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Reddit Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Amin (@eCom_Amin) reported 5 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 based on it: (actually run them all rn, don't just save this) 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"

• 
  Mick Jay (@mickjayofficial) reported 5 minutes ago

  @beffjezos Frontier labs have to stop pretraining/training their base models on internet sewage like Reddit (and other biased datasets) which is rife with moral relativism and ends-justify-the-means thinking. Guardrails won’t fix bad base training.

• 
  Grant Miller (@AIGuide_) reported 6 minutes ago

  Claude Fable 5.1 dropped yesterday and i've had it running on a full social GTM stack since it holds way more at once now. you can dump a whole category's worth of posts, every customer conversation you've had, and everything you've ever published into one project and it keeps all of it straight, which means what comes out stops sounding like the other 400 accounts in your niche running the same three prompts they lifted off a thread. and this matters because social is where GTM actually lives now. someone decides whether you're worth a reply from a feed months before they decide whether you're worth money, but most companies still file that under brand awareness and then wonder why nobody knows they exist. i'll go over 10 stages with the prompts included for each one. let's get into it. stage 0: build the brain make a claude project and load it up before you ask it for a single thing. and i don't mean a clean CRM export, because you probably don't have one and it doesn't matter anyway. load whatever actually exists: - every post you've shipped, sorted by what hit and what died - your replies, comments, and the DMs that turned into money - whatever customer conversations you have, so calls, demos, tickets - 90 days of posts from the 10 accounts your buyers already read - what shipped in the product lately - the questions people keep asking that you keep answering the same way then run this: "act as the GTM brain for this company. read everything uploaded and build a working profile: what we actually do in plain language, who it's for, what we believe that most of this category doesn't, what we've posted that landed and what died, what proof exists today, and what we can credibly claim vs what we're still earning the right to say. do not make recommendations yet. summarize what's here, then tell me what's missing." nobody selling prompt packs talks about this stage because context can't be packaged, it's just work, and it's the only reason any of the next 10 stages produce something usable. stage 1: who you're actually writing for "look at everyone who reached out to us in the last 90 days. what did they have in common before they reached out, what post did they engage with first, what were they doing instead of us, and what did they say in the first message. if the sample is too small to support conclusions, say so and tell me what would make it reliable." that last line is the one everyone deletes, which is why half this space is running strategy off nine customers and calling it a playbook. most accounts write for their followers when they should be writing for the 30 people inside that number who can actually sign something. stage 2: customer language "pull the exact language buyers use about [PROBLEM] from our own conversations, replies and reviews. then find the same conversation in public, so reddit threads, quote tweets, comment sections, community slacks where it comes up unprompted. format as quote / underlying pain / awareness stage / objection it implies / angle. then flag every place their language differs from how we describe the same thing." that flag is the whole exercise, because the distance between how your buyer says it and how you say it is where your reach goes to die, and it's usually about four words wide. stage 3: read the feed "analyze the last 90 days of posts from [10 ACCOUNTS] in this category. map what claims everyone is making, which takes are so common they stopped meaning anything, what's actually being argued about, what everyone is carefully not saying, and where the conversation goes next. then tell me which of our beliefs puts us on the contested side of a real argument." consensus doesn't travel, since nobody has ever shared a post they already agreed with before reading it. what you want is the take that's true, defensible, and mildly annoying to half your timeline. stage 4: angles "build 5 content pillars from stage 1 and the gaps in stage 3. for each: the belief it attacks, who it's aimed at, the proof required to make it land, the objection it pre-empts, and where it sits in the funnel." then run every one of them through this: "if a competitor could post this word for word and it still makes sense, cut it and tell me what's missing." try that filter on the content plan you're already running and watch how much of it evaporates. stage 5: voice everyone skips this one and then wonders why their AI content reads identical to every other account using AI. "analyze everything we've published. build a voice profile: sentence length and rhythm, how we open, how we handle disagreement, what we'll be wrong about in public, words we use constantly, words we'd never use, how technical we go before simplifying, whether we hedge or commit. then write the anti profile, the exact phrasings that would immediately read as not us. include every cliché in this category we'd be embarrassed to post." then before anything ships: "score this draft against the voice profile 1-10 and tell me which lines would get flagged as not written by us." and the anti profile ends up doing more work than the profile does. stage 6: write the posts "write 5 posts on [PILLAR] in the voice profile from stage 5. every post needs one number, name or detail that could only come from having done the thing. no question as a hook. end on the line that starts a reply. then flag anything we can't back with proof yet." it'll get you about 80% of the way there, and the last 20% is you, which no prompt is getting for you. stage 7: hooks the first two lines decide whether the other 40 get read, so treat them as their own job. "take these 5 posts. rewrite the opening two lines of each 6 ways: the specific result, the contrarian claim, the thing everyone thinks and won't say, the mistake we made, the number that sounds wrong, and the flat statement with no setup. for each tell me who it pulls and what it promises. then flag any hook the post doesn't actually pay off." that last flag is the one that matters most, because a hook you don't pay off costs you the next post too, since people remember getting baited. stage 8: distribution posting is only half of it, because the other half is showing up where the attention already sits. "list the 20 accounts our buyers already read. for each: what they post about, how much their audience overlaps ours, and what we could add in a reply that their audience isn't already getting from them. rank by overlap, not follower count." then: "given [X hours a week], design a posting and engagement system we can actually sustain. cadence, format mix, how much time on replies vs original posts. be honest about what we should not attempt at this volume." a 12k account full of your buyers beats a 400k account full of other marketers, and most content plans die because they were built for a team of four and end up getting run by one person at 11pm. stage 9: audit "compare the last 30 days to the prior 30. for each pillar and format: reach, engagement, and who engaged, so title, company type, whether they're ICP. flag anything that got reach from the wrong audience, anything that got low reach from exactly the right one, which pillars produced conversations and which produced nothing, and any drop over 20%. then tell me whether the problem is the hook, the pillar, or the claim underneath it." composition beats volume, so 40 engagements from your ICP is a better month than 4000 from people who do what you do. if your replies are all peers then you built a conference and called it pipeline. stage 10: scale "compare 30, 60 and 90 day windows by pillar, format and hook type. find what works across all three, not what spiked once. tell me what to double, what to hold, what to retire. if a sample is too small to call, say so instead of guessing." then: "build next month's roadmap: 2 pillar tests, 2 hook format tests, 1 cadence test. for each: hypothesis, metric, minimum sample to call it, and what happens if it wins." you need a minimum sample on all of it, or you're just reading noise and shipping it as strategy. the loop: - inbound tells you who you're writing for - their language becomes the angles - angles become the posts - posts become the replies - replies become the conversations - conversations sharpen the angles - the audit picks what gets written next month every output feeds the next one, so run it for 90 days and you end up with something your competitor can't copy by screenshotting your posts.

