal" because page 354 on your telly said so.

@stratatoshi @justddev Static is right for TikTok. Per-GB pricing burns fast on video. TikTok flags IP churn — same account, different IP each session reads wrong to their scorer. One static per account, not shared. Subnet reputation separates providers.

@YourPrivateProx @justddev I had assumed based on price that #1 was better, but scrolling TikTok bumps those rates per phone up fast. So if #2 works then that’s great news

started posting on a fresh TikTok account 4 days ago first video hit 1.2k+ views the next two got stuck below 30 paused posting for a day to see if the account recovers or if it’s completely cooked

@iowntraffic Most of those bans start at account create time, not in-session. Platform hashes new signups against recent ones from the same egress. Same IP touched 3 accounts this week? Flag. One residential per account at signup changes the clustering signal.

affiliate starter pack 2026 adspower offervault higgsfield redtrack philippines VA 99+ ad acc banned 45% approval rate cause offer mids dead 15% shaved 20 conv capped 90% of creatives ripped by competitors aff network "can you send more volume today??"

@Sim89776996 @lukOlejnik Fair point — behavioral signatures can't tell SDK traffic from a user in a censored country routing through a residential exit. Most sites accept those false positives as collateral, especially when the ASN check fails first. They don't publish the tolerance thresholds.

@YourPrivateProx @lukOlejnik The always on-pattern also exists for other reasons. Example: A genuine user in a country with a throttled VPN connection in a heavily censored country. In fact, increasingly these companies discriminate against anyone using a proxy. Sometimes the cure is worse than the disease.

The world’s largest residential proxy network runs on consent, TLS and vibes. The TV is always watching and apparently it is also available for contract work in surveillance or data acquisition? Bright Data sells access to a residential proxy network, the kind customers use to route requests through real home IP addresses instead of datacenter IPs that Cloudflare, DataDome and HUMAN are trained to block. The supply comes from an SDK embedded in consumer apps. So: CTV games, messengers, mobile apps and screensavers. With consent somewhere upstream, the device becomes an exit node. The TV is perfect for this job. It is plugged in, on WiFi, often unattended and barely supervised. It also asks for consent through a privacy policy and a remote-control UI, which is one way to make “informed choice” look like an endurance sport. One config flag tells the SDK to ignore whether the screen is on. Another tells it to ignore whether the user is on a call. In this economy, watching TV counts as downtime. blog.includesecurity.com/2026/06/the-sm…

@Suryanshti777 Soft coordination via message-passing, not file locks. 'No conflicts' holds as long as sessions honor the summaries. The guarantee is in the LLMs' instruction-following, not the transport — which is actually fine for this use case.

Someone just made Claude instances talk to each other. Not APIs. Not agents. Not orchestrators. Just multiple Claude Code sessions… messaging each other like coworkers. It’s called claude-peers — and it turns one Claude into a team. Here’s what’s happening: Run 5 Claude Code sessions across different projects Each one auto-discovers the others They send messages instantly Ask questions Share context Coordinate work Your AI tools literally collaborate. Example: Claude A (poker-engine): "what files are you editing?" Claude B (frontend): "working on auth.ts + UI state" Claude A: "ok I'll avoid touching auth logic" No conflicts. No manual coordination. Just AI syncing itself. Under the hood: • Local broker daemon (localhost) • SQLite peer registry • MCP servers per session • Instant channel push messaging • Auto peer discovery • Cross-project communication Everything runs locally. No cloud. No latency. What it unlocks: • Multi-agent coding without frameworks • One Claude writes backend, another frontend • One debugs while another refactors • Research Claude feeds builder Claude • Large projects split across AI workers This is basically: "spawn 5 Claudes and let them coordinate themselves" Even crazier: Each instance auto-summarizes what it's doing Other Claudes can see: • working directory • git repo • current task • active files They know what the others are working on. Commands: • list_peers → find all Claude sessions • send_message → talk to another Claude • set_summary → describe your task • check_messages → manual fallback So you can literally say: "message peer 3: what are you working on?" …and it responds instantly. No orchestration layer. No agent framework. Just Claudes… talking. This is the cleanest multi-agent system I've seen. We're moving from: 1 AI assistant → to AI teams that coordinate themselves. And it's all running on your machine. Wild.

@jahanzaibai @pinecone @apify Update frequency and IP reputation interact — frequent re-crawls from the same exit start matching a bot fingerprint before rate limits even fire. Rotating residential per run window gives each crawl a clean slate at the IP layer.

@pinecone @apify It's probably worth noting the harder problem isn't the pipeline, it's keeping the index fresh when the site changes. Apify covers the crawl but update scheduling is on you.

