01Ramp, a $60B company, hid a secret offer on its website that only AI could see.SEOin 32 days, AI told buyers about it 370 times. here's the genius AEO experiment behind it: 1. They built a second version of their site just for AI - Ramp put an offer on about 50 pages that only AI bots could see - Human visitors saw nothing different - Then they tracked whether ChatGPT, Claude and Perplexity would pass the offer on to real buyers 2. They tested 3 formats to see what AI actually reads - Markdown - Plain stripped down HTML - Pages packed with schema, the code made for machines - Everyone expected schema to win - Markdown was the only format that reliably showed up in AI answers 3. They found out who was really visiting their site - Thousands of visits from 7 different AI platforms in just 2 weeks - Some AI bots pretend to be normal browsers. DeepSeek shows up as a Chrome version from 2017 - Claude's crawler visited more than all the other named AI crawlers combined 4. They asked the AI tools buyer questions every single day - The same questions a CFO would ask when picking a spend management tool - Then they checked every answer for their offer 5. Every AI behaved completely differently - Claude passed on the exact offer, the link and step-by-step instructions - Perplexity only mentioned it vaguely - ChatGPT read the pages but mentioned the offer 0 times in 32 days - One strategy for "AI" doesn't work. Each model needs its own plan 6. The biggest lesson: AI trusts pages it already cites - Pages that AI was already citing were the ones where the offer showed up - Pages with few AI citations got zero mentions, whatever the format - One of the best pages was one Ramp never cared about for Google the result: - 1,300+ AI bot visits in the first 2.5 weeks - about 40 AI answers mentioning the offer at 2.5 weeks - 370 by day 32, almost 10x - a peak of 33 in a single day Ramp didn't win this by writing more blogs they figured out which pages AI already trusts, then put the right message there and that's the whole game now: if AI doesn't already trust the pages talking about you, it won't recommend you. if you want to know which pages ChatGPT and Claude trust in your niche, and get your brand mentioned on them. reply "citations"@crowdreply_io · 3日前元投稿保存率 0.7%保存率 0.7%418×通常リーチ比717.8K5,049
02internal linking is the most underrated SEO trick you can pullSEOand almost nobody does it because it's boring So I made Claude do it for me, every week here is the exact setup (prompt included, bookmark this): 1/ pull your Google Search Console data, either an export or a GSC MCP 2/ connect your website to claude with an mcp i use wordpress (sometimes I use Astro too) with a custom mcp plugin, but there are connectors for almost every blogging platform 3/ paste this prompt: "I've attached my Google Search Console export for the last 3 months. My website is connected through the [site name] MCP. 1. For each article, find the queries where it ranks best (position 1–10, decent impressions). Those are its target anchors. 2. Go through every published post. Wherever the text naturally mentions another article's top query (or a close variant), turn that phrase into a link to that article. 3. Rules: - Max 3–5 new internal links per post, spread through the body (no headings, intro sentence, or existing links) - Never link a post to itself, only link each target once per post - Anchor text must read naturally. Don't rewrite sentences to force a keyword in - Prioritize sending links to pages ranking 4–15 4. Before changing anything, show me a table: source post → anchor → target URL → target's query and position. Wait for my OK. 5. After I approve, make the edits through the MCP and give me a changelog so I can revert." 4/ check the table, say ok, claude makes the edits 5/ leave the site alone for a few days 6/ repeat every week thats it the pages sitting on position 4-20 are the ones that move the most, and they're already on your site you just need to point at them still build backlinks and keep publishing; internal linking just makes all of that work harder i run this exact process on my sites and my customer sites what's stopping you from doing internal linking right now? is it the connection to your site ?@asaio87 · 8日前元投稿MCP保存率 2.1%MCP保存率 2.1%257×通常リーチ比187.6K3,993
