Viktor Smirnov

@Hartdrawss Dos anyone have experience with scaling on supabase. Software is on track to hit 10k users soon. What needs to be taken into consideration to make sure it runs smoothly? Any advice

25 signs your VIBE CODED app will BREAK at 500 users : Save this before you go live ! 1/ no load testing before launch > you don't know where it breaks because you've never pushed it > one traffic spike and you're debugging live in production 2/ session data stored in server memory > works on one instance > breaks the moment you need two 3/ file uploads going directly to your app server > disk fills up. server dies. files lost. > move uploads to object storage on day one 4/ synchronous email sending in API routes > slow email provider = slow API response for every request that triggers one > offload to a queue. always. 5/ no queue system for background tasks > everything blocking > one slow task pauses everything behind it 6/ hardcoded secrets in deployment scripts > sitting in your CI logs > visible to anyone with pipeline access 7/ single database with no read replica > all reads and writes hitting one machine > first real traffic spike kills query performance 8/ no CDN in front of static assets > every image served by your app server > 500 concurrent users = 500 image requests hitting your backend 9/ DB migrations running automatically on app start > two instances deploy at the same time > both run migrations. race condition. data inconsistency. 10/ no database backup ever tested with a restore > you have backups > you've never actually restored from one 11/ unindexed foreign key columns > every JOIN is a full scan > slow at 100 rows. broken at 100,000. 12/ no rate limiting anywhere > 500 users. one of them is a bot. > your server is now a bot server 13/ API responses with no compression > JSON payloads sent uncompressed > 10x the bandwidth they need to use 14/ no error alerting configured > app crashes at 3 AM > you find out when a user emails you at 9 AM 15/ transactions not used for multi-step writes > step 1 succeeds. app crashes. step 2 never runs. > data is now inconsistent permanently 16/ health check endpoint missing > load balancer sends traffic to crashed instances > users get 502s. you get support emails. 17/ memory leaks in long-running processes > memory grows slowly. server hits 100%. > everything grinds to a halt. restart. repeat. 18/ no graceful shutdown handling > deploy kills active requests > users mid-action get errors with no retry 19/ dependent on a third-party API with no fallback > that API goes down > your core feature goes down with it 20/ all logs written to local disk > logs rotate off > incident happens. no history to debug with. 21/ no circuit breaker on external calls > external service is slow > your thread pool fills waiting for it. everything queues. 22/ unparameterized search queries > search with any real data volume > 5-second response times at scale 23/ no connection timeout on outbound HTTP calls > external API hangs > your thread hangs with it. indefinitely. 24/ WebSockets not handled by a stateful service > horizontal scale breaks real-time features > every user gets disconnected 25/ no runbook for common incidents > something breaks at 2 AM > nobody knows what to do. everyone panics. you can ship fast and still build something that holds. bookmark this before you go live.

@code_codeforge whali.co.uk

Drop your project URL Let’s drive some traffic

@DeRonin_ Would be cool to get some actual numbers on the ROAV ( return on ai video)

startup idea for you build an AI UGC machine and sell it to e-commerce brands who are paying $150-500 per video from creators on Fiverr what is it? UGC ads get 10x higher conversions and 50% lower ad costs than branded content. every e-commerce brand needs 10-50 new UGC videos per month. most are paying creators $150-500 per video. that's $1,500-25,000/mo just on content your tool generates the same thing with AI for $2-5 per video. same talking head format, same "real person reviewing a product" energy. 99% cheaper how to build it with fully open-sourced stack ↓ 1. use LivePortrait (16k+ github stars) or SadTalker (13k+ stars) for AI talking head generation. feed it one photo → it generates a realistic person talking. no actors, no filming, no studio 2. use Coqui TTS or XTTS v2 for voice cloning. clone any voice from a 6-second clip. 17 languages. your client's brand voice, replicated infinitely 3. use GPT or Claude to generate the scripts. feed it the product description + target audience → it writes 10 UGC scripts in 30 seconds. hooks, pain points, CTAs, all formatted for TikTok and Reels 4. stitch it together with FFmpeg. auto-add captions, product shots, background music. output vertical video ready to upload 5. wrap it in a simple UI with Next.js + Supabase. your client logs in, types their product name, picks a face and voice, clicks generate. 3 minutes later they have 10 UGC videos ready to test 6. pick one niche. dropshippers, Amazon sellers, DTC skincare brands, supplement companies, app developers. wrap it in their language. "AI UGC ads for skincare brands", NOT "AI video generator" 7. charge $299-499/mo for unlimited generations. Arcads charges $110/mo with limits. human creators charge $150-500 per single video. you're 10x cheaper than creators and more flexible than Arcads. the math sells itself 8. build media around results. post ad performance comparisons on X. "AI UGC ad: $0.43 CPC, 4.2% CTR vs branded ad: $1.80 CPC, 0.9% CTR." that's the content that gets you clients without cold outreach 9. once you own one niche, expand. add AI product photography. add AI ad copy generation. add automated A/B testing across platforms. now you're not a video tool, you're the entire creative department Arcads just raised $16M. Creatify just raised $15.5M. the market is validated but nobody built the open-source version yet the models are free on GitHub. the deployment tools are mature. the demand is daily: brands retesting creatives every single week the $10B+ UGC market is growing 29% per year. the tools to build this cost $0. the customer relationship is where the margin lives you can build this as one person. you don't need actors. you don't need a studio. you need a GPU, a niche, and a landing page, THAT'S ALL btw, if you love such as format of ideas exploration in public, drop your fat LIKE, maybe i will go on it as a rubric since basically i get 5-10 ideas per day and don't have time to build it why they should stay only in my notetaker lol

