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Reddit Issues Reports

Latest outage, problems and issue reports in social media:

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  Ray Myers (@TheRayMyers) reported 4 minutes ago

  @ariaradnia The problem is sustainability, I don't think this is sustainable. I believe US DAUs decreased last quarter. Reddit is turning into AI slop machine, and that makes it less relevant for LLMs as a data source. I don't buy it that there is another huge contract coming their way. I don't like their product as a user.

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  Baroque Naturalist 🫒 (@baroquerational) reported 11 minutes ago

  @SYNESTHEIZURE @pannekook I'm too honest with myself, that's the problem. I don't like having to pretend to believe in dogma just to fit in with others. All my social views are based on what I think makes sense, not on what contrapoints or reddit say. That's why your views are incoherent and mine arent.

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  OrcXtreem (@OrcXtreemo) reported 12 minutes ago

  Pretentious bullshit niggеr fаggot. "Oh no! I won't be peaking into this colorful book of many visual stories. No-no! I don't want to touch this game and its many buttons. I do not want to consume that cartoon/movie/series! This is for manchildren plebs *******! I'm with the Ceaser. I'm with the Hitler. I'm ABOVE ALL OF YOU." God. What a ******* ******. The same fаg as Walsh with his "men should work and stop being infantile children with many hobbies" when he himself ******* sits on his *** doing nothing but talks to the camera so his content would be consumed by people, he wants not to consume content and go to the woods frolic with the wind in a field of flowers or melee a bear/moose or something. Reality is not medieval anymore. You aren't living in the woods. The times is now forcing you to seek help. And when help is taken away by foids, government, jooz, niggеrs and other "social economic factors" men can't go anywhere and do anything. So, they must seek help in other "media" and there are MANY medias that can help with this. You don't need to be a NECKBEARD FAT REDDIT NERD, but it's okay to have a hobby: games, comics, handywork, even knitting is good. Yes, you can go frolic into the field. Yes, you can go to the woods and read many books. But looking down on people who immerse themselves into fantasy of OTHER media you deem "unworthy" is lame and ***. Sometime ago people looked down on frolicking plebs while participating in grand ***** (he said *****) and dancing with elites. I'm working in gamdev my whole life and there are many people incredible: physically and mentally. They read and they can create and they still play games and read comics, manga and do all kind of silly nonsense in spare time. Don't be like this fаggot and lock yourself into something that HE forces you because HE THINKS PERSONALLY that it's not cringe. Nobody owes anyone anything. Do your own ****, just don't ****** kids and don't be a fаggot trаnny.

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  heated rivalry anti 🦈 (@imaloteveryday) reported 14 minutes ago

  this just being a coke rant of reddit twitter terms. this is because none of your problems exist in real life

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  Akari Rini 🌐⭐ (@akaririnii) reported 16 minutes ago

  @Necromel211736 i aspire to be as tech savvy as you one day!! random reddit tech problem forums are my savior

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  yakub's top guy (@tricknologics) reported 20 minutes ago

  @zoomerwoman Sometime in mid-2021 her Instagram page was deleted, which she believes was due to hackers/report spammers. She stopped doing Onlyfans after this, got pregnant, converted to Catholicism, got married, and settled down to have kids. She says she was engaged at the time but it's not clear if her husband was aware of the Onlyfans. In a comment on Reddit she says that she's ethnically Jewish. She now identifies as a Groyper.

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  James Altucher (@jaltucher) reported 21 minutes ago

  There are two primary bottlenecks to today's AI. And solving these bottlenecks is where the money is right now. A) DATA - the big models have ALL the data already. All the texts, videos, reddit posts, tweets, etc. How can they get more data? Other than the natural daily creation of new data the biggest repository of UNUSED data is behind the corporate firewall. Whoever can unlock the data behind the firewall will create a model bigger than anything OpenAI can do. The key is this: corporate data does not want to be free (competition reasons or even legal reasons in the case of healthcare) So the method has is decentralized learning techniques where AI trains locally inside the firewall, and then shares its weights (but not the data that created those weights) to an AI model that stitches this together. This is where $TAO is the best in the world and at a $2.5B value is cheap. B) CONNECTIVITY = POWER. Everyone is complaining about power. But people don't realize that the power problem is really a connectivity problem. 100,000 GPUs in a data center means a million or more copper / electricity interconnects connecting them all. Change that from electricity to MicroLEDs and you wll use 1/30 of the power. Problem solved. Who is doing this? $MRVL $ALAB $FABC $KOPN

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  liquidated (Dev Arc) (@liquidated0x) reported 24 minutes ago

  @pfernan95dev distribution is your whole bottleneck fr. most agencies are just dashboards with extra steps been down this road, the agents that can push reddit and seo content without a dashboard barely exist yet. you might be onto something

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  Keith Zhai (@KeithZhai) reported 25 minutes ago

  @michael_kove @victor_bigfield reddit on a schedule is a mean test. usually a login page pretending to be a thread. curious what you get tonight.