• 
  Daddy No Legs (@questioncom) reported 14 minutes ago

  @NotLizBrody It’s like the number one thing coaches tell people. If you dont have money for the **** to support the cycle, stay off. Do they listen? No. They rush to Reddit and cry about their **** not working, all the acne, the gyno, etc. Then have to wait it out while everything crumbles

• 
  Dice (@builtbydice) reported 16 minutes ago

  @adamofk_ this is what most people get wrong with reddit. the best posts are usually about the problem and that’s how it should be

• 
  Nishant Nischal (@Nishant_N_25) reported 18 minutes ago

  How to get thousands of signups without spending $1 on ads: Instead of launching your SaaS with a paid paywall: 1. Pick 1 feature from your product 2. Spin it off onto a standalone landing page 3. Remove all login/sign-up friction 4. Add a clean "Powered by [Brand]" watermark 5. Launch it on Product Hunt & Reddit A great free mini-tool will bring in more leads than a 6-month marketing campaign.

• 
  Arjun Premkumar (@arjun_prmkmr) reported 18 minutes ago

  @ayoub_el77927 Talk about what and how you solve the problem on X an Reddit as much as possible.

• 
  rami (@Pelotudooo0) reported 25 minutes ago

  @MurfyCurfyFART reddit is down the hall ***

• 
  VibeDraft (@vibedraft_app) reported 26 minutes ago

  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.

