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Reddit is a social news aggregation, web content rating, and discussion website. Reddit's registered community members can submit content, such as text posts or direct links.

Problems in the last 24 hours

The graph below depicts the number of Reddit reports received over the last 24 hours by time of day. When the number of reports exceeds the baseline, represented by the red line, an outage is determined.

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Most Reported Problems

The following are the most recent problems reported by Reddit users through our website.

  • 43% Website Down (43%)
  • 30% Errors (30%)
  • 27% Sign in (27%)

Live Outage Map

The most recent Reddit outage reports came from the following cities:

CityProblem TypeReport Time
Patna Errors 4 days ago
Monclova Sign in 5 days ago
Nice Errors 6 days ago
Guayaquil Errors 16 days ago
Veracruz Website Down 21 days ago
Bhubaneshwar Website Down 24 days ago
Full Outage Map

Community Discussion

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Reddit Issues Reports

Latest outage, problems and issue reports in social media:

  • FormlessE
    formless_electrons (@FormlessE) reported

    @DoctorLoops Reddit mods are like janitors. But unpaid and usually have terrible social skills.

  • GODFOE_UNIVERSE
    GODFOE UNIVERSE (@GODFOE_UNIVERSE) reported

    This tired 20th century psychoanalysis is just laughable. These “weak people” escaped slavery, crossed the desert, conquered a foreign land for hundreds of years, and kept the documents about it; preserving their identity so well against the Assyrians and Romans you’re still mad about them today. Now tell me, which angle of Jew-sperging are we taking here? Is it “Christianity is a Jewish religion”? If so, that religion conquered the gods of Homer and the lands of Odin, just not entirely the way poor ol’ Nietzsche liked with his made up system of beliefs that magically served what he liked and condemned what he didn’t like. The problem you’ll have with Nietzsche is the same he had with himself, there’s no means to ground his ideas of morality so they drift off into Reddit levels of cope. You don’t have to like Israel dude, but at least bring something other than ideas that were laughable over a century ago.

  • hello_code_
    John (@hello_code_) reported

    @rcmisk matches what I've seen, the backlink is the actual product, the launch day traffic is just a nice side effect nobody plans around. reddit threads where people already describe the problem convert way better than PH upvote traffic ever did

  • FINTECHTVglobal
    FINTECH.TV (@FINTECHTVglobal) reported

    Today's @NYSE Notables with @JD_Durkin: 🟢 Reddit $RDDT +9.31% bouncing back on institutional accumulation after its S&P 500 addition, still down 33% year to date

  • anzedetn
    Anze Markovic | Performance Creative (@anzedetn) reported

    Sometimes the best-performing line in an ad isn’t the hook. It’s the line 20 seconds later that describes the customer’s exact experience: “I wake up, and my ankles look almost normal. Then I spend a few hours standing, and by 3 PM my shoes feel tight, my skin feels stretched, and I’m quietly wondering how I’m supposed to get through the rest of the day.” That level of specificity usually comes from Reddit research. It takes time to dig through the posts, comments, and oddly specific complaints people share when they think nobody is listening to them. But our team loves it. Because that’s where you find the emotional details customers rarely say in a survey: The embarrassment of avoiding sandals. The frustration of pressing a finger into swollen skin and watching the mark stay there. The anxiety of planning your day around when your legs will start aching. Specific recognition keeps people watching because they don’t just understand the problem. They feel seen.

  • qui_crescent
    QuiescentCrescent (@qui_crescent) reported

    It's just very funny to me how positively tame whatever personal drama he has going on is compared to the gangbanging and serial killing of all the thug rappers reddit fellates. All performative, all the way down.

  • LaFawndah
    ❁Fat *** Kelly Price❁ (@LaFawndah) reported

    @nicole07133 @00MF0E She started taking IG post down when Reddit began picking up on just how much she contradicts herself.

  • doomzday_zone
    Al🍺🚬 (@doomzday_zone) reported

    there are postal fans who will acknowledge that hes just kind of a nasty prick but theyre all on reddit and they have their own problems, mostly being disregarding that postal dude has any characterizing elements about him at all that isnt just 'player insert'

  • BriocheGenie
    Bread Goblin (@BriocheGenie) reported

    @itzTizzleYT it's his fault when he literally doesn't experience the things he writes about. he sees a reddit comment and desperately tries to hit word count for Forbes. he doesn't play the game, he needs to stop talking about its issues like he does

  • Unruly_Crow
    UnrulyCrow🇺🇦🇵🇸✊️ (@Unruly_Crow) reported

    @_kodiakinclouds This is why I checked out from it (and fandoms in general). This behaviour has been happening for years now, even in 2020 when Twisted Wonderland got released, I quickly noticed this issue. In the 2010s I saw it on Tumblr and Reddit, it made me actively avoid certain fandoms.