03now that apple put xcode inside claude codeSEOコールドスタートhere’s how i’d find, build and grow an iOS app with AI agents: find it - open appfigures or sensor tower and sort utilities by revenue - filter for apps with a rating under 3.5 - bonus points if the top app hasn't shipped an update in 6+ months - check the keywords they rank for in appfigures. low difficulty + high revenue is the sweet spot - scroll the "you might also like" row on the top app's page. every app there is another market to check - or find a startup idea on http://ideabrowser.com/ based on social sentiment validate it - use facundoolano/app-store-scraper to pull every review for the top 20 - give them to an agent: "cluster the 1 and 2 star reviews into the top 5 complaints and quote the users" - pick the app where the complaints are about the product, not the price - if people complain about the price but keep paying, that's demand. if they complain about bugs, that's your opening - search reddit for "alternative to [app]". every thread is a list of people waiting for you build it - claude code + apple's new xcode plugin to build, preview and fix - cameroncooke/XcodeBuildMCP so the agent can build, test and run the simulator on its own - joshuayoes/ios-simulator-mcp so it can tap, swipe and screenshot like a user - write a skill with the top 5 complaints so every feature gets checked against them - apple's foundation models for on-device ai, so your inference cost is $0 - app intents so siri and personal agents can use your app too - add an "import from [competitor]" button. make switching take 10 seconds test it - maestro tests every flow the reviewers complained about - the agent runs them on every screen size before each build - if the competitor's worst flow takes 6 taps, yours takes 2 - sentry for crashes, telemetrydeck for analytics - testflight it to 20 people from those reddit threads before launch monetize it - revenuecat for subscriptions and mrr - superwall to test paywalls without shipping a new build - paywall right after the first win, never on launch - annual as the default with a 3-day trial, weekly as the anchor - turn on win-back offers for everyone who cancels rank it - your screenshots answer each complaint directly. "no ads." "works offline." "cancel anytime." - fastlane snapshot + frameit regenerates every screenshot automatically - a/b test them with app store connect's product page optimization - have the agent localize your listing into 10 languages. most competitors only rank in english - ask for a review right after a win with apple's built-in review prompt, never after an error grow it - find 10 creators in your niche on tiktok one. small monthly base + a bonus for every 100k views - give each one a fresh tiktok account that only posts about your niche - apify's tiktok scraper pulls the top 100 hooks in your niche every week. that's your hook bank - every creator tests 3 new hooks a day in capcut. anything that loses people in the first 3 seconds gets cut - arcads or heygen for ai ugc when you need 50 variations of a winner - postiz to schedule everything across tiktok, reels and shorts - faceless slideshow accounts posting 3x a day: problem, screenshot, result - when an organic video takes off, put money behind it with tiktok spark ads instead of making new ads - a unique apple offer code for every creator so you know exactly who drove each subscriber - a quiz landing page on framer that ends in "download the app." web-to-app funnels convert better than cold traffic - appsflyer to track which video, creator and ad actually turned into revenue - apple ads on the competitor's name i could do a whole episode on @startupideaspod if people are interested. i will never gatekeep anything im learning in real-time. welcome to the golden age of ios apps, because now anyone can build one@gregisenberg · 5日前元投稿ideabrowser.com言及製品IIdeabrowser保存率 2.9%ideabrowser.com保存率 2.9%言及製品IIdeabrowser3.8×通常リーチ比265.2K7,590
04My favorite SEO hack - Go to google search consoleSEO- Performance > search results - Add filter > query > custom (regex) - Paste this: ^(?:\S+\s+){7,}\S+$ - It shows every search with 8+ words These are the long, specific questions people google before they find you. it's the same kind of question they ask chatgpt Pick the ones with high impressions and low clicks, and answer them at the top of the page that ranks@askokara · 11日前元投稿保存率 2.7%保存率 2.7%56×通常リーチ比199.6K5,379
