正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

Postgres 19 can query relationships like a GRAPH NOT with a long manual join chain. With a path: customer → bought → product product ← bought ← similar customer similar customer → follows → brand That is a recommendation system in one readable pattern. SQL/PGQ finds the relationship. COLUMNS... show more

alex shapalov

2,256 subscribers

55,524 次观看 • 23 天前 •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

0 条评论

暂无评论

原始帖子的评论将显示在这里

相关视频

Big moment for Postgres! Search has always been Postgres' weak spot, and everyone just accepted it. If you needed a real relevance-ranked keyword search, the default answer was to spin up Elasticsearch or add Algolia and deal with the data sync headaches forever. The problem isn't that Postgres can't do text search. It can. But the built-in `ts_rank` function uses a basic term frequency algorithm that doesn't come close to what modern search engines deliver. So teams end up: - Running a separate Elasticsearch cluster just for search - Building sync pipelines that inevitably drift out of consistency - Paying for managed search services that charge per query - Accepting mediocre search relevance because "good enough" ships faster But this is actually a solvable problem. You can realistically bring industry-standard search ranking directly into Postgres, which eliminates the need for external infra entirely. This exact solution is now available with the newly open-sourced pg_textsearch by Tiger Data - Creators of TimescaleDB, a Postgres extension that brings true BM25 relevance ranking into the database. BM25 is the algorithm behind Elasticsearch, Lucene, and most modern search engines. Now it runs natively in Postgres. Here's what pg_textsearch enables: - True BM25 ranking with configurable parameters (the same algorithm powering production search systems) - Simple SQL syntax: `ORDER BY content 'search terms'` - Works with Postgres text search configurations for multiple languages - Pairs naturally with pgvector for hybrid keyword + semantic search That last point matters a lot for RAG apps. The video below shows this in action, and I worked with the team to put this together. You can now do hybrid retrieval (combining keyword matching with vector similarity) in a single database, without stitching together multiple systems. The syntax is clean enough that you can add relevance-ranked search to existing queries in minutes. pg_textsearch is fully open-source under the PostgreSQL license. You can find a link to their GitHub repo in the next tweet.

Big moment for Postgres! Search has always been Postgres' weak spot, and everyone just accepted it. If you needed a real relevance-ranked keyword search, the default answer was to spin up Elasticsearch or add Algolia and deal with the data sync headaches forever. The problem isn't that Postgres can't do text search. It can. But the built-in `ts_rank` function uses a basic term frequency algorithm that doesn't come close to what modern search engines deliver. So teams end up: - Running a separate Elasticsearch cluster just for search - Building sync pipelines that inevitably drift out of consistency - Paying for managed search services that charge per query - Accepting mediocre search relevance because "good enough" ships faster But this is actually a solvable problem. You can realistically bring industry-standard search ranking directly into Postgres, which eliminates the need for external infra entirely. This exact solution is now available with the newly open-sourced pg_textsearch by Tiger Data - Creators of TimescaleDB, a Postgres extension that brings true BM25 relevance ranking into the database. BM25 is the algorithm behind Elasticsearch, Lucene, and most modern search engines. Now it runs natively in Postgres. Here's what pg_textsearch enables: - True BM25 ranking with configurable parameters (the same algorithm powering production search systems) - Simple SQL syntax: `ORDER BY content 'search terms'` - Works with Postgres text search configurations for multiple languages - Pairs naturally with pgvector for hybrid keyword + semantic search That last point matters a lot for RAG apps. The video below shows this in action, and I worked with the team to put this together. You can now do hybrid retrieval (combining keyword matching with vector similarity) in a single database, without stitching together multiple systems. The syntax is clean enough that you can add relevance-ranked search to existing queries in minutes. pg_textsearch is fully open-source under the PostgreSQL license. You can find a link to their GitHub repo in the next tweet.

