Why your AI coding agent forgets team decisions (and what to store instead) Teams running Cursor and Claude Code side by side hit the same wall. CLAUDE.md works for one seat. It does not carry decisions across seats. One agent learns why you dropped Redis. Another suggests Redis tomorrow.
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Sync Stripe, QuickBooks, Xero or Paddle into Supabase Postgres in about 5 minutes. Auto-created tables, scheduled syncs, and the RLS step most guides skip. By Ilshaad Kheerdali · 5 October 2026 Supabase is where a lot of small SaaS teams keep their application database, so it is the obvious place to put billing data too. One database, one SQL console, and your Stripe invoices sitting next to your own users table so you can join them. Getting the data there is the part people underestimate.
Most "no cookies" LinkedIn scrapers on the market return data that a logged-out visitor never sees: exact connection counts, every past job, people search with "15,666 results". That data has to come from somewhere — usually logged-in accounts on the seller's side. Sometimes that's fine for you. Sometimes it's a compliance problem you only discover later. I wanted a clear answer to a narrower question: how far can you get using only what LinkedIn shows to a logged-out visitor?
💀 I Hunted Down the Silent Killers in ATLOCK v5 (And Why Your Python App is Probably Failing in Silence) 🔥 "The devil isn't in the missing comma. The devil is in the background thread that silently fails to lock the vault when Windows goes to sleep." We are at 984 downloads across all Akhouri Systems products. Just 16 more until we hit the 1,000 milestone. ATLOCK v5 is 100% built, battle-tested, and ready to ship. But before we drop the hammer and release it to the wild, I need to talk about the monsters I had to slay in the codebase.
Once you have decided to charge, the next decision arrives quickly: what billing periods do you offer, and which one do you put front and centre on the paywall? The 2026 data leans strongly in one direction. Annual subscribers retain dramatically better than monthly ones through their first year, with median first-year retention for yearly plans landing roughly in the 20 to 40% range against roughly 6 to 14% for monthly. Annual plans also tend to generate meaningfully more revenue per user, with one large analysis of tens of millions of subscribers putting the gap around 50 to 60%. And the sub
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