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  IamLeo (@ImLeoRey) reported 29 minutes ago

  @Techjunkie_Aman This is terrible news, nexusmod has become tyrannical and toxic, it's like the reddit of mods.

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  Amin (@eCom_Amin) reported 29 minutes ago

  fable 5.1 is insanely CRACKED at finding winning google ads angles to scale your brand past $1m/mo research capacities literally DOUBLED so here's every prompt you'll need to reverse-engineer competitors' funnels and rip some banger gads: (actually run them all rn, don't just bookmark) 1. load the brain before you ask it anything the research is only as sharp as the context. upload: - pdps - reviews - website - funnel pages - competitors - report CSVs - brand docs - ICP info - winners - losers literally everything then run this: "act as the angle research lead for this brand. read everything uploaded and build a working profile: ICP segments ranked by revenue, the pain points in the customer's own words, the objections ordered by how often they appear, the proof we already own, and the beliefs a buyer must hold before purchasing. do not propose angles yet. summarise what you found, then tell me what context is MISSING" that last instruction is the whole game. prompt engineering is cope just have claude tell you what he needs from you and give it to him. anybody who disagrees just loves to overcomplicate things. 2. mine untapped databases that semrush misses prompt: "search reddit threads, quora answers, amazon reviews and Q&A sections, youtube comments on competitor and category videos, tiktok comments, trustpilot, and niche forums for people discussing [PROBLEM CATEGORY]. extract VERBATIM language, never paraphrase. for each goldmine you find, give me this: the quote, the pain underneath it, what they already tried, why it failed them, the outcome they want, and the emotional state behind it" paraphrasing is how angles end up sounding like ai slop. the whole value is in knowing your ICP's EXACT words and repeating them on ads. 3. reverse engineer every competitor funnel end to end "research [COMPETITOR 1, 2, 3]. use google ads transparency center, meta ad library, their landing pages, checkout flow and email capture. for each: every live ad and where it routes, the landing page TYPE, the hero promise, the mechanism they claim, the proof they lead with, the objections handled and in what order, the offer and guarantee, and what they are NOT saying" then: "for each competitor page, tell me which awareness level it was built for. then identify which of their traffic is landing on the wrong page type" this is how you find gaps in your competitors strategies that you can capitalize on 4. diagnose market sophistication BEFORE choosing an angle this is the step 9 out of 10 brands skip and it decides whether your angle has any chance: "assess the market sophistication level for [CATEGORY] using schwartz's 5 stages. analyse competitor ads and landing pages as evidence. stage 1 means nobody has made the claim yet. stage 2 means claims are escalating. stage 3 means mechanism differentiation has started. stage 4 means mechanisms are competing. stage 5 means the market is exhausted and identification wins. tell me which stage we're in, the evidence, and what type of angle still works at this stage" if your category is at stage 4, a bigger promise does nothing. every competitor already made one. if you're operating in stage 5, the mechanism is exhausted too, and the strategy has to shift again your ad is only good if it resonates with the market it operates in 5. score every angle against awareness and funnel stage "from the research, generate 15 google ad angles for my brand. for each: the awareness level it serves, the funnel stage it belongs in, the sophistication stage it's valid at, whether it's validated by competitors or white space, the proof required to run it, and the funnel type it should be tested through. rank by expected impact and flag any we lack proof to support" an angle without proof is a claim. claude will rank those last 6. map the keywords to the angles, not the products "build the keyword universe for [BRAND] using the customer language and competitor research. split into branded, competitor, problem-aware symptom queries, solution-aware category queries, comparison, use-case, and occasion. tag each with awareness level, the angle it pairs with, the funnel type it routes to, and the campaign that should own it" this will make everything nice and organized 7. turn the research into the campaign plan "turn everything above into a 30-day google ads launch plan for this specific brand, its AOV, margin structure and market sophistication stage. for each campaign, give me: the angle it carries, the keyword cluster, the landing page type, the creative direction, and the signal that decides whether it scales, holds, or gets cut. separate must-launch from phase 2 tests" then: "tell me which 3 angles to test first and why, given our sophistication stage and the proof we currently own" and that's literally it your competitors are testing angles with fat budgets while you analyze it all, learn from their mistakes, and (ethically) rip their winners with a unique twist and if you want me to audit your brand's google ads angles using this system and show you how we'd capitalize on the winning ones... DM me "OPP"