Akshay 🚀

215,532 次观看 • 7 个月前

The Meta Creator Marketplace keeps getting better and better. You can now select a Custom or Lookalike audience and see a list of creators with similar audience profiles. This is publicly accessible via the Creator Marketplace API. This means 10 minutes in Claude Code can build a dashboard that constantly uncovers new creators with audience profiles statistically similar to your brand. We used to DREAM OF STUFF LIKE THIS in 2019.

Peter Czepiga

50,534 次观看 • 2 个月前

Now is the best time for founders and brands to take advantage of this AI bubble to actually stand out from their competitors. First thing that potential customer see is your product video/demo, and If I wanted to buy your product, and the presentation you show me looks crap, I will get an impression you cheaped out on the product as well and just pass. A lot of founders/brands sadly fall for that, especially now with AI hype promising fast and cheap content. Just be honest, if you are a potential customer - would you be converted by AI slop, or videos like ones below, that were fundamentally and manually structured and animated to a T for conversion ?

Now is the best time for founders and brands to take advantage of this AI bubble to actually stand out from their competitors. First thing that potential customer see is your product video/demo, and If I wanted to buy your product, and the presentation you show me looks crap, I will get an impression you cheaped out on the product as well and just pass. A lot of founders/brands sadly fall for that, especially now with AI hype promising fast and cheap content. Just be honest, if you are a potential customer - would you be converted by AI slop, or videos like ones below, that were fundamentally and manually structured and animated to a T for conversion ?

Leon Fucak

61,980 次观看 • 5 个月前

I just vibe-coded a Shopify Reviews Scraper that swipes all your competitors' customer reviews instantly. 🤯 Paste any competitor's product URL → pull every review in under 30 seconds → export to CSV. Built 100% in Codex. Perfect for brands and agencies who want to mine competitor voice-of-customer data at scale and turn it into winning ad creative. Here's how it works: → Drop a Shopify product URL into the tool → Set your review limit (50, 100, 500+) → Hit scrape — it launches a browser, finds the review widget, pulls every review → Export clean rows: rating, body, author, date → Feed the CSV to Claude and ask "what do customers love and hate about this product" → Turn the output into ad angles, hooks, and headlines No more paying $99/mo for clunky review scraping SaaS that locks you behind credits. What you get: - Any Shopify store's reviews in 30 seconds - Clean structured data (rating, body, author, date) - CSV or JSON export — drops straight into Sheets or an LLM - Unlimited scrapes, no per-review fees - A voice-of-customer firehose you can turn into ad creative on demand This is essentially a competitor review intelligence engine in a box. I'm giving away the full GitHub repo so you can clone it and run it yourself for free. Want the repo? > Like this post > Comment "SCRAPE" And I'll send it over (must be following so I can DM)

I just vibe-coded a Shopify Reviews Scraper that swipes all your competitors' customer reviews instantly. 🤯 Paste any competitor's product URL → pull every review in under 30 seconds → export to CSV. Built 100% in Codex. Perfect for brands and agencies who want to mine competitor voice-of-customer data at scale and turn it into winning ad creative. Here's how it works: → Drop a Shopify product URL into the tool → Set your review limit (50, 100, 500+) → Hit scrape — it launches a browser, finds the review widget, pulls every review → Export clean rows: rating, body, author, date → Feed the CSV to Claude and ask "what do customers love and hate about this product" → Turn the output into ad angles, hooks, and headlines No more paying $99/mo for clunky review scraping SaaS that locks you behind credits. What you get: - Any Shopify store's reviews in 30 seconds - Clean structured data (rating, body, author, date) - CSV or JSON export — drops straight into Sheets or an LLM - Unlimited scrapes, no per-review fees - A voice-of-customer firehose you can turn into ad creative on demand This is essentially a competitor review intelligence engine in a box. I'm giving away the full GitHub repo so you can clone it and run it yourself for free. Want the repo? > Like this post > Comment "SCRAPE" And I'll send it over (must be following so I can DM)