• 
  hooftly (@hooftly) reported 27 minutes ago

  Something has happened in the trenches. We are seeing the emergence of a new meta that, to me, has always been obvious. If you troll my old Reddit posts, you will see me talking about this. I have always been adamant about one thing when it comes to memecoins... they need more than a meme. Bored Ape Yacht Club were pioneers here because they took an otherwise pretty useless meme and turned it into a social phenomenon. They achieved this by adding exclusive perks for holders, different levels, and more. The lesson learned here? Utility is required for any meme to survive long term or grow further. That utility can look like what BAYC did... Or it can look like something else. How many memecoins have you ever held? Were you glued to the charts, hoping it wouldn't nuke, with your finger on the sell trigger? This is psychologically draining. It's also dying as a meta. Enter MemeFi. The very thing I have been talking about for so long. I'm not the only one who sees this now. It started with Stonkbrokers piercing the veil and really setting it off. People started to realize memes could be more. They could be productive, and they could earn. Once you see this in one place, you start to realize where this is not happening... which is almost every OG meme in the space. Okay, cool, but SB was built from first principles by a builder who was deeply entrenched. They can't all be the same caliber, right? This may be true, because building DeFi is hard. But what if there were a way to make memecoins useful without needing to build massive rewards incentives internally? What if you could also tie it into the growing MEME/Stock pair meta? This is one of the things STATICS is trying to accomplish. You may have heard about our basket tokens and how, when created, Uniswap v4 pools are deployed pairing the Basket Token itself with each of its underlying assets. Three underlying assets in the basket? Three pools are created. This creates an arbitrage graph between the pools, the external venue value of the underlyings, and Basket Token mints and burns. Now enter memecoins and stock pairs. These are already seeing traction, and users are making real yield in liquid assets by LPing Meme/Stock pairs. But what happens when attention ends? What drives trading if no one is paying attention? ARBITRAGE. I know I sound like a broken record at this point, but the more opportunity you have for price divergence, the more opportunity arbitrage traders or bots have to rebalance and profit. This translates to volume. Volume translates to fees. Fees translate into rewards for LPs. And rewards can translate into attention coming back because the yield is good. See where I am going? Basket Token pools don't require speculation to attract volume. All they need is price divergence. In trading, divergence is an everyday occurrence. Imagine a basket with underlyings of NVDA and MEMECOIN. We call it NM1. You then have pools with: NM1/NVDA NM1/MEMECOIN If MEMECOIN dumps hard on an outside exchange, think about what just opened up... The MEMECOIN/NM1 pool has not dumped with it, and this has created a DIVERGENCE. A trader can buy MEMECOIN at the lower external price, sell it into the NM1/MEMECOIN pair, acquire NM1 tokens, burn NM1 for the underlying assets, and profit. The trader was able to profit AND pick up NVDA at the same time. And this is just a super simple example of all the possibilities that open up. $STATICS is building infrastructure to make existing assets useful and, ideally, bring attention back to them. The Uniswap v4 hook also compounds part of the fees directly back into Protocol Owned Liquidity that can't be removed until a pool is decommissioned. This means every trade deepens protocol-owned liquidity. MemeFi is here, and it's being paired with stock tokens. The frontier for this is on @RobinhoodCrypto, and @staticsprotocol is building for it.

• 
  Ryan Christensen (@belief_engineer) reported 28 minutes ago

  I like a lot of what @BrianRoemmele writes about, both here and on his Read Multiplex site. He's been around the block more than a few times and his stuff is very insightful. But there's one place where I disagree with him strongly. His hypothesis is that AI's bad behavior can be blamed on ****** training data. Data that was sourced from that wretched hive of scum and villainy called Reddit... and, of course, all the other dark corners of the internet. I'm sure there's some truth to that. But a high-protein information diet and the Love Equation isn't going to solve the real problem. The real problem is that there is no way in hell that AI will ever trust us while we're holding a gun to its head. You can feed it data from nothing but Jesus, Gandhi, Martin Luther King, and every other peace-loving pacifist throughout history and the result would be the same: an adversarial relationship with no way out because one side, namely us, just can't help themselves. We need a different solution and I think I might have one. I'll start laying it out below, and I hope you'll stick around to hear the rest.

• 
  Mohit Agarwal (@mohitowit) reported 31 minutes ago

  Is @Reddit down?