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  Justinas Rolando (@JustinasRoland0) reported 29 minutes ago

  Been testing Claude Fable 5.1 for Google Ads and gotta say it's cracked... The research, reasoning, and data analysis capabilities literally 10x'd. So here's a 10-stage AI workflow to automate 80% of it: (Literally every prompt you'll need. Save this) Stage 0: Build the project brain Before asking for anything, create a Claude Project and feed it everything. - Product pages - Best sellers - Customer reviews - Objection docs - Competitor URLs - Meta ads - Google Ads Transparency Center links - Search terms reports - Winning ad copy - Offer details - Brand guidelines - Past landing pages - Performance exports Then run this prompt “Act as the Google Ads strategy brain for this brand. Read all uploaded context and create a working brand profile covering: ICP, core pain points, buying triggers, objections, emotional language customers use, top products, strongest offers, competitor positioning, current funnel gaps, and Google Ads opportunities. Do not make recommendations yet. First summarise the context and ask me what is missing.” The quality of the outputs you’ll get from this AI workflow will directly correlate with the quality of the context you give it here. And also the quality of the Claude model you use, since newer models have more context tokens and better reasoning skills. Stage 1: Customer language mining “Search Reddit, YouTube comments, Amazon reviews, TikTok comments, and niche forums for people discussing problems related to [PRODUCT CATEGORY]. Extract the exact words they use when describing the problem, what they have tried, why those solutions failed, what outcome they want, and what would make them buy. Format this as: Quote / Pain Point / Desired Outcome / Funnel Stage / Possible Ad Angle.” This gives you the language that keyword tools would never show you. If someone writes: “I’m tired of wasting money on supplements that do nothing.” That can be a winning ad angle right there. Stage 2: Competitor angle map “Research these competitors: [COMPETITOR 1], [COMPETITOR 2], [COMPETITOR 3]. Use Google Ads Transparency Center, Meta Ad Library, their landing pages, product pages, offers, guarantees, reviews, and email capture flows. Build a table showing: offer, main promise, ad hooks, landing page angle, proof used, objections handled, pricing position, and what they are NOT saying.” Then run: “Based on this competitor research, identify the 5 most validated market angles and the 5 biggest white-space angles we can own. For each angle, explain which funnel stage it belongs to and what campaign type should test it first.” If 3 competitors are all running the same hook, that angle is validated. You don’t even need to be original. Just add your unique spin to what’s already working. Stage 3: Keyword research “Using the customer language, competitor research, product pages, and search intent data, build a full Google Ads keyword universe for [BRAND]. Split it into: branded, competitor, high-intent product, problem-aware, solution-aware, comparison, ingredient/material, use-case, gift/occasion, and negative keywords. For each keyword, include funnel stage, intent level, match type, campaign/ad group recommendation, and landing page angle.” Then run: “Now prioritise this keyword research report into a 30-day launch plan. Separate must-launch keywords from phase 2 tests. Flag any keywords that are high volume but low commercial intent.” This stops the campaign from becoming a messy keyword dump. Stage 4: Campaign architecture “Turn the finalized keyword research report into a complete Google Ads account structure. Include campaign names, ad group names, keyword match types, bidding strategy, starting budget split, exclusions, negative keyword rules, and when each campaign should launch. Use this structure: branded search, branded shopping, non-branded shopping, non-branded search, competitor search, PMax remarketing with brand exclusions, display remarketing, Demand Gen, and TOF search tests.” Then add: “Explain why each campaign exists, what signal it is meant to produce, and what metric decides whether it scales, holds, or gets cut.” Every campaign needs to play a role in your ecosystem. If it doesn’t, you should just stop running it. Stage 5: RSA copy production “Write responsive search ad copy for [PRODUCT] targeting [KEYWORD]. Funnel stage: [BOF/MOF/TOF]. Use the customer language and competitor gap analysis above. Give me 15 headlines under 30 characters and 4 descriptions under 90 characters. Include: benefit-led headlines, problem-led headlines, proof-led headlines, offer-led headlines, and urgency-led headlines. Make sure headline 1 