Mike Futia

29,870 次观看 • 3 个月前

$you can legally steal any viral ugc, rewrite it for your product, and generate it with AI UGC. people are generating photorealistic AI actors that hold real products in their hands and reading scripts that convert like real UGC. Vodafone already ran a full TikTok campaign with AI influencers. same engagement, same conversions, fraction of the cost here's the ugc system anyone can run today: - find a product that hits an emotional pain point (aging skin, insecurity, frustration). one retinol serum video has 8M views and 300k likes with comments begging for the link - download the viral video, transcribe it with Gemini, then feed the transcript + your product + your audience into Claude. it spits out 3 scripts that sound like a friend talking, not an ad - build your actor in any ai ugc platform: filter by age, location, accessories, or generate one from a prompt. nano banana places your exact product in her hand with real lighting and shadows - create two versions of the same actor. no product for the problem hook, product in hand for the solution. that switch is what makes it feel like a real story - use the scenes feature to generate actual application footage: fingertips dabbing serum, circular motions, natural hand movement. not just a talking head - a UGC creator charges $200 to $600 for this exact video. it takes 2 minutes and you can make 10 variations tomorrow the brands winning right now aren't the ones with the biggest budgets. they're the ones testing fastest. reply "ugc" + RT and i'll send you the full video so you can build this too.$

you can legally steal any viral ugc, rewrite it for your product, and generate it with AI UGC. people are generating photorealistic AI actors that hold real products in their hands and reading scripts that convert like real UGC. Vodafone already ran a full TikTok campaign with AI influencers. same engagement, same conversions, fraction of the cost here's the ugc system anyone can run today: - find a product that hits an emotional pain point (aging skin, insecurity, frustration). one retinol serum video has 8M views and 300k likes with comments begging for the link - download the viral video, transcribe it with Gemini, then feed the transcript + your product + your audience into Claude. it spits out 3 scripts that sound like a friend talking, not an ad - build your actor in any ai ugc platform: filter by age, location, accessories, or generate one from a prompt. nano banana places your exact product in her hand with real lighting and shadows - create two versions of the same actor. no product for the problem hook, product in hand for the solution. that switch is what makes it feel like a real story - use the scenes feature to generate actual application footage: fingertips dabbing serum, circular motions, natural hand movement. not just a talking head - a UGC creator charges $200 to $600 for this exact video. it takes 2 minutes and you can make 10 variations tomorrow the brands winning right now aren't the ones with the biggest budgets. they're the ones testing fastest. reply "ugc" + RT and i'll send you the full video so you can build this too.

Sulfur

17,525 次观看 • 1 个月前

TIP: TRY AGAIN: FATIGUE EDITION Waitress worked a full shift just to get tipped like it was 1998 Is a $3 tip on $55 disrespectful or just cheap? Would YOU say something if you were the waitress? A waitress hustles all night…refills drinks before they even ask, brings extra ranch like a hero, checks in with perfect timing… Bill comes out: $55. Customer grins like she just won the lottery…leaves $3. THREE. Not even enough for a decent gas station snack. Customer is smiling. Waitress is blinking like her soul just lagged. She picks up the receipt thinking maybe it’s a joke…nah…that’s the full tip. No sequel. No bonus scene. If service was good, what’s the minimum acceptable tip?

TIP: TRY AGAIN: FATIGUE EDITION Waitress worked a full shift just to get tipped like it was 1998 Is a $3 tip on $55 disrespectful or just cheap? Would YOU say something if you were the waitress? A waitress hustles all night…refills drinks before they even ask, brings extra ranch like a hero, checks in with perfect timing… Bill comes out: $55. Customer grins like she just won the lottery…leaves $3. THREE. Not even enough for a decent gas station snack. Customer is smiling. Waitress is blinking like her soul just lagged. She picks up the receipt thinking maybe it’s a joke…nah…that’s the full tip. No sequel. No bonus scene. If service was good, what’s the minimum acceptable tip?