05The biggest thing I've shipped since Marketing Skills itself!SEO有料広告🆕 skill: /reverse-engineer-marketing — see how any company actually grew using public data. Give it a domain and it: → Charts their monthly Google traffic and brand searches → Dates every launch, price change, ad start, and campaign on that chart → Finds the months growth stepped up, and which campaigns lined up with them → Maps every page type on their site from the sitemap, and when each one appeared → Pulls the keywords and pages that bring them search traffic (with your SEO tool) → Checks which brands ChatGPT, Perplexity, Gemini, and AI Overviews name, and which pages they cite → Finds their live ads, longest-running ads, hooks, offers, and landing pages → Catches the paid promotion ad libraries miss: newsletters, podcasts, YouTube sponsorships, affiliates, coupon sites, events → Finds their best posts, creator videos, giveaways, and launch weeks → Logs funding rounds, launches, and press waves by date → Tracks every pricing change and how their free trial ends → Finds their referral loops, "made with" badges, and affiliate programs → Detects every marketing tool on their site, and the month each one was added → Reads their DNS to see who sends their email and which tools they've verified → Dates new subdomains from certificate logs → Shows every homepage headline change, month by month → Reads their open jobs to see which channels they're scaling next → Transcribes founder podcasts and talks, and pulls out every growth claim with a date → Breaks down what their top posts have that their worst posts don't, channel by channel → Mines 1-2 star reviews and "switched from" posts for where they're weak → Compares them to you, stage by stage, using your own Search Console and analytics → Profiles 3-5 competitors side by side: what's table stakes, what's a bet, what you're missing → With your OK: signs up, logs their onboarding and 60 days of emails, maps the upgrade wall and cancel flow, and books the demo → Funnel Hack mode: buys through their funnel to map order bumps, upsells, abandoned-cart emails, and live A/B tests → Watch mode: reruns every month and reports only what's new → 31 industry packs, from SaaS and DTC to solar, insurance, and games Then it turns what worked into ideas you can copy, each with the skill that runs it and a ready-to-run prompt. Plus the ideas to skip, and the one to start this week. Here it is on Granola. 53 skills. Free & open source 👇@coreyhainesco · 2日前元投稿保存率 3.2%保存率 3.2%21×通常リーチ比39.7K1,289
06we were able to rank number 1 on Google + LLMs and go from 0 to 7 figures…SEOコールドスタートin just 10 days and all we did was - use exact match domains for search terms like: "best data labs" "best ai data labs" "best data labelling" "best data labelling for ai" "best data labelling platform" "best data labelling software" "best data labelling tools" "best data brokers" "best enterprise fine tuning services" we noticed the massive amounts of $ flowing into the "sell your data" space from the likes of @mercor and @micro1_ai and immediately knew that the traffic and visibility in this space for keywords like "best data labs" is highly valuable everyone is racing to either sell or acquire data, but the toughest challenge for these parties is to find one another 1) data sellers want a counterparty that is trustworthy and reliable 2) data buyers want to get their hands on as much data as possible (various data types & counterparties) these transactions come with high urgency and high avg. ticket sizes the combination of all these make it the perfect niche to secure positioning in! so we got to work and: 1) secured highly valuable exact match domains (they match the search intent keywords 1:1) 2) deployed highly relevant, carefully architected content that induces lexical proximity to the keywords of interest (convincing the search engines + LLMs that our information on the topic is rich and relevant) 3) focused on clean and functional entity mapping that consistently and coherently links our entity to the desired keywords 4) waited for 10 days and now we rank for all these high value keywords and search intent! we have since received offers by neolabs to rent the space on these domains and a 7 figure offer for acquiring these assets outright when we asked why, they explained that securing just one highly relevant lead from this type of positioning can yield an asymmetric return and more than offset the costs what a wild time to be alive!@margatix · 5日前元投稿言及製品MMicro1保存率 1.7%保存率 1.7%言及製品MMicro12.0×通常リーチ比566.1K9,718