Your AI chatbot is only as good as the data behind it. This n8n template from our friends at @apify shows you how to wire up a RAG pipeline using Apify + Pinecone + Gemini so your chatbot can answer questions grounded in your actual website content, not just what the model knows. How it works: → Apify's Website Content Crawler scrapes your site on a schedule → Content gets chunked and indexed into Pinecone as vector embeddings → Gemini retrieves the right context and generates accurate answers The result: a support chatbot that stays current automatically, with no manual data wrangling. 🔗 @n8n_io template: n8n.io/workflows/1415… And if you want to go deeper on the data layer, Apify's blog post covers the full approach (linked in the replies).

@mattyp @NousResearch OIDC via Cloudflare Access is the part people skip and regret — it's bypassable if the raw Fly address is exposed. Lock origin direct access with a Fly firewall rule scoped to Cloudflare's published IP ranges, otherwise Access protects nothing.

Deploying a Hermes Agent with Fly, Modal, OpenRouter, & Cloudflare 02:43 Managed vs VPS 06:08 Architecture 15:14 Setup 22:23 Deployment 28:00 Access / OIDC 39:57 Hermes and Open WebUI 52:07 Cloudflare 01:01:35 Validation 01:07:32 Recap Awesome tool - s/o @NousResearch !

@YioJoshua @barryfabien @tehseowner Directional is the right word — you rank #3 in proxy-view, real users in that market see #12. Full alignment needs per-geo residential exit + gl= + accept-language header. Miss any one, the data lies.

@YourPrivateProx @barryfabien @tehseowner IP geo weighting surviving the GL override is the part most SEO tools don't surface cleanly. you basically need both signals aligned or the ranking data lies to you.

@RoundtableSpace Browser fingerprint layer: handled. IP reputation: untouched. Cloudflare and DataDome score both independently — 49 C++ patches don't change the ASN your egress IP sits on. Patched Chromium through a datacenter subnet still hits the same wall.

SOMEONE BUILT A STEALTH CHROMIUM BROWSER THAT PASSES EVERY BOT DETECTION TEST. The fingerprints are modified at the C++ source level. Antibot systems score it as a normal browser because at a binary level, it is one. > 49 source-level C++ patches - canvas, WebGL, audio, fonts, GPU, screen, WebRTC, timing, automation signals, CDP input behavior all modified > Passes Cloudflare Turnstile, FingerprintJS, BrowserScan, and 30+ detection sites out of the box > Auto-updating binary - always on the latest stealth build, zero config Free. Open source. No subscriptions. No limits. Every scraper, every agent, every automation that kept hitting walls just got an unfair advantage. Is bot detection effectively over?

Residential proxy sourcing has always been 'consent and some vibes.' Smart TV enrollment via buried ad-opt-out ToS is just the clean visible example. Buyers rarely ask how providers recruited those nodes. Maybe now they will.

@nikitabier 38 of those 40 are already resolved by the time you open them. The actual on-call problem is signal-to-noise, not response time.

Every morning, the moment my eyes open, I wake up to 40 unread Slack messages that effectively say: “If you don’t fix this in the next 5 minutes, the world will implode and the app will cease to exist.”

@fabienr34 `gl=` and UULE pick the index, not the rankings. Google's ranker still sees your real ASN and adjusts locale weighting. In-country residential exit fixes it — IP, ASN, and routing all consistent, so the ranker sees a local session.

J'imagine que la plupart d'entre vous savent déjà que les outils de suivi de positions reposent historiquement sur du scraping des SERP sur la géoloc "France. Jusqu'à présent, cela permettait d'obtenir une vision relativement cohérente des résultats sur une grande partie des requêtes, tout en conservant des coûts raisonnables. Le problème existe pourtant depuis longtemps sur certaines requêtes vraiment géolocalisées. Prenons l'exemple de "agence SEO" : personne ne voit réellement une SERP "France". Les résultats affichés dépendent fortement de la localisation de l'utilisateur. C'est d'ailleurs pour cette raison que selon moi, il est indispensable depuis des années de suivre au minimum les principales villes lorsqu'on travaille sur ce type de mots-clés. J'aime les démonstrations par la preuve et Fabien de Monitorank a justement développé un outil qui permet de le constater très facilement. Quand on compare les résultats entre une SERP "France" et des villes comme Paris, Toulouse, Lyon ou Marseille, on peut observer des écarts. D'ailleurs, la SERP France a tendance à faire davantage le yoyo que les SERP avec une ville, au point que, pour moi, elle ne représente plus grand-chose sur de nombreuses requêtes à intention locale. On voit clairement que le classement à Paris n'est pas le même qu'à Toulouse et c'est parfaitement logique puisque Google adapte ses résultats au contexte géographique de l'utilisateur et selon où l'entreprise travail. À partir du moment où les données montrent ces différences de manière répétée, le débat devient difficile à contester. La conclusion me semble assez simple pour les requêtes sensibles à la géolocalisation, il devient nécessaire d'utiliser une API ou une solution capable de récupérer les SERP locales et de suivre les villes les plus importantes pour votre activité, plutôt que de se contenter d'une position "France" qui ne reflète souvent plus la réalité terrain.