𝐌𝐑. 𝐖𝐇𝐈𝐓𝐄 ™

39,809 次观看 • 5 个月前

Rivian has announced in a new blog post that it is still aiming to release point-to-point assisted driving later this year, with widespread rollout in 2027. "Enter an address and supervise while your vehicle follows the route from start to finish, handling city streets, highway interchanges and everything in between. A limited rollout begins later this year, with a widespread customer rollout targeted for 2027. The path from Universal Hands-Free to Point-to-Point is shorter than it looks from the outside, because so much of the work is already done. Every mile our fleet drives makes our Large Driving Model smarter for the next one. That's the engine driving R2 autonomy: not just a sensor suite, but a constantly learning fleet powering a vehicle that keeps evolving right in your driveway."

Rivian has announced in a new blog post that it is still aiming to release point-to-point assisted driving later this year, with widespread rollout in 2027. "Enter an address and supervise while your vehicle follows the route from start to finish, handling city streets, highway interchanges and everything in between. A limited rollout begins later this year, with a widespread customer rollout targeted for 2027. The path from Universal Hands-Free to Point-to-Point is shorter than it looks from the outside, because so much of the work is already done. Every mile our fleet drives makes our Large Driving Model smarter for the next one. That's the engine driving R2 autonomy: not just a sensor suite, but a constantly learning fleet powering a vehicle that keeps evolving right in your driveway."

Sawyer Merritt

174,885 次观看 • 6 天前

this brazilian ai tiktok shop creator is quietly printing with one repeatable ugc format same face same store background same casual product demo style ai swaps the product in her hands keeps the lighting, framing, and pacing identical and posts daily across dozens of offers no filming days no brand negotiations no creator management it looks like one real influencer but it’s actually a content engine whoever copies this in first world markets early is going to push past $300k–$500k/month fast rt + comment “shop” and i’ll dm the system (follow for dm)

Alessandro

90,373 次观看 • 6 个月前

Claude Code + Nano Banana 2 is f*cking cracked for advertorials 🤯 One prompt → a complete presell page with editorial copy, AI product photography, testimonials, and pricing — ready to paste into Shopify. Built 100% in Claude Code. Perfect for DTC brands and agencies running advertorials on Meta who need 5-10 different pages per month but can't keep paying $1,500 each. If you're briefing copywriters, waiting days for a draft, giving notes, waiting again, and still only getting one or two new pages per month... This system eliminates the entire loop: → Enter your brand, product, target customer, and unique mechanism → Pick a style preset (clinical editorial, news exposé, lifestyle magazine, warm and trustworthy) → Claude writes the full page — urgency banner to guarantee to final CTA → Nano Banana 2 generates product images and mechanism diagrams inline → Get back a complete HTML page following the same DR structure that's already scaling on Meta No copywriter back-and-forth. No designing from scratch. No starting from a blank page every time. What you get: → A production-ready HTML advertorial page you paste into Shopify → DR copy structure extracted from real pages scaling on Meta right now → AI-generated product photography and diagrams matched to your brand → 4 style presets that shift tone, colors, and authority framing per niche → A fully customizable system prompt — swap in your own templates and it follows those instead I built 3 complete advertorial pages for 3 different brands in under 5 minutes. Skincare, supplements, and pet products. All different styles, all production-ready. I put together a full playbook with the exact system prompt so you can get this running yourself. Want access for free? > Like this post > Comment "CLAUDE" And I'll send it over (must be following so I can DM)

Mike Futia

34,317 次观看 • 5 个月前

A waiter accidentally spilled one drop of juice on a customer—and her response was to fling food all over him in anger. That’s not “standing up for yourself.” That’s abuse. No service worker should ever be treated like a punching bag over a simple mistake. At what point does bad behavior cross the line? Throwing food at someone can absolutely be considered assault, depending on local laws and circumstances. Either way, it’s unacceptable. If you were the manager, would you immediately remove the customer? Call the police? Ban them for life? And if you were the waiter—would you walk away, press charges, or just quit on the spot? Mistakes happen. Abuse is a choice. 🍽️🚫