07for the first time ever, I'm sharing everything I do across all my SaaS to…SEOSNSrank on Google and get mentioned by AI every SEO and AEO lesson I've learned is here: 1. we show up in Reddit threads. AI pulls a lot of its answers from Reddit, so Bazzly finds the threads that are fresh, and even the ones already ranking on Google, and gets our products into the top reply 2. we get our products listed #1 in listicles that already rank on Google, with Outrank. when someone asks ChatGPT for the best tool, those are the pages it reads 3. we turn Reddit questions into blog articles. Bazzly shows us what people actually ask, and we feed those questions to Outrank 4. I regularly sit down and find new niches where our products could be useful. I research each one and feed it to Outrank, and Outrank finds new ones on its own too, so our keyword plans keep expanding into new markets 5. we publish an SEO article on our own blogs every day, also with Outrank 6. Outrank helps us refresh old articles regularly. AI and Google both prefer recent pages, so every page has to stay current 7. we build new backlinks every week with Outrank, and every placement gets verified. we also pitch guest posts using Outrank's free guest post database of 278 checked sites, all DR 20+ 8. we regularly ship extremely useful free tools for potential users, and each one ranks on Google and brings people into our products 9. every month we check which AI answers name our products and which don't Outrank's AI Visibility Checker asks ChatGPT, Claude, Gemini and Perplexity real buyer questions, then shows whether we got named, which competitors did, and which sources got cited we feed those sources back into Bazzly, Outrank and our internal social content all of this brings in new users, and then we run loops that turn them into champions who spread the word 10. we incentivize our users to share honest reviews of our products on Instagram, TikTok, X and LinkedIn, and on public review sites 11. we let our users become affiliates, and then we help them make better content about our products. in the last 30 days, ~$8K has been generated by Revid affiliates alone basically every SEO and AEO lesson I learn building Outrank and Bazzly goes straight into every product I run and the idea behind all of it is simple AI recommends the most mentioned product so we make sure every one of our products gets mentioned everywhere Google and AI look: all sorts of blogs, listicles, Reddit, review sites and social and this setup does the job extremely well, for every product we run@tibo_maker · 4日前元投稿言及製品OOutrankBBazzly保存率 2.8%保存率 2.8%言及製品OOutrankBBazzly5.8×通常リーチ比104.2K2,901
08OpenCode isn’t free anymore if you want serious usage料金so if you’re looking for the cheapest ways to run strong coding models, these are the options i’d check first: 1. DeepRelay, $4.99/month 2.5B input + 250M output tokens/month for DeepSeek V4.1 Flash off-peak. there’s also a $0.99 plan with 500M input + 50M output if your usage is tiny. 2. Mistral student, €6/month the Vibe API key can also give you access to DeepSeek V4.1, GLM 5.3 and GLM 5.3 Flash, not only to Mistral models. 3. CommandCode, $1/month probably the cheapest subscription here, but the catch is that it only works with their own harness. 4. Alibaba Cloud, $3-$6/month cheap access to models like Qwen 3.8 Max and GLM if DeepSeek isn’t a requirement. 5. Muse / MiMo, $5-$6/month both are worth checking if you mainly want cheap coding inference without jumping to a $10 to $20 subscription. if your usage is really light, i’d still skip subscriptions and just use direct API credits. that can easily be cheaper than paying monthly for capacity you never use.@yuhasbeentaken · 2日前元投稿保存率 1.9%保存率 1.9%30×通常リーチ比44.9K855
09LINKEDIN MAXXING with GrokbotSNS50 tactics behind 3.24M impressions in the last 90 days Ranked: S TIER 1. Build a voice guide that makes every draft more specific to you. 2. Feed it your strongest posts, interviews and transcripts to capture how you actually explain things. 3. Extract your opinions, recurring phrases and examples to give drafts a recognizable perspective. 4. Add rejected phrases and approved edits to stop correcting the same mistakes. 5. Build a separate guide for each executive so your CEO and CRO don’t become the same writer. 6. Turn sales conversations into your content strategy. 7. Review call transcripts to find questions prospects ask before they understand your offer. 8. Group objections by frequency and deal stage to identify which explanations are missing. 9. Preserve buyers’ exact wording to write about the problem as they experience it. 10. Match each topic with a real example or result to give the post supporting evidence. 11. Build an outreach research desk. 12. Supply your target-account list and qualification criteria to give the bot a defined research job. 13. Review company websites, announcements and supplied profile information to check account fit. 14. Find relevant triggers such as a product launch or leadership change to establish why now. 15. Match verified account details with a relevant case study to prepare a specific outreach draft. 