@romanbuildsaas How safe is this. LinkedIn has some pretty tight guidelines

After wrestling with Cursor for 3 hours, my LinkedIn auto-commenter is finally ready. As soon as I post a lead magnet, it automatically replies to every comment with the resource link, using randomized delays to keep it natural. People don’t realize it, but as a marketer, being able to build your own tools is an unfair advantage.

@chhddavid How does the self maintain work?

so you're telling me Claude Code Opus 4.7 can now... - scan an entire website - build it as a mobile app - prepare for App Store submission - self-maintain the app without any human in the loop?!? it's so over...

@DeRonin_ Does this work for twitter

I automated my content engine and 2 hrs/day dropped to 10 min [ what’s new in v2 ]: - 9 platforms scraped while I sleep → 2,000+ topics/day - a 5-signal scoring brain that filters down to the 10 that matter - voice DNA writer.. same tone, different structure every time - a self-learning loop that remembers every approve and decline - profile DNA — knows exactly what goes viral on MY account v1 was a brain with no body v2 has eyes, a filter, and memory + fully automated Here’s how to build it step-by-step ↓ [ The architecture]: /content-engine ├── scrapers/ (9 platform scrapers) ├── extension/ (chrome ext for X, linkedin, reddit) ├── ai/ │ ├── ranker.py (5-signal scoring brain) │ ├── content_writer.py (voice DNA + structures) │ ├── profile_analyzer.py (your positioning DNA) │ └── sentiment_analyzer.py ├── publisher/ (export + time slot scheduling) ├── gui/dashboard.py (streamlit command center) ├── ingest_server.py (local server on localhost) └── data/content_engine.db (everything stored locally) let me walk you through each layer ↓ LAYER 1: Research engine 9 sources scanned 24/7 (X, reddit, YT, HN, github, trends + chrome ext for reddit and linkedin) every post you scroll past gets tagged and stored locally LAYER 2: Scoring brain every topic scored on 5 signals: - freshness (0.20) - velocity (0.25) - virality (0.25) - relevance (0.20) - uniqueness (0.10) velocity 8+ → forced min score of 7. catches late bloomers that suddenly explode 2,000 topics → top 10 ranked LAYER 3: Voice DNA writer not one structure every time. system picks the format: - short take - tactical playbook - QT contrast - contrarian - resource drop - proof post a voice guardian auto-rewrites anything that fails: lowercase ratio, no hashtags, no corporate words LAYER 4: Dashboard Streamlit dark theme. 5 tabs review queue = tinder for content. swipe approve, swipe decline LAYER 5: Publishing no auto-posting. zero account risk approve → pick a slot (8am / 12pm / 5pm) → exports a .txt → copy / paste / post also auto-drafts a linkedin version of every approved tweet LAYER 6: Self-learning loop every click logged. weekly the system embeds your decline notes and re-tunes the scoring brain month 1: you approve 30% month 3: 70% pre-filtered month 6: 10 min/day LAYER 7: Profile DNA analyzes your past tweets. tells you exactly which pillars, formats, and hooks perform best on YOUR account the scoring brain uses it to prioritize what already works for you daily run: open dashboard → 10 min reviewing → post 3x → close total cost: ~$15/month everything else: local, sqlite, no cloud, no subscription unfortunately I couldn’t paste in long-form format initial description which was made before but if this hits 2,000 likes I drop the full build guide with every prompt you need to ship it in claude code reply "ENGINE" + RT and I'll DM you access to test it (follow me first so I can write) save this so you don't lose it

@jakecastilloooo Any advice for software/app builders for defensibility against Claude releasing a similar tool

I started Cal AI at 29. A mortgage. $40K in student loans. A girlfriend I was supposed to be proposing to that year. When I told my mom and my girlfriend I was quitting, both said the same thing: "What's the worst that could happen?" 18 months later we sold the company.