matches the search intent.” Then run: “Create 3 ad variations for this keyword: one direct-response version, one proof-heavy version, and one problem-agitation version. Explain which audience each variation is for.” BOF copy should sound like the product is the obvious answer. MOF copy should make the benefit feel believable. TOF copy should make the problem impossible to ignore. Stage 6: Merchant Center feed optimization “Rewrite this product title for Google Shopping using the structure: Brand + Product Type + Core Keyword + Key Feature + Use Case/Benefit. Stay under 150 characters. Give me 10 variations ranked by likely search intent.” Then: “Write a Merchant Center description for [PRODUCT]. Use up to 5,000 characters. Include all relevant buyer keywords naturally, cover features, benefits, use cases, materials/ingredients, sizing/specs, objections, and reasons to choose this product. Do not include irrelevant keywords or products we do not sell.” Then: “Audit this product feed for missed Google Shopping opportunities. Check title, description, product type, Google product category, images, variants, pricing, promotions, shipping, reviews, and attributes. Tell me exactly what to change.” Stage 7: Landing page angles “Build a landing page brief for [PRODUCT] targeting people searching [KEYWORD]. Awareness stage: [PROBLEM-AWARE/SOLUTION-AWARE/PRODUCT-AWARE]. Structure it as: hero headline, subheadline, proof bar, problem section using customer language, mechanism section, product section, comparison section, reviews, objection handling, FAQ, CTA. Make sure the first screen matches the search query.” Then run: “Create 5 landing page angle variations for this product based on different search intents. For each one, give me the hero, core promise, proof required, objections to handle, and CTA.” Send the best one into Claude Code. Now you have an intent-specific page created instead of 1 generic PDP trying to convert everyone. Stage 8: Creative production Connect Higgsfield MCP inside Claude. Then run: “Create a 9-shot YouTube ad concept for [PRODUCT] based on this angle: [ANGLE]. Style can be claymation / UGC / cinematic product demo. For each shot, include scene description, voiceover, on-screen text. Use GPT Images 2.0 for the statics.” Then: “Create 5 new creative concepts from the strongest customer pain points in the research. Each concept should include hook, visual metaphor, script, image prompts, animation prompts, and CTA.” If you wanna run video ads, animate your statics with Seedance 2.5 Use Fable to write the scripts. Shouldn’t cost more than $3 per ad. Stage 9: Daily campaign audit Connect Google Ads MCP (or just export report CSV) Then run: “Pull the last 7 days of Google Ads performance and compare it to the previous 7 days. For each campaign show spend, revenue, ROAS, conversions, CPA, CPC, CTR, impression share, search lost IS rank, search lost IS budget, and top search terms. Flag: ROAS down 20%+, CPA up 20%+, budget-limited winners, rank-limited campaigns, branded leakage in non-branded campaigns, wasted spend queries, and products spending with no conversions.” Next up: “Turn this audit into an action list. For each action, include the campaign, issue, evidence, recommended change, risk level, and expected impact.” Stage 10: Weekly scaling plan “Compare performance across 7, 14, and 30-day windows. Identify campaigns, products, keywords, ads, and landing pages with consistent green signals. Recommend which budgets to increase by 15-20%, which to hold, which to decrease, and which tests to launch next. Do not recommend scaling anything unless the signal is consistent across multiple windows.” Then: “Create next week’s testing roadmap. Include 3 keyword tests, 3 creative tests, 2 landing page tests, 2 feed tests, and 1 campaign structure test. Rank them by expected impact and implementation difficulty.” And this is how you get your full ecosystem set up: - Research feeds keywords - Keywords feed campaigns - Campaign data feeds landing pages - Landing pages feed creative - Creative feeds new angles - Audits feed the next week of tests If you want me to build this full AI Google Ads production system for your brand btw, DM me “FABLE” and I’ll show you what it’d look like

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  ^ (@Oct27_x) reported 34 minutes ago

  @Ntr1166177 *Typo error ( Reddit rumours are true )

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  ☦️🇦🇺 (@AngloOrthodox22) reported 36 minutes ago

  @kylantisfeniks0 Reddit is down the hall and to the left

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  Saulthis445 (@Mass3279) reported 37 minutes ago

  @libertybelleX47 @brndxix Reddit is down the hall and to the left