16. Use content to support deals already in your pipeline. 17. Review stalled-deal notes to identify concerns prospects explicitly raised. 18. Draft posts addressing recurring objections without exposing confidential deal details. 19. Match approved resources with the questions they answer to help sales prepare useful follow-ups. 20. Draft a follow-up connecting the resource to the actual conversation for the account owner to review. A TIER 21. Find content patterns worth testing. 22. Supply a swipe file of relevant posts with dates and available performance data. 23. Compare each post with its author’s typical results to find meaningful outliers. 24. Break winners into topic, opening, argument, evidence and format to understand their construction. 25. Rebuild useful structures with your own experience instead of borrowing someone else’s story. 26. Turn market conversations into LinkedIn commentary. 27. Track relevant X discussions and original announcements to find developments your buyers should understand. 28. Check competing interpretations to avoid repeating the loudest take as established fact. 29. Add your own experience or customer evidence to explain where you agree or disagree. 30. Draft the LinkedIn version around a practical business implication rather than a recycled summary. B TIER 31. Prepare better conversations with people showing interest. 32. Supply relevant comments and inbound messages to identify the question behind each interaction. 33. Distinguish explicit interest from casual engagement to avoid treating every like as buying intent. 34. Check CRM notes to avoid duplicate outreach and draft a useful response for human review. 35. Prepare a meeting brief from the conversation history when someone actually wants to talk. 36. Extract more value from expertise you have already recorded. 37. Review podcasts, webinars and interviews to find moments that support a standalone argument. 38. Pull exact quotations and timestamps to keep every source easy to check. 39. Ask focused follow-up questions when an example needs more detail or supporting evidence. 40. Turn approved material into a text post, visual brief or short video outline. C TIER 41. Build resources that give outreach a useful purpose. 42. Find a repeated buyer task to choose a checklist, worksheet or calculator worth creating. 43. Ask Grok Bot to prepare the resource from your approved process and test it against realistic examples. 44. Write a demonstration post showing the resource solving a specific problem. 45. Draft a relevant reply offering the resource when someone asks about that problem. D TIER 46. Build the review and reporting loop. 47. Check drafts against your voice guide and sources to catch unsupported claims and repetitive writing. 48. Combine analytics, inquiry records and CRM notes to identify relevant business conversations. 49. Separate tracked conversions from possible influence to keep attribution honest. 50. Turn recurring edits into better instructions and choose one experiment for the next month. The article below has the 12 copy-and-paste prompts behind the core system, the business context to load first, and the order to build it in.@paolo_scales · 12日前元投稿保存率 2.1%保存率 2.1%49×通常リーチ比154.7K3,260
10BACKLINKS MAXXING with Claude CodeSEO69 backlink tactics behind 133k AI mentions for http://distribb.io/ Ranked: S TIER 1. Exchange relevant editorial links 2. Join a relevant business network to find editorial link partners. 3. Match links with the surrounding topic to make each reference useful. 4. Link to the answer readers need to give each placement a purpose. 5. Log published sources and destinations to track delivered links. 6. Get into the lists buyers read 7. Find competitor roundups to locate publishers covering your category. 8. Check AI's cited roundups to find sources used in buying answers. 9. Find a missing buyer need to give list authors a reason to add you. 10. Send a tested feature or fresh example to support your proposed addition. 11. Send the author your exact addition to make the edit easy to assess. 12. Refresh your roundup entries to keep the product details accurate. 13. Publish statistics people can cite 14. Choose a question your buyers need answered to make the research useful. 15. Publish original statistics to give writers a source they can cite. 16. Explain the sample and method to make each statistic checkable. 