@NikChr1414 · X

@im_pradee_p · X

Backend as a service

ent101 · HN

The Safe, Production-Ready Backend for AI-Generated Apps

@MuratOnX · X

roguetink · Product Hunt

MonoCloud for Startups One identity layer for your customers, APIs, and agents

maor_dayan_ · Product Hunt

Veridome Surface The security layer for apps you built with AI

@BinaryScriptar · X

Introducing OtterKit. Always-on webhook endpoints and instant tunnels, built for developers and their AI agents. It started with a problem I kept hitting: every time my coding agent needed to test a Stripe or GitHub webhook, it had to open a tunnel. What OtterKit does • Permanent webhook URLs that answer senders 24/7 with the status, body and headers you choose, verify signatures on arrival (Stripe, GitHub, Shopify, Slack and 12 more), store full history, and forward matching events to your app, signed and retried • Instant HTTPS tunnels to any local port in one command, stable subdomains, auto stop, basic auth • Replay any captured request, edit the payload, re sign it, fire it at your local handler • Pulses: scheduled HTTP calls and dead man's switches with email alerts • Payload drift detection: baseline the JSON shape per event type, get emailed when a provider changes it • Custom domains ( and an email inbox on the same endpoint • A

@SimpleWebAPIs · X

@WurkHaus · X

What happens when you got told no to a 3k quote for a data tool and spend a year building one instead.

@Parths049 · X

@StuSim · X

hey Adam, I run , lightweight agent memory

u/bob__io · Reddit

What we learned from trying to turn vibe-coded prototypes into production SaaS applications Founder here. While developing MCPBackend, we noticed a major difference between generating a convincing application demo and building a maintainable SaaS product. AI coding tools are increasingly capable of generating interfaces, routes and even initial application logic. But a production application still needs: a reliable data model authentication and authorization backend validation