2 new milestones for my little SaaS @DataFast_: ✅ $3,000/day ✅ $4,000/day Growth stalled after hitting $20K MRR, but since adding the AI bot traffic feature, it’s picking up again ($24K MRR now). A good reminder to keep shipping!

I made $83,701 in June 2026. ⭐️ TrustMRR — $30K 📈 DataFast — $21K 🏴‍☠️ Ship or Die — $15K 🧑‍💻 CodeFast — $9K 🐥 Twitter — $4K ⚡️ ShipFast — $3K 🍜 Indie Page — $845 🛡️ ByeDispute — $222 🦐 SuperShrimp — $170 🧾 Zenvoice — $138 🎞️ YouTube — $116 🌱 HabitsGarden — $114 📚 WorkbookPDF — $77 💩 PoopUp — $19 ✂️ Margins: ~85% My portfolio of small bets is on track to make $1M this year, too. It's just me and AI turning my weird thoughts into startups. Keep building!

If you're an affiliate and you've sent 500+ visitors to CodeFast/ShipFast in the last 3 months, please DM your affiliate link and proof so I can compensate you. DataFast affiliate program remains up and running! The SaaS is doing $30K+ MRR now, so it's either to get commissions because people trust the product more:

Marc Lou spent 90 minutes in the tmaker Founders Room and answered everything the gems that stuck with me: 1. his DataFast launch got 1,000 likes and $300 MRR. that's what his entire audience was worth. word of mouth took it from $300 to $25k/month. an audience gives you a shot, it doesn't make the product work 2. he builds "clickbait features". before shipping anything he asks: would users screenshot this? the DataFast globe exists because of that question. your customers sharing beats you promoting, every time 3. he doubled his prices with a 30-day notice to existing users. MRR 2x'd. (maybe I pushed him on this one 😅) 4. his whole AI setup is Codex + localhost. yes, that's it no agent stack, no 10 subscriptions he said 90% of new AI tools are just noise. he is the most productive shipper I know and he has the most boring stack 5. he never kills projects, he "lets them be" all 35 of his projects are still live, support still answered one of them had zero customers for a month, he kept using it himself and kept shipping.. first customer came 2 days before our call next Friday, we do it again opening the tmaker Founders Room for the next 4 days so you can join: see you there

I flew to San Francisco and ended up doing all of this: 🏎️ (self) driving a Cybertruck 💳 attending @stripe sessions 🍻 drinking non alcoholic beer with @jrfarr 💰 making 100 no-VC founders do 20 squats 🤖 making my SaaS @DataFast_ AI agent first 👴🏻 meeting our indie hacking father @csallen 🤝 meeting my favorite indie hackers @jackfriks @illyism @sobedominik @marckohlbrugge @phuctm97 @ky__zo @yasser_elsaid_ @JohnONolan and more 🔼 meeting the G @rauchg CEO of V 🇰🇷 heading to Korea

Use Hermes Agent however you want. Modify it, extend it, share it, fork it. Use it locally or in the cloud. Use the desktop app or the TUI or text it or talk to it from your smart fridge. Set up your great-aunt with it or run a Fortune 500 on it. Give it your own keys, use it through Nous Portal, or use local models on your own stack. Use one model or fifteen or blend them with MoA. Use it to plan an elopement, debug an EVM event, summarize a lease, troubleshoot that pesky issue with your car, reverse a DataFrame, or autorespond to your boss's emails. Run it on a Mac Studio, a $35 SBC, a hand-me-down ThinkPad, a Docker container, a Hermes Cloud VPS that costs as much as a cup of coffee, or eight of each at once. Create a shared bot that answers questions no one on your team can. Ask it to modify itself. Use it to parse a WhatsApp backup, answer your mother's questions about a power bill, or set a cron to scan the group chat and notify you when someone mentions that deadline you're avoiding. Put it in charge of remembering why you named the branch that. Put it in charge of filing your email into folders or cleaning up all the files named report_final_draft1.pdf. Have it scan the news weekly to settle that stupid bet you made with your brother that one time. Ask it to send your wife an article about cats every morning which she will pretend to be annoyed by even though it really makes her day.

Run inference over millions of records — free of SQL, and without your data ever leaving Snowflake. Here's distributed batch inference at scale ⚙️ Title: Batch Inference at Scale URL: ⚙️ Overview A capability that runs distributed inference workloads on Snowpark Container Services (SPCS) with Ray as the execution framework. Inference runs as a dedicated distributed workload, supporting both traditional models and LLMs, consolidating complex operations into a single API call. ❓ Challenges Solved Many customers, especially those migrating from non-SQL systems, need batch inference decoupled from SQL. ・This is especially true for files and unstructured data at large scale ・Rearchitecting workflows around SQL-first patterns is a heavy burden 💡 Methodology & How It Works ・The input DataFrame is materialized and written to a stage as Parquet files ・A job is provisioned on SPCS; the primary node initializes as the Ray head and replicas join as workers ・Each worker reads staged data, performs inference independently, and writes results to an output stage ・Unified API: a single run_batch() call handles both structured and unstructured data ・Multimodal support (images, audio, video); workers load weights once and reuse across batches; JobSpec controls workers and GPU allocation 🌍 Use Cases ・Nightly summarization of millions of support tickets ・Product catalog enrichment via image-to-text generation ・Information extraction from scanned PDFs, audio transcription and labeling, video classification and description BatchInferenceTask integrates with Snowflake Tasks for DAG automation, and all processing stays inside Snowflake — running large-scale inference while preserving data governance. #Snowflake# #BatchInference#