A waiter accidentally spilled one drop of juice on a customer—and her response was to fling food all over him in anger. That’s not “standing up for yourself.” That’s abuse. No service worker should ever be treated like a punching bag over a simple mistake. At what point does bad behavior cross the line? Throwing food at someone can absolutely be considered assault, depending on local laws and circumstances. Either way, it’s unacceptable. If you were the manager, would you immediately remove the customer? Call the police? Ban them for life? And if you were the waiter—would you walk away, press charges, or just quit on the spot? Mistakes happen. Abuse is a choice. 🍽️🚫

TheRealCherokeeOwl 🦉

164,462 次观看 • 7 个月前

Jeff Bezos just described AI in three words that make most of the economy temporary. Bezos: “AI is real and it is going to change every industry. In fact it’s a very unusual technology in that regard in that it’s a horizontal enabling layer.” Horizontal enabling layer. Not a product. Not a platform. Not a feature. A layer. Underneath everything. Everyone is asking which AI company wins. Bezos is telling you that is the wrong question entirely. A horizontal layer does not produce winners. It produces a new floor. Everything standing on the old one either gets rebuilt or gets erased. This has happened exactly twice in modern history. Electricity. The internet. Both times the same pattern. The new layer appeared. The old economy kept running above it. Revenue held. Careers continued. Everything looked normal. Then quietly and permanently the entire structure reorganized around the new substrate. The people who did not move were not outcompeted. They were made structurally irrelevant. Not because they were wrong. Because the ground they stood on stopped being ground. Bezos is telling you it is happening a third time. Not with a product. Not with a platform. With intelligence itself becoming infrastructure. A horizontal layer does not compete with the expert. It makes expertise free. It hands a 22 year old with zero credentials the same cognitive output you spent a decade and a quarter million dollars learning to produce. For $20 a month. That is not disruption. Disruption replaces a product with a better product. This dissolves the scarcity your entire career was priced on. Not because the work disappeared. Because the wall around it did. Every profession that exists because knowledge is hard to acquire. Every company that profits because analysis takes time. Every industry that survives because complexity locks outsiders out. All of it rests on a single assumption. That cognition is scarce. AI does not challenge that assumption. It retires it. The people who understand this are already rebuilding. Quietly. Deliberately. While everyone else argues about whether the thing underneath them is real. Bezos did not give you a prediction. He gave you a position on a map. You are either above the new layer or beneath it.

Jeff Bezos just described AI in three words that make most of the economy temporary. Bezos: “AI is real and it is going to change every industry. In fact it’s a very unusual technology in that regard in that it’s a horizontal enabling layer.” Horizontal enabling layer. Not a product. Not a platform. Not a feature. A layer. Underneath everything. Everyone is asking which AI company wins. Bezos is telling you that is the wrong question entirely. A horizontal layer does not produce winners. It produces a new floor. Everything standing on the old one either gets rebuilt or gets erased. This has happened exactly twice in modern history. Electricity. The internet. Both times the same pattern. The new layer appeared. The old economy kept running above it. Revenue held. Careers continued. Everything looked normal. Then quietly and permanently the entire structure reorganized around the new substrate. The people who did not move were not outcompeted. They were made structurally irrelevant. Not because they were wrong. Because the ground they stood on stopped being ground. Bezos is telling you it is happening a third time. Not with a product. Not with a platform. With intelligence itself becoming infrastructure. A horizontal layer does not compete with the expert. It makes expertise free. It hands a 22 year old with zero credentials the same cognitive output you spent a decade and a quarter million dollars learning to produce. For $20 a month. That is not disruption. Disruption replaces a product with a better product. This dissolves the scarcity your entire career was priced on. Not because the work disappeared. Because the wall around it did. Every profession that exists because knowledge is hard to acquire. Every company that profits because analysis takes time. Every industry that survives because complexity locks outsiders out. All of it rests on a single assumption. That cognition is scarce. AI does not challenge that assumption. It retires it. The people who understand this are already rebuilding. Quietly. Deliberately. While everyone else argues about whether the thing underneath them is real. Bezos did not give you a prediction. He gave you a position on a map. You are either above the new layer or beneath it.