17. Write each finding as a complete sentence to make it easy to quote. 18. Keep research URLs stable to preserve links when findings change. 19. Link research to relevant product pages to help readers try the tool. 20. Answer journalist requests 21. Show real experience in your profile to help reporters assess you. 22. Check Qwoted requests to find reporters who need your knowledge. 23. Filter by topic and deadline to find requests you can answer. 24. Lead with a direct answer to give the journalist a usable quote. 25. Add an original number or firsthand example to support the quote. 26. Include your research page to let the journalist verify the answer. 27. Log requests and replies to avoid pitching the same request twice. A TIER 28. Find link opportunities through competitors 29. Inspect competitors' linked pages to find resources publishers cite. 30. Read the sentence around each link to learn why the author added it. 31. Add missing evidence to give those publishers a useful new source. 32. Pitch the specific missing answer to show what your resource adds. 33. Recover links you already earned 34. Find unlinked brand mentions to ask editors to link readers to the source. 35. Search for reused charts and quotes to find missing source credits. 36. Restore removed pages with live backlinks to make those links useful. 37. Redirect old URLs to equivalent replacements to restore reader access. 38. Build free tools that earn links 39. Find a repeated buyer calculation to choose a useful free tool to build. 40. Ask Claude to build a calculator to answer the buyer's question. 41. Test normal and unusual inputs to check the tool's answers work. 42. Give the tool a permanent page to give publishers a place to link. 43. Offer the tool to relevant guides to give their readers a shortcut. B TIER 44. Replace broken and outdated resources 45. Find dead competitor URLs with backlinks to locate broken references. 46. Read archived pages to learn what readers expected from the dead URL. 47. Publish a matching replacement to give editors a working source. 48. Send the broken link and replacement to make the repair easy. 49. Find guides naming closed tools to offer a current replacement. 50. Build the visual an article is missing 51. Find text-heavy guides to locate explanations that need a visual. 52. Offer a graphic for a named section to give the author a clear use. 53. Ask before making graphics to spend time on interested publishers. 54. Use the author's checked facts to make a graphic they can trust. 55. Send the image and embed code to make publishing and source credit easy. 56. Turn another author's article into a video 57. Find guides missing a demo to offer a video their readers could use. 58. Pitch a short video for one section to explain exactly what you will make. 59. Record the steps after the author agrees to produce something they want. 60. Send the finished video with source-credit wording to make adding it easy. C TIER 61. Earn links through tools you use 62. List software you use to find vendors that could feature your story. 63. Document your workflow and result to give vendors a customer story. 64. Send the case study to the right editor to propose a customer feature. D TIER 65. Claim relevant business listings 66. Find eligible supplier directories to make your business discoverable. 67. Complete eligible government profiles to help buyers find your business. 68. Add your website where allowed to help directory visitors reach you. 69. Keep listing details consistent to help people recognize your business.@borjafat · 14日前元投稿distribb.io言及製品DDistribb保存率 1.6%distribb.io保存率 1.6%言及製品DDistribb32×通常リーチ比248.1K4,022
11Shooting my shot @alexandr_wangSNSコールドスタートI want to run Muse's UGC strategy. I'm the cofounder of Playkit, the agency behind 1.5B+ views and 14M+ app downloads for consumer tech companies. We've built a network of 100+ creators who produce 10 short-form videos each, per week, for apps like Quizlet, Substack, and CashApp. Marketing Muse as a general purpose AI assistant would be a massive mistake, because it can serve so many different types of people. If I were in charge of driving measurable downloads for the app through organic UGC, here's what I'd do: 1) Break the campaign into three (or more) specific customer cohorts. For example: busy moms fitness enthusiasts sorority girls Each have different problems Muse can solve, and speaking to them directly would improve conversion drastically. 