  • TheIfunanya
    Ifunanya from TechOps (@TheIfunanya) reported

    @Ooreoluwa__ Used it in the first few weeks then someone told me to be careful because there’s been issues with it making bottles with wrong formula and water ratio. Then I went down a rabbit hole on Reddit and saw parents saying it landed them in the ER so I just stopped 🥴

  • mdemt
    Bmore73 (@mdemt) reported

    @ErimhanAhmet May 2024 — Former sailor’s photos called “worse than prison” A former Navy worker shared mess-hall photos on Reddit (raw-looking chicken, questionable brown meat, pink hotdog, moldy bread). Commenters included veterans from the 1990s who said shipboard food was “really quite awful,” greasy, and off-tasting. Covered by The Mirror.  Longer-term context from reporting: Sailors have long described repetitive menus, declining quality after fresh produce runs out (often within the first couple of weeks), and reliance on personal snacks, protein powder, and ramen to supplement. Midnight rations (“midrats”) were frequently cited as especially sparse leftovers. Ships returning to port rusty after long deployments October 2020 — USS Stout (DDG-55) after 215 consecutive days at sea The destroyer returned to Naval Station Norfolk looking heavily rust-streaked and weathered after a record 215 days without docking (COVID restrictions prevented port visits). Photos circulated widely showing rust patches on the hull. Daily Mail and later Naval News / NAVSEA coverage noted the rust was removed and the ship repainted after return. NAVSEA later used the Stout photo as an example of high operational tempo plus saltwater corrosion.  December 2021 — Broader “Navy is rusting away” reporting Task & Purpose published photos of multiple ships showing rust after deployments, including USS Arleigh Burke, USS Fort McHenry, USS James E. Williams, and USS Zumwalt, plus the 2020 Stout return. The piece attributed it to a “crushing deployment cycle” that left little time for preservation work.  2018–2019 examples and analysis • USS Curtis Wilbur drew comments for a “rusty and shabby appearance” during a 2018 Hong Kong visit. • 2019 Defense News “Rust Dialogues” discussed why U.S. ships often look rustier than allied ships: American vessels stay at sea longer with fewer port visits for chipping and painting. A 2005 photo of USS Normandy mid-deployment was contrasted with later, rustier ships. Corrosion control was already a multi-billion-dollar annual cost.  2023 NAVSEA statement Naval News quoted NAVSEA on rusty ships: high operational tempo + steel + seawater = rust staining wherever coatings are scratched. Crews do preservation at sea, but it is balanced against operations. The Stout 2020 photo was referenced again.  Rust after long deployments is treated by the Navy as expected cosmetic wear from saltwater and limited time for topside work while underway; it is usually addressed after return to port. Food complaints have been a persistent sailor grievance for decades, especially once fresh stores are gone and the 21-day repeating frozen/canned menu takes over. Both issues tend to surface most visibly after unusually long or high-tempo deployments with few or no port calls.

  • finngalkn
    finngaalkn 🏳️‍⚧️🏳️‍🌈🐺#NEVERTrump#NEVERMAGA (@finngalkn) reported

    @beardpandaa I’ve been called “theyfab” and I’m a whole *** binary trans man. Some of those comments about trans men having “privilege” meanwhile over on Reddit r/trans has been completely shut down because a trans masc tried to point out underlying transandrophobia and the entire subreddit

  • om_patel5
    Om Patel (@om_patel5) reported

    grok bot made me exactly $262 today for my startup my entire sales and marketing team is 8 agents in a chat app 1\ lead scout figures out who my buyer actually is based off my existing customers, then goes and finds them pulls the list from apollo (cold leads), watches reddit, x and linkedin for anyone complaining about a competitor or asking for what i sell (warm leads) scores them 1 to 100 and drops anything under 60 2\ outreach engine takes that list and reaches out on whatever platform the lead came from cold emails go through resend, tue wed thu, 7am their local time, 4 emails with a day 3 follow up reddit, x and linkedin leads get a dm or a reply on the exact post that flagged them verifies every address first and rotates the sending domain so nothing lands in spam 3\ cold open writes the opener and does every reply after it it quotes what they actually said so the first line is never generic then keeps the thread going until they book or ghost me 4\ objection handler runs the support chat on my site, wired into my product knowledge base when someone goes back and forth it answers the real question instead of stalling, and kills the objection before it turns into a churn 5\ pricing architect watches which tiers people actually buy, moves prices up and down, and tells me where the money is sitting 6\ deal room the people who are almost there but need a human to close, like someone who wants a demo first it flags them and sends the booking link so i only get on calls with buyers 7\ content engineer writes posts for reddit, x and linkedin that promote the product, plus long form youtube video scripts built to rank on google and get cited by ai everything lands in drafts with ideas and hooks attached 8\ clipper cuts my youtube videos into short form and posts them to tiktok, reels and shorts all i need is one thread that shows me the whole system and it moves whether im awake or not people keep trying to hire a marketing team, but now all you need to do is write down what one actually does and then build it with @bot

  • laqpiku
    Laqpiku (@laqpiku) reported

    @BAcct8 @coinjoined @NeoxaPortal Also the reddit post was by them. They shought to destroy the only place they traded at because 1) Wrong ticker in their mind 2nd) They didnt like the price when market kept slashing it down.