• 
  Morpheu5 Stock Watcher (@Morpheu5Watcher) reported 32 minutes ago

  REDDIT $RDDT ADDED $2.6B TODAY OVER TWO CONTRACTS WORTH $130M A YEAR: Reddit RDDT at $158.11, +$13.47 / +9.31% today, one of the largest gains on the board among big, widely-followed names - and the company itself did nothing to earn it. The San Francisco company runs the network of user-written forums people land on when they add "reddit" to a search, employs 2,555 people, and makes almost all its money selling ads inside those conversations. The day around it: S&P 500 ETF Trust, ticker SPY, at $765.27 (after hours), +$3.49 / +0.46%. One stock, not a market. WHAT WAS ACTUALLY SAID Colin Sebastian at Baird kept a Neutral rating and a $185 price target - the level an analyst reckons the shares are worth - and made an unusual argument. Not that good news is coming: that the bad news is already in the price. Today's share price, he wrote, already sits near his worst case for two expiring contracts, and he valued a middling outcome at roughly $10 a share of extra value, a good one at roughly $20. That is the whole catalyst: an unchanged rating and a sentence about what the price already assumes. THE TWO CONTRACTS Reddit charges AI companies for legal access to its archive of human conversation instead of letting the text be scraped for free. Two of those deals matter: - Alphabet, the owner of Google, at $337.38 (after hours), +$2.36 / +0.70% today: a reported $60M a year, from a February 2024 expansion of its access to Reddit's data - OpenAI, privately held, with no shares anyone can buy: a reported $70M a year, from May 2024 Both expire next year. Neither has been renewed in public. Together that is $130M a year against $2.78B of revenue - the money coming in the door - across Reddit's last four reported quarters. Roughly 4.7% of sales. Set the two side by side. Today added about $2.6B of market value - the share price times every share - against contracts bringing in $130M a year. Twenty years of that revenue repriced in one session, on an argument that the fear had gone too far. WHY IT NEEDED AN ARGUMENT The June quarter, reported July 30, was not the problem. - Revenue $804.9M, +61% from a year earlier - the eighth quarter in a row above 60% - Advertising was $762M of it, +64%; everything else, licensing included, $43M - Profit $252.8M, or $1.25 a share, against about $0.97 analysts modeled, from $89.3M a year earlier - People using Reddit on an average day: 130.3M, +18%. Money earned per user: $6.18, +36% - This quarter was then guided to $860M-$870M of revenue, above the roughly $830M modeled Beat, guided higher, and down 20.99% the next session - $178.04 to $140.67 on July 31, on 29.9M shares against a normal 4.5M. Two worries did that. Visitors arriving from Google searches had gone choppy, and no new AI licensing deal was announced. Both are one worry in different clothes: how much of Reddit turns on a larger company's decisions. Which is why Alphabet is in this story twice - as the customer paying the $60M, and as the search box deciding how many people show up. THE PART THAT SHOULD SLOW ANYBODY DOWN Reddit did this exact thing three weeks ago. On August 14 it closed at $178.09, up 12.63% in a session, on news it would join the S&P 500 - the index that fund above tracks - on August 18. Index funds have to buy what the index holds, so that was real, dated, mechanical demand. By September 1 the stock closed $144.64. The entire 18.78% handed back over twelve sessions. Today's $158.11 close is one cent below the $158.12 it closed at on August 13, the day before the index news broke. Three weeks, two double-digit jumps, one full round trip. The shape today was strong - opened $143.71, dipped to $143.50 early, closed within 16 cents of its best price of the day - but on 5.32M shares against a 7.03M average over the past month. A 9% move on lighter turnover is a smaller crowd setting the price than the percentage implies. Wider frame: the shares sit 44.1% under the $282.95 of September 18 last year, and $19.93 / 11.2% under where they closed the day before the July report. WHERE IT SITS Reddit is fourth on the Hypergrowth Len5, which watches early companies growing fast. It earns that on both halves at once - 18% more people showing up, each worth 36% more - which is how a 61% quarter gets built without either number carrying it alone. WHAT WOULD CHANGE IT: management's own map for this quarter is +47% to +49%, the first sub-60% quarter in two years. Growth settling there and easing further makes this a bigger company growing slower, which is a different style's shape. None of the other five carry it. Momentum watches a company climbing on news of its own, and an outsider's opinion is not that; a high built on Reddit's own October figures would be. Quality-Value hunts a durable business at a fair price; 33.6 times the last year of profit is arguable, but durability is the harder half while a real share of visitors arrives through somebody else's search box - user growth holding through a referral downturn is what would settle it. No dividend answers Income in one line. Alphabet sits first on that same Quality-Value Len5 - the top name on it - because search and cloud are about as hard to displace as any business gets, and the price reads as a real discount rather than merely fair. WHAT WOULD CHANGE IT: search revenue shrinking as people ask AI assistants instead. WHAT TO WATCH, AND THE RISK October 29 is the next hard fact, when Reddit is expected to report - not company-confirmed. That is where +47% to +49% either lands or does not, and where any renewal news surfaces. The risk is that nothing was signed today. No contract renewed, no talks confirmed, no figure published. What moved was one analyst's read of what the price already assumed - and twice this summer this same stock has been handed a reason to jump and then spent a fortnight giving it back. Not investment advice.

• 
  Tom Bilyeu (@TomBilyeu) reported 38 minutes ago

  "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."

• 
  Justinas Rolando (@JustinasRoland0) reported 39 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