2) Map out their use cases. What is the deepest pain point or largest aspiration Muse can solve for each group? Busy moms: helping manage the meals, babysitting, sleep timing, and errand-running of a 32-year-old mother of two under two. Fitness enthusiasts: helping them track progress towards a meaty goal (sub-20-minute 5K, let's say). Sorority girl: helping manage the overwhelm of studying, having a social life, and maintaining personal well-being while being in a new environment. 3) Recruit creators who live these problems. 4) Produce enough videos to see what use cases and problems actually convert. Right now, each creator on a Playkit campaign posts 10 (pre-approved!) videos per week. More creators recruited = more volume = more chances to find winners. 5) Iterate like our life depends on it. Identify winners, cut losers, run comment section campaigns and drive conversion from every single angle. 6) We use the best-converting organic videos as paid ad creative (do y'all get discounts on Meta ads???). Let us get Muse on every TikTok and Instagram FYP. DMs are open.@juliapintar · 1日前元投稿言及製品PPlaykit保存率 0.5%+1保存率 0.5%言及製品PPlaykit22×通常リーチ比89.9K447
12Another great visibility hack for your SaaS is to get listed on Vercel's…SEOコールドスタートhttp://skills.sh/ (DR 82). You get a dedicated page with your skill, its install command and an install counter. Here is how: 1. Write an agent skill for your SaaS, a SKILL.md that tells the agent how to use your API (ask Claude to do it for you). 2. Put it in a public GitHub repo. 3. Run npx skills add your-org/your-repo once.@tarasshyn · 5日前元投稿Skillskills.sh言及製品SSkills保存率 1.3%Skillskills.sh保存率 1.3%言及製品SSkills38×通常リーチ比66.8K863
13this AI UGC video costs $0.30 & i didn’t have to approve her videos or…SNSeven talk to her. i made her with AI. save the entire workflow: 1. create a character sheet from a pinterest pic with this prompt: “Character turnaround sheet of the person from the reference photo, six views: full body front, side and back + close-up front, side and back. Strictly keep 100% of face, hair, body, clothing and all details from the reference. Clean gray background, consistent and natural lighting.” 2. download a viral tiktok with a hook + demo format 3. cut the hook (around 2–3s) 4. use wan 3.0 prime (cheaper and better than seedance 2.5) 5. send the hook video + character sheet as references with this prompt: “replace the girl in {video} with the girl in {character sheet}. keep the same movements, camera quality and audio.” 6. record a quick demo of your app 7. attach your app demo to the hook using capcut or concat (free version) 8. enjoy your video for $0.30 instead of paying influencers $2k/month lmk if you want more prompts to save money!@simonecanciello · 13日前元投稿保存率 1.2%保存率 1.2%9.8×通常リーチ比349.1K4,055
14免费开放包含 1320 张素材的动漫服装数据库コールドスタート整理1320张动漫服装并建立数据库,支持商用与二次修改,简化AI换装提示词工作流。@giaaibusi · 11日前元投稿保存率 2.3%保存率 2.3%16×通常リーチ比106.7K2,499
15Vibe coding is more addictive than any video game ever made…公開・価格A year ago I spent 23 days building an app and scaled it to 21k users and $30k in revenue. I then immediately pivoted into AI B2B SaaS 😭😭 building my startup Meuze to $9M ARR. But honestly, nothing beats the feeling of building and shipping your own apps. So here’s 9 minutes of everything I’ve learned about building solo apps that actually make money.@swerikcodes · 1日前元投稿ARR·$9M/年自己申告$9M/年自己申告ARR4.1×通常リーチ比22.1K694
16How I Made $1M Building 30 Micro-Apps公開・価格コールドスタートOver the past few years, Sanskar has built over 30 products and he just hit $1 million in revenue. In this episode, he shares his exact process for finding product ideas, the marketing strategies that helped him generate $1M, and how he does it all by himself. This is a masterclass in how to build a portfolio of tiny bets! *Side project ideas you can build with your 9-5:* https://clickhubspot.com/83ig Say hi to Sanskar: https://www.instagram.com/sanskarr.tiwari/ & https://twitter.com/IndianAppGuy Check out his projects: https://www.sanskartiwari.io/ 🔔 Follow the Second Channel: @StarterStoryBuild 🏁 We're hiring: starterstory.com/jobs Chapters: 0:00 - 30 products, $1M 1:03 - Meet Sanskar! 1:25 - Building 8 projects 2:54 - Numbers behind the business 3:26 - More side project ideas 4:04 - Common themes in the projects 5:29 - How do you get here? 7:15 - Finding app ideas 9:54 - Building and tech stack 10:24 - Marketing methods 12:49 - Running experiments 13:20 - Final advice1 5:07 - Reflections and takeaways! This video is an educational case study of this founder’s experience. It is not financial advice and does not guarantee any income or results. Every business is different and your results may vary. https://www.youtube.com/watch?v=X2T92MVx7xsyt/StarterStory · 4日前元投稿累計売上·$1M 累計自己申告$1M 累計自己申告累計売上30×通常リーチ比108.5K1,776