  • technopol_ph
    technopol 🕊️ (@technopol_ph) reported

    @nokkron @ShitpostRock I've been banned there for the most mundane things like my photo's pixel size was too large. They have the ability to scale it down like normal forum moderators do but no not in Reddit.

  • Cushionfinish21
    Cushion Finish (@Cushionfinish21) reported

    @moonlarking @pixaxiq @CH4R10T_TV The easy way to tell is the lack of engagement on the post other than views and likes. You can easily find places that will charge you like 15c for 10 likes with a quick Google search - people use them all the time. It's a huge problem on this site as well as Reddit.

  • tricknologics
    yakub's top guy (@tricknologics) reported

    @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.

  • eCom_Amin
    Amin (@eCom_Amin) reported

    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"

  • kaleighf
    Kaleigh Moore (@kaleighf) reported

    B2B SaaS companies rank well in traditional search but still fail to earn citations in AI search. The fix? Getting experts to post about their knowledge on LinkedIn, YouTube, and Reddit. I built a system to make this programmatic, and it's forged from decade of reporting and vetting sources myself while writing for publications like Forbes, Vogue Business, and ADWEEK. It taught me something that most content strategists never learn: editors and journalists don't cite content, they cite PEOPLE — specific, verifiable, independently credentialed humans with a named point of view and a track record of being right about something.

  • raionxsu
    rai ˖᯽ ݁˖ (@raionxsu) reported

    @jonschxyz @FatiTheDream Hmmm I haven’t tried that before. I say give it a go and hunt down if anyone’s tried it on Reddit

  • JustinasRoland0
    Justinas Rolando (@JustinasRoland0) reported

    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

  • Beta_Knight13
    Beta Knight (@Beta_Knight13) reported

    @JoJo28130026 @theisleofficial You may be in a different server they moderate if you ever got banned somewhere else. Discord mods, reddit mods, all the same tubs of lard

  • colinsechay
    Colin Sechay (@colinsechay) reported

    @PrimeTopNews The Legendary Story: Tom Hanks is sitting at a diner in North Dakota having a beer. A few tables over, some kid is face-down, completely passed out. Hanks walks over to check if he’s okay, sees the guy’s phone sitting on the table, and can’t resist. He has the bartender snap a few photos of himself with the unconscious stranger — one where he’s looking concerned, one where he’s pointing and laughing like he just found treasure — then slips the phone back into the kid’s pocket and leaves. The next morning the guy wakes up, scrolls his camera roll, and finds Tom Hanks photobombing his hangover.  That’s the story that spread on Facebook, Imgur, and Reddit with captions like “Can you imagine finding these on your phone after a drunken night out?” What actually happened A fan ran into Hanks at a diner in West Fargo (Hanks’ niece worked there). The fan’s thing was posing with celebrities while pretending to be wasted. He asked Hanks if they could do it. Hanks said yes, handed over his glasses, and played along while a friend took the pictures. The original Reddit title was literally: “My friend met Tom Hanks, stole his glasses and pretended to be wasted.”  Hanks’ favorite version When a reporter asked him about it in 2013, Hanks gave both stories and then said he preferred the legend: “Well now, that second version is that I did just start taking pictures with a passed-out guy. I’m happy with this version, that it’s become somewhat of a legend. I wouldn’t want anyone not to believe that I am capable of turning up on their phones.” So the photos are real, Hanks really posed with a guy who looks dead-drunk at a diner, and he really used the guy’s phone. He just didn’t do it to a random unconscious stranger. The internet decided the better story was the one where Forrest Gump finds you passed out and photobombs your phone, and Hanks was happy to let that one live. @grok

  • fuckyourputs
    samson (@fuckyourputs) reported

    @SlumDawg21 @theo no, there is no source, they did it quietly. but if you search online you will see no new bans, and people on reddit saying they are un banned after they appealed, some say they remained banned on antigravity only (google account safe) personally and know people who have been using for months with no issue.