Dustin

104,086 次观看 • 1 个月前

I just built a Claude skill that writes 20 Meta ad hooks in 60 seconds 🤯 Give it your product, your audience, and your best-performing angles → it writes hooks across 10 proven frameworks, each one targeted at a specific customer pain point. All inside Claude Cowork. Perfect for DTC brands and agencies who are still writing hooks from scratch every time they need new creative — staring at a blank doc, scrolling competitors for inspiration, and recycling the same 3 angles because you ran out of ideas two weeks ago. If you're launching Meta Ads and your hook writing process looks like this — open a Google Doc, try to remember what worked last time, write 5 hooks that all sound the same, run them, 4 flop, go back to the doc, repeat ... This skill replaces the entire process: → You give it your product name, key benefits, and target customer → It writes hooks across 10 frameworks: problem-solution, curiosity gap, bold claim, social proof, before/after, us vs them, question, contrarian, urgency, and storytelling → Each hook targets a specific pain point — not generic "Shop now" copy → Generates 2 variations per framework so you have options to test → Outputs everything organized by framework with notes on when to use each one → Takes about 60 seconds No blank page. No recycling the same 3 angles. No writing 5 hooks that all sound like the same ad. What you get: → 20 hooks across 10 proven frameworks, ready to drop into your ads → Each hook written for a specific customer pain point, not a generic audience → Framework labels so you know which hook type you're testing → A reusable skill — run it for every new product, every new campaign, every new angle sprint → Works from a product brief — no API connection, no CSV export, no setup beyond installing the skill One product brief. 20 hooks. 60 seconds. I put together the full skill file plus a playbook showing how to install it, customize the frameworks, and run your first hook sprint. Want it for free? > Like this post > Comment "HOOKS" And I'll send it over (must be following so I can DM)

I just built a Claude skill that writes 20 Meta ad hooks in 60 seconds 🤯 Give it your product, your audience, and your best-performing angles → it writes hooks across 10 proven frameworks, each one targeted at a specific customer pain point. All inside Claude Cowork. Perfect for DTC brands and agencies who are still writing hooks from scratch every time they need new creative — staring at a blank doc, scrolling competitors for inspiration, and recycling the same 3 angles because you ran out of ideas two weeks ago. If you're launching Meta Ads and your hook writing process looks like this — open a Google Doc, try to remember what worked last time, write 5 hooks that all sound the same, run them, 4 flop, go back to the doc, repeat ... This skill replaces the entire process: → You give it your product name, key benefits, and target customer → It writes hooks across 10 frameworks: problem-solution, curiosity gap, bold claim, social proof, before/after, us vs them, question, contrarian, urgency, and storytelling → Each hook targets a specific pain point — not generic "Shop now" copy → Generates 2 variations per framework so you have options to test → Outputs everything organized by framework with notes on when to use each one → Takes about 60 seconds No blank page. No recycling the same 3 angles. No writing 5 hooks that all sound like the same ad. What you get: → 20 hooks across 10 proven frameworks, ready to drop into your ads → Each hook written for a specific customer pain point, not a generic audience → Framework labels so you know which hook type you're testing → A reusable skill — run it for every new product, every new campaign, every new angle sprint → Works from a product brief — no API connection, no CSV export, no setup beyond installing the skill One product brief. 20 hooks. 60 seconds. I put together the full skill file plus a playbook showing how to install it, customize the frameworks, and run your first hook sprint. Want it for free? > Like this post > Comment "HOOKS" And I'll send it over (must be following so I can DM)