@learnwithella SEO

I just built a Claude Code SEO agent that replaces your $200/mo. Ahrefs subscription 🤯 One prompt → keyword gaps found, competitors analyzed, content written in your brand voice, rankings tracked weekly. All inside Claude Code. Perfect for DTC brands and agencies who know SEO matters but never have the bandwidth to actually do it consistently. If your SEO workflow looks like this — log into Ahrefs once a month, export a CSV, skim it for 5 minutes, close the tab, tell yourself you'll write that blog post next week, never do... This agent runs the entire loop for you: → Connects to Google Search Console and pulls your real ranking data → Finds your "gap zone" — keywords sitting at positions 5-20, one article away from page 1 → Uses Apify to scrape who's outranking you and breaks down exactly why they're winning → Interviews you once about your brand, customers, and positioning — then never asks again → Writes content in your voice — not generic AI slop that tanks after 90 days → Tracks rankings weekly and feeds what's working back into the next cycle → Optimizes your product listings for AI shopping — so you show up when someone asks ChatGPT for a recommendation, not just Google No $200/month tools you open once and forget. No freelancers writing content that sounds like everyone else. No manually checking rankings and forgetting to act on it. What you get: - Keyword cards with a specific action recommendation for each gap zone opportunity - A competitive breakdown — who's beating you and the exact fix for each keyword - A weekly content plan generated from your real GSC data - A brand voice profile Claude uses for every article it writes - Product listing optimization for AI shopping (ChatGPT, Gemini, Perplexity) — the new SEO nobody's doing yet Built 100% in Claude Code with Google Search Console. I put together a full playbook with the skill files, brand interview, and the exact weekly workflow. Want it for free? > Like this post > Comment "SEO" And I'll send it over (must be following @learnwithella so I can DM)

@denohawari LLM

we helped a SaaS company rank #1 in ChatGPT • $1.8M+ total revenue • 8,200%+ traffic growth • $35K+ monthly SEO traffic value all powered by our LLM SEO framework. most companies have no idea this is even happening: buyers are rapidly moving to LLM-driven discovery tools like ChatGPT, Claude, and Gemini if your brand isn’t showing up there, your competitors are straight up stealing your traffic and conversions. I broke down our entire methodology into a 800-word guide: • how we structure content LLMs consistently surface • data from the 8,200% growth case study • the step-by-step system that drove the $1.8M+ revenue lift • the AI-first keyword discovery framework we use across LLM platforms • the on-page signals that unlock visibility in ChatGPT, Claude, and Gemini this SaaS company's entire organic engine was built through this new AI-first SEO method now you can just steal it want the full breakdown? 1. like + follow 2. comment “LLM” and I’ll send it to you

@ErnestoSOFTWARE How much is it costing you to run this per day?

@AlfieJCarter GROUP

I'm building the BIGGEST cold email community in the world. It's perfect to network with other killers in your space. And you'll find strategies that are not shared anywhere else. Comment "GROUP" and I'll invite you (make sure you're following)

@ItsAnonApe #OPENCLAW

@reachvaldo How

You still haven't built your first Clawdbot? like + reply “How” and I’ll DM you my exact setup system for FREE.

@matt_elevenlabs Congrats! 11B

We just raised $500M at an 11B valuation 🎉 To celebrate, we’re giving away 1,000 free credits so you can test our platform. For the next 6 hours, comment “11B” below and we’ll DM you the credits (must follow) 👇

@LoganTGott System

I automated my LinkedIn client acquisition. Now I close qualified calls every month on autopilot. Most B2B founders struggle with LinkedIn because they're missing the system. They post randomly. Their DMs get ignored. Their lead magnets flop. I spent 18+ months perfecting a framework that solves this: → Targeting filters that identify decision-makers with budget → A system to extract exact pain points your ICP faces → Content creation using their language → Lead magnet strategy to identify leads → DM sequences with follow-ups that actually close deals → Lead list building that generates 100+ qualified connections weekly This is the exact system I use to book calls without cold calling, paid ads, or spammy outreach. One client used this to generate 100+ leads in 30 days. I've packaged the entire framework into a complete training. 1- Follow me 2- Comment "SYSTEM" and I'll send it over. (Must be following for me to DM you)

@nahidulislam404 LEADS

I am giving out contact list of 75 000 Founders and CEOs This list is freshly scraped from X today (quality leads worth $1655) Like, and comment "LEADS" and I will DM you the database! (Must be Following ) (only first 200)

@romanbuildsaas Agents

I built 3 AI agents that run my LinkedIn end-to-end: • They write my posts • They reply to every comment • They find high-intent leads and handle outreach I’m sharing the entire system. Want it? Repost ♻️ so others see it Comment “Agents” and I’ll DM you.

@paolo_scales LI

i generated $119.8k this january ONLY using linkedin... to celebrate i’m giving away EVERY lead magnet i ran in 2025 158-pages. 4-hours of content. the MOST valuable doc on linkedin lead gen like + comment “LI” and i’ll send you EVERYTHING (must be following)