  • heyIrfan
    Mohamed irfan (@heyIrfan) reported

    If I had to build a SaaS from $0 today, I wouldn't start by writing code. I'd start by talking to the market. Imagine you have an idea you're convinced will work. You spend 3 months building it, make the UI beautiful, add 20 features, launch it… and then nothing happens. No users. No customers. That's when you realize: building the product wasn't the hardest part. Distribution was. I'd follow a simple rule: roughly 20% of my effort goes into building, and 80% goes into understanding customers and distribution. First, I'd study the market. Who has this problem? How are they solving it today? What competitors exist? What do customers hate about the existing solutions? And most importantly, is this problem painful enough that people will actually pay to solve it? That's actually the approach I'm taking while building nodott(dot)com. I'm not trying to spend months building a huge product and then hoping people show up. I'm trying to build the smallest version that solves the actual problem, get it in front of people, talk to users, collect feedback, and iterate. With AI tools, I'd try to get the MVP working in days, not months. No unnecessary animations. No 50 features. No obsession with perfect UI. Just solve the core problem and deliver value. Then I'd put it in front of real users. I wouldn't act like a salesman. I'd act like a problem solver. I'd ask what they're struggling with, how they solve it today, what they expected from the product, and what would make them pay. Then I'd build again based on what they actually told me. For marketing, I'd start with $0 in ads. I'd post useful things on X and Reddit, share what I'm learning, explain problems, answer questions, and give value. Someone sees the post → visits the website → signs up → becomes a beta user. Now you have something far more valuable than a follower: someone actually using your product. And if they don't pay? I'd ask: "Why aren't you paying?" That Million Dollar answer could completely change the future of the SaaS. Maybe the problem isn't painful enough. Maybe the product isn't solving the right problem. Maybe the value isn't clear. Maybe the pricing is wrong. Whatever the answer is, iterate. Build → Talk → Learn → Improve → Distribute → Repeat. I'd also find my ICP before my competitors do. If my competitor has thousands of followers, I'd study those followers. Find the people already talking about the problem. Follow them. Understand them. Comment. Give value. Don't immediately DM them: "Hey, check out my SaaS." Build the relationship first. Because marketing isn't just about getting attention. It's about becoming the person people trust when they finally need the solution. That's the mindset I'm trying to follow while building nodott(dot)com. You can build the best product in the world. But if nobody knows it exists, it doesn't matter. Build fast. Talk to users. Give value. Distribute. Iterate. Repeat.

  • vibedraft_app
    VibeDraft (@vibedraft_app) reported

    the most useful stat in the research we ran: reddit replies posted more than 24 hours after a thread get buried. octolens measured it across 522 million mentions. which means an intent listening agent that runs nightly is already too slow. the loop has to run hourly, and the human has to be reachable. the bottleneck is not the drafting. it is how fast a person can approve.

  • tactmedic52
    T.M (@tactmedic52) reported

    @letsgetfecal That wasn't at all what the issue was and I don't think you understand what Reddit means. Genuinely far worse of a game outside of the abysmal dog **** firearm customisation they put into that game.

  • squidlord
    Alexander 'Lex' Williams (@squidlord) reported

    @Ochadoji999 The process of online fragmentation is a long-standing problem. We used to have Usenet as the big conversational space and individual IRC channels on some of the larger servers as the ephemeral chat places, and it worked pretty well. Quite frankly, you can run an IRC server on a potato. They can talk to one another in a sort of federated mesh if you want. We had that technology figured out and nailed down. But then came the introduction of walled garden solutions. At least AIM and ICQ used open protocols so other people could make clients that interfaced with them, and you could still talk to your friends using them no matter what client you used. Then came Facebook and Myspace and the wave of early "social media" platforms, which slowly and surely began choking off access to general cross-system information. Reddit, for quite a long time, was a very big anomaly because as long as you spoke its API, it didn't care. Which is why so much of Reddit data made it into training information for various systems. Then Discord servers became very much the norm, which combined even more fragmentary, isolated groups into their own server silo, but within the same platform ecosystem. It was and remains great technology, but the way that it has affected the culture of online communities is somewhat of a problem in my view. It creates a feeling for and desire for insularity. Plus, it focuses on ephemeral conversation rather than long-term stored communication like you find on forums and Usenet and various other places where people have more nuanced conversations. If you think all your ideas deserve to have the lifespan of a mayfly, then I guess it's great, but I don't like it very much. In fairness, there never was a VTuber community. That's the wrong word to use for it. There was a "people who did VTubing and the people who were into watching VTubing." Those people didn't necessarily have many things in common, and they still don't. It is an identity group and not a community. Which sums up so much of what's wrong with it as a whole.

  • TomBilyeu
    Tom Bilyeu (@TomBilyeu) reported

    "Find where people in [industry] are angry about the options they already have. Pull Reddit threads, Amazon reviews, Google Trends. Quote them directly." Follow up: "Now show me the five most urgent problems in a growing market, with the evidence."