Mike Futia

17,007 次观看 • 4 个月前

Claude Code + ChatGPT Images 2.0 is f*cking cracked 🤯 I rebuilt my static ad system inside Claude Code on the new ChatGPT Images 2.0 model. One brand name + one URL = 40 production-ready static ads. All inside Claude Code. Perfect for DTC brands and agencies who need high-volume ad creative without briefing a designer or spending hours in Canva. If you're finding winning ad concepts on Meta and manually recreating them one at a time — copying prompts, pasting product details, tweaking aspect ratios, downloading, organizing... This system eliminates the entire loop: → Give Claude a brand name and URL → It researches the brand's fonts, colors, packaging, and photography style → Builds a Brand DNA document from scratch → Fills in 40 proven ad templates (headline, us vs them, testimonial, UGC, review cards, stat callouts) with brand-specific details → Fires every prompt to ChatGPT Images 2.0 with your product photos as reference → Downloads finished ads into organized folders with an HTML gallery No manual prompt filling. No Canva templates. No copy-pasting between tools. What you get: → 40 ad formats filled with your exact brand colors, fonts, and copy → Text that actually renders correctly (the new model handles dense copy, logos, and multi-language callouts cleanly) → Product photos passed as reference so the model matches your real packaging → A reusable system — new brand, new folder, same pipeline Built 100% in Claude Code with ChatGPT Images 2.0. I put together a DIY playbook showing the exact architecture so you can build this yourself in Claude Code. Want it for free? > Like this post > Comment "CHAT" And I'll send it over (must be following @learnwithella so I can DM)

Ismail Khan

19,829 次观看 • 3 个月前

Claude Code + ChatGPT Images 2.0 is f*cking cracked 🤯 I rebuilt my static ad system inside Claude Code on the new ChatGPT Images 2.0 model. One brand name + one URL = 40 production-ready static ads. All inside Claude Code. Perfect for DTC brands and agencies who need high-volume ad creative without briefing a designer or spending hours in Canva. If you're finding winning ad concepts on Meta and manually recreating them one at a time — copying prompts, pasting product details, tweaking aspect ratios, downloading, organizing... This system eliminates the entire loop: → Give Claude a brand name and URL → It researches the brand's fonts, colors, packaging, and photography style → Builds a Brand DNA document from scratch → Fills in 40 proven ad templates (headline, us vs them, testimonial, UGC, review cards, stat callouts) with brand-specific details → Fires every prompt to ChatGPT Images 2.0 with your product photos as reference → Downloads finished ads into organized folders with an HTML gallery No manual prompt filling. No Canva templates. No copy-pasting between tools. What you get: → 40 ad formats filled with your exact brand colors, fonts, and copy → Text that actually renders correctly (the new model handles dense copy, logos, and multi-language callouts cleanly) → Product photos passed as reference so the model matches your real packaging → A reusable system — new brand, new folder, same pipeline Built 100% in Claude Code with ChatGPT Images 2.0. I put together a DIY playbook showing the exact architecture so you can build this yourself in Claude Code. Want it for free? > Like this post > Comment "CHAT" And I'll send it over (must be following so I can DM)

Mike Futia

189,607 次观看 • 4 个月前

i'm still processing this. marc andreessen just said he's "completely in love" with our product on lenny's podcast. the co-founder of andreessen horowitz. the guy who's backed stripe, twitter, airbnb, slack. said this about Wispr Flow. most people think wispr is just better dictation. but marc got what we've been building toward from day one: voice ai that understands intent, not just words. we've spent years in conversations where people couldn't see the difference. where the thing we were obsessed with felt impossible to explain. and here's someone who's seen thousands of startups articulating it perfectly in one sentence. grateful to have Marc Andreessen 🇺🇸 as a customer.

i'm still processing this. marc andreessen just said he's "completely in love" with our product on lenny's podcast. the co-founder of andreessen horowitz. the guy who's backed stripe, twitter, airbnb, slack. said this about Wispr Flow. most people think wispr is just better dictation. but marc got what we've been building toward from day one: voice ai that understands intent, not just words. we've spent years in conversations where people couldn't see the difference. where the thing we were obsessed with felt impossible to explain. and here's someone who's seen thousands of startups articulating it perfectly in one sentence. grateful to have Marc Andreessen 🇺🇸 as a customer.