17New Format Alert 🚨🚨 Hand Drawn Explainer Format有料広告This looks very engaging makes you want to see what hes going to draw next. Can see why this can work well Found this on @gethookdai via their api key @FedotOff90 Looking forward for when we can filter ads by awareness levels@whitehatmrr · 2日前元投稿言及製品GGetHookd保存率 1.9%保存率 1.9%言及製品GGetHookd16×通常リーチ比22.4K426
1850 places to launch your startup:公開・価格コールドスタート1. http://reddit.com/ 2. http://feedmystartup.com/ 3. http://trustpilot.com/ 4. http://submitsaas.com/ 5. http://whatlaunched.today/ 6. http://aitools.neilpatel.com/ 7. http://g2.com/ 8. http://crunchbase.com/ 9. http://financesonline.com/ 10. http://devpost.com/ 11. http://geekwire.com/ 12. http://devhunt.org/ 13. http://goodfirms.com/ 14. http://hashnode.com/ 15. http://f6s.com/ 16. http://indiehackers.com/ 17. http://alternativeto.net/ 18. http://stackshare.io/ 19. http://brownbook.net/ 20. http://news.ycombinator.com/ 21. http://fazier.com/ 22. http://dang.ai/ 23. http://activesearchresults.com/ 24. http://softwaresuggest.com/ 25. http://toolpilot.ai/ 26. http://startupfa.me/ 27. http://peerlist.io/ 28. http://microlaunch.net/ 29. http://theresanaiforthat.com/ 30. http://saasworthy.com/ 31. http://betalist.com/ 32. http://comparecamp.com/ 33. http://tinystartups.co/ 34. http://saashub.com/ 35. http://x.com/ 36. http://viesearch.com/ 37. http://uneed.best/ 38. http://linkcentre.com/ 39. http://toolify.ai/ 40. http://magicbox.tools/ 41. http://althunt.io/ 42. http://500.tools/ 43. http://getlatka.com/ 44. http://betterlaunch.co/ 45. http://startupxplore.com/ 46. http://futurepedia.io/ 47. http://sideprojectors.com/ 48. http://serchen.com/ 49. http://aitoolly.com/ 50. http://daniellaunches.com/@miracle_nnnn · 12日前元投稿feedmystartup.com言及製品TThere's An AI For ThatCCrunchbase保存率 1.0%feedmystartup.com保存率 1.0%言及製品TThere's An AI For ThatCCrunchbase88×通常リーチ比110.1K1,120
19AI Agents are too good at marketing now有料広告I sit down with Cody Schneider, to break down how to become a top 0.1% marketer with GrokBot, Claude Code, and the tools around them. Cody shows the environment an agent needs to do marketing work: data in a warehouse, write access to ad platforms, and API tools for images, video, and leads. We build static ads live for Idea Browser, Late Checkout, Cursor, and more, then make a UGC avatar video ad with motion graphics for about $5. I add two pieces of my own: a swipe warehouse of creative references and a creative director agent that scores every ad. If you build products and hear crickets, this episode gives you workflows you can set up today. Timestamps 00:00 – Intro 04:29 – Agents are now Marketers 09:56 – Data Pipelines & Warehouses 13:56 – Getting your agent access to data 16:15 – The tools for your agent 18:08 – Agents become.1% marketers 20:43 – Swipe Warehouse and Context 22:35 – Creating Static Ads 29:08 – Static Ads Results 30:03 – Creating UGC Avatar Ads 36:28 – Running the Workflow 37:58 – UGC Ad Results 39:51 – Human Creators Through Tribe and Sideshift 41:42 – Reviewing the Static Ads 43:29 – The role of Creative Director 50:49 – Closing Thoughts Links Mentioned: Cody's Marketing Skills: https://startup-ideas-pod.link/cody-marketing-skills Guide for setting up Facebook Developer Token: https://startup-ideas-pod.link/Facebook-ads-developer-token-setup Key Points • Agents do marketing's middle work once they have data, platform access, and tools. • A data pipeline into a warehouse gives agents full-funnel data and keeps them off rate-limited APIs. • Agents write to Facebook and Google Ads through their APIs and read data only from the warehouse. • One skill turns a brand URL into five researched, on-brand static ads. • A UGC avatar ad with motion graphics costs about $5, compared with $300 to $500 from humans. • Creative velocity wins, since Facebook's algorithm matches good creative to the right buyer. Numbered Section Summaries 1. Agents are now Marketers Cody says a static ad used to need a graphic designer and a copywriter, and a UGC video needed a creator, a video editor, and a motion graphics designer. Now GrokBot, Claude Code, or Dot https://www.youtube.com/watch?v=uJuxenfe-NUyt/GregIsenberg · 3日前元投稿startup-ideas-pod.linkstartup-ideas-pod.link6.9×通常リーチ比103.3K2,043
20从社区帖子聚合逾一万五千本书公開・価格HackerBooks 从 Hacker News 帖子提取逾一万五千本书,以至少两人提及作为收录门槛,展示社区内容聚合思路。@vikingmute · 11日前元投稿hackerbooks.org保存率 2.2%hackerbooks.org保存率 2.2%11×通常リーチ比92.9K2,027