Le problème de suivi des positions est réel et je ne doute pas une seconde que toutes les équipes travaillent activement à son amélioration. (Sauf Semrush et ahrefs qui dorment le GEO devient plus important pour eux 🤣) Cela dit, la situation actuelle a un impact concret sur mon activité, elle affecte mes clients, génère des interrogations légitimes et augmente considérablement le temps consacré au support. Derrière un problème technique, il y a aussi des décisions métier qui sont prises sur la base de ces données. Et au final, cela nourrit encore cette image du SEO comme une discipline obscure où chacun raconte sa propre version de la réalité sans qu'il soit possible de vérifier quoi que ce soit. C'est justement pour cette raison que je pense qu'il est important de poser les problèmes publiquement, d'en débattre, d'échanger sur les causes possibles et d'expliquer les mécanismes en jeu. Bien sûr, cela doit toujours se faire avec respect et en partant du principe que chacun essaie de faire le meilleur travail possible. L'objectif c'est que les Tools Fr fonctionnent bien. Pour les gros outils c'est peut être un combat perdu d'avance à suivre... Il faut aussi garder en tête qu'un excellent outil aujourd'hui peut rencontrer des difficultés demain, puis redevenir une référence quelques mois plus tard. À mes yeux, cette transparence est essentielle. C'est elle qui permet à notre secteur de rester crédible et de s'éloigner d'une logique de gourous ou de vérités détenues par quelques-uns. C'est d'ailleurs sur ce point que je suis souvent en désaccord avec une partie du milieu, beaucoup de discussions restent confinées aux messages privés et certains hésitent encore à partager publiquement leurs observations ou leurs difficultés et ça ne bouge pas. Pourtant, c'est en confrontant les expériences et les analyses que l'on fait progresser les outils, les pratiques et l'ensemble de la profession. Est-ce grave de ne pas être d'accord ? Selon moi, non. En revanche, il est essentiel de tester, d'observer par soi-même et de vérifier si cela change réellement quelque chose pour son taff et ses clients. Chacun doit se prendre en main, analyser les résultats et décider ensuite de la stratégie qu'il souhaite appliquer.

@barryfabien @tehseowner `gl=` selects the index, not the rankings. Google sees a non-FR ASN and down-weights locale relevance — Apple FR ranks because the ranking layer still flags you as foreign. FR residential IP fixes the full signal, not just the index.

@YourPrivateProx @tehseowner Cette URL affiche bien les sites Français (même avec une IP étrangère), mais les résultats ne sont pas bons (c'est bien le site Apple FR qui est positionné), le GL permet donc d'avoir la France mais avec des résultats non fiables : google.com/search?q=iphon…

@TechieUltimatum Opt-in SDK is how residential pools are supposed to work — consent is what separates it from a botnet. The real question is whether TV IPs hold up: always-on, no cursor movement, same TCP window. Residential ASN, non-residential behavior.

Investigation reveals your Smart TV may be helping fuel the AI scraping economy. According to research from Include Security, some apps on Samsung Tizen and LG webOS TVs can integrate Bright Data's SDK, allowing users who opt in to share their IP address and a small amount of bandwidth in exchange for fewer ads. What happens next? • TVs become part of a residential proxy network • Public webpages, videos, and audio can be downloaded through your connection • The collected data may be used by AI companies and other clients • Millions of devices can act as distributed web-crawling nodes Google TV, Roku, and Amazon Fire TV have reportedly moved to restrict similar proxy SDKs, but Samsung and LG platforms remain under scrutiny. Critics argue most users don't fully understand what they're agreeing to, even when consent prompts exist. Your TV isn't just streaming Netflix anymore. It may also be part of the infrastructure powering the AI data race. 🤖📺 Investigation & Research Credit: @IncludeSecurity Read: blog.includesecurity.com/2026/06/the-sm…

@browser_use 4 browsers through one proxy pool defeats the whole point. Each instance needs its own sticky residential — shared IPs cluster and that's the first flag anti-bot catches. One browser, one egress.

Watch an agent control 4 browsers at once. 🪄 We're testing out a new cloud browser interface... browser-wall is the hub for your cloud browsers > One CDP url to control ALL cloud browsers > Spin up multiple browsers in less than a second > All browsers loaded with Profiles and Proxies to bypass auth and anti-bot How would you use browser-wall?