Tanay Kothari

75,535 次观看 • 4 个月前

$🚨SPACEX DIDN'T ACQUIRE CURSOR FOR TALENT A rocket company buying software for the largest startup acquisition in history Here's what almost nobody realizes: They didn't buy a talent or a coding app. They bought the data underneath it. Cursor's users generate ~150 million lines of code a day. Every keystroke is a record of how real engineers build and fix software The exact raw material to train an AI that can code. You can't buy that on a market. You have to own the thing that produces it. So SpaceX bought a permanent data firehose for Grok. The product is almost a side effect. The entire $60B was covered by a fraction of their market-cap gains since the IPO This is a catch-up bet with Anthropic and openAI You see how they are slowly building it don't you?$

🚨SPACEX DIDN'T ACQUIRE CURSOR FOR TALENT A rocket company buying software for the largest startup acquisition in history Here's what almost nobody realizes: They didn't buy a talent or a coding app. They bought the data underneath it. Cursor's users generate ~150 million lines of code a day. Every keystroke is a record of how real engineers build and fix software The exact raw material to train an AI that can code. You can't buy that on a market. You have to own the thing that produces it. So SpaceX bought a permanent data firehose for Grok. The product is almost a side effect. The entire $60B was covered by a fraction of their market-cap gains since the IPO This is a catch-up bet with Anthropic and openAI You see how they are slowly building it don't you?

Frogify

35,452 次观看 • 5 天前

There’s a reason the LimeWire name still hits people instantly. If you were around in the early internet days, LimeWire was everywhere. Music discovery, file sharing, chaos, excitement. It shaped how a whole generation interacted with the web. That kind of brand memory doesn’t fade and LimeWire is proving it can be reused in a serious way. What’s different now is the foundation. LimeWire Network is the decentralized storage layer of LimeWire, built on BNB Chain. It is not a nostalgia project. It is infrastructure. Storage, transfers, and usage are happening on chain, designed to scale for real applications rather than demos. The growth backs that up. Looking at recent data on lmwrscan, LimeWire Network has already moved into tens of terabytes of stored data, with tens of thousands of uploads and consistent daily activity. Network usage keeps climbing, not spiking once and disappearing. That kind of curve usually shows real users, not incentive farming. And the economics are clear. The $LMWR token sits at the center of the system. Users pay in LMWR to use storage. Node operators earn LMWR for providing resources. Rewards and payments stay inside the ecosystem instead of leaking out to third parties. That loop matters. Most decentralized storage networks struggle because nobody knows they exist. LimeWire doesn’t have that problem. The brand alone opens doors, pulls attention, and lowers the friction for new users to try the product. When you combine that with live usage data and a functioning token economy, the upside starts to look asymmetric. Built on BNB Chain, LimeWire Network also gets the scalability needed if adoption keeps accelerating. That choice signals intent to grow, not just experiment. This feels like a rare case where nostalgia is not the product, it is the distribution layer. Curious how you see it. Are you watching LimeWire because of the brand comeback, the LimeWire Network growth, or the role of the LMWR token in the long run?

ryu 龙

25,416 次观看 • 6 个月前

Claude Code + Gemini Omni + GPT Image 2 is f*cking cracked i just built an AUTOMATED AI UGC content system that generates full ad creatives end to end drop in your product photos and a one line pitch, and the system analyzes your brand, generates a realistic AI avatar, writes the script, renders the video, adds captions, and stitches everything together. in literally one click. if you're still wasting hours generating videos or hiring expensive editors with long turnaround times, this is for you.. here's how it works: > drop in your product photos and brand info > the system finds a reference image that matches your target audience it generates a detailed JSON prompt and creates a hyper realistic starting frame > feeds everything into Gemini Omni and renders the full video with voice outputs and captions, all ready to post and all through Kie AI MCP or Higgsfield MCP (you have full control) the whole process runs inside Claude Code. so you're not jumping between 6 different tabs trying to piece things together. one system handles everything its only a 3 minute setup and 4-12 min per ad. each 30 second ad costs under $3 in API credits which is way cheaper than any editor and 10x faster.. RT + reply "UGC" and i'll send it over (must follow so i can dm)

Miko

58,370 次观看 • 1 个月前