OpenSaaS.sh

I deployed Open SaaS to OpenShip (@openshipio)! It was my first time successfully self-hosting an app on a Hetzner VPS. The video below summarises what it took to get it done, and some of my thoughts on the process and platform, e.g.: - Server: Hetzner CPX22 4GB RAM, 80GB disk, with Ubuntu 24.04 -> $23/month - Create an SSH key locally, add it in Hetzner, and set up firewall rules - Add the server in OpenShip - Buy domain, point it at VPS - Write a Docker Compose file and Dockerfiles so OpenShip would deploy all three parts of Open SaaS stack (react, expressjs, postgres) as one unit - Set Env Vars - Add domain TXT records and get SSL certs Things I like: - Auto-deploy from GitHub pushes. - OpenShip handles domains, certs, and SSL provisioning for you. - Built-in jobs and backups: nightly database backups called out as a genuinely cool feature. - Satisfaction of ending up with a fully self-hosted SaaS. Things I didn't like: - The "$5/month VPS" everyone talks about wasn't actually available in any region. Ended up at $23/month. SAD. - OpenShip is still in beta and I hit multiple bugs. - Deploying anything multi-service isn't a first class citizen on OpenShip yet / requires hand-writing Docker config. - Whether to run your own mail server on a VPS is contested. Verdict: - At $23/month, managed hosting providers still look like better value until you have serious traffic, given how little you have to think about. - Would use it for hobby apps and small projects; wouldn't put an important or high-traffic SaaS on it yet until I trust OpenShip more and understand self-hosting better.

Building a SaaS with AI. Without getting stuck. 00:00 Common issues & intro to approach 01:50 Why you should give your agent code & knowledge rails 02:19 Using a SaaS starter (code rails) 04:00 Using AI-optimized docs/llms.txt (knowledge rails) 05:23 Example: How to use agent memory/skill files w/ llms.txt 07:50 Why you should have a conversation with your agent 09:22 The two prompt styles: "clarify first" & "brainstorm w/ pros & cons" 10:18 Example: using the prompt styles in action 12:23 Why you should know what your SaaS is built on 13:22 Example: let your agent teach you about the systems 14:43 Why you should plan/build in vertical slices 15:14 Example: planning a feature implementation using the vertical slice approach 18:01 Why this approach is great for your agent's context management 19:43 Example 1: How to fix issues with your agent 21:39 Example 2: How to let your agent discover and fix issues for you 23:28 Where to go for help

Paid coding courses make their creators rich. Not you. so I built Open Vibe: ✦ free & open-source - not $299 ✦ runs inside your agent - @claudeai, @opencode, etc ✦ the agent tutors as you build ✦ ends with a real SaaS via @opensaas_sh I built Open SaaS, the #1 free SaaS starter on Github (14k★). Open Vibe is the prequel. openvibe.sh

Most tutorials are boring. So I built an interactive web dev course for Claude Code. Claude is your tutor as you build real apps, providing animated diagrams, and explanations. It's 100% free and open-source, too!

Open SaaS just got a big update: - Lazy-loaded pages: smaller bundles, faster loads - OpenAI SDK v6 - Zod v4 - New AGENTS .md / CLAUDE .md files - Updated agent skillz - Improved env var validation - Improved payments code

hey gurl, check out my public dev roadmap 😎

raw look at using Gemini 3 to build a SaaS TL;DR: best model yet🤯 00:00 -- Intro: Testing Gemini 3 with Open SaaS 00:30 -- Easy Task: Landing Page Redesign 02:21 -- Medium Task: AI Task Scheduling & Structured Outputs 06:03 -- Difficult Task: Building an AI Day Planner Collaborative Chat Interface 09:56 -- Conclusion: Gemini 3 Lives Up to the Hype

Hi Everyone! I just built my first SaaS app (applify.ltd) in 1 week using @opensaas_sh. It basically generate ATS compliant resumes and has editor features. It's also my first time launching a product — any advice on how to market it and get my first users? TIA🙏

extracting tool call results for richer agent UI (code is open-source, btw)

who wants this free SaaS source code? its a recipe agent that - brainstorms recipes - knows your preferences and ingredients on hand - has access to your recipes postgres db - generates full recipes w/ images (gpt-image-1) - has stripe and aws s3 hooked up - built w/ @WaspLang & @mastra

Verified template spotlight 🔦 Partnering with: @WaspLang and @opensaas_sh Deploy with one click on Railway: railway.com/deploy/open-saas Read more in their docs: wasp.sh/docs/deployment/depl…

Open SaaS > ShipFast

the fastest way to launch a SaaS is backwards ⏮ deploy first → iterate the Open SaaS template on @Railway let's you: ✦ deploy a fullstack SaaS w/ one click ✦ auto-redeploy on every GitHub push ✦ focus on your app, not DevOps ⏱ timestamps: 00:00 - Introduction to Open SaaS x Railway template 01:00 - Deploying the template 01:34 - Getting the local code ("ejecting") 02:35 - Local Development Setup 06:25 - Making Changes 07:56 - Pushing and redeploying 09:00 - Conclusion & Benefits

i expected gpt-5 to kick sonnet 4's ass 🥊 - prompt: make a fullstack story generator. - workflow: cursor w/ gpt-5 vs claude code w/ sonnet - results: i'm a claude code convert now

holy crap 12k stars have been reached! thanks to the community for making Open SaaS the #1 open source SaaS boilerplate out there =}

paid SaaS templates are for suckers. Open SaaS v2 is free, open‑source & way more badass: ✦ sexy ui - @shadcn ✦ payments integrated - @stripe @lemonsqueezy @polar_sh ✦ admin dashboard - @PlausibleHQ ✦ secure aws s3 file uploads - @awscloud ✦ full cursor rules & llms.txt - @cursor_ai check out the @ProductHunt launch👇

Kiro lives up to the hype. I might replace @cursor_ai with @kirodotdev as my IDE if they can fix a few things. ✓ Specialized planning tools: plan, design, spec, todo. ✓ Really great at executing and overseeing tasks. ✓ Groks your codebase well & implements quickly! 🆇 Need to reign in the planning phase. It wants to be (overly) thorough. 🆇 Queued tasks always failed. 🆇 Separates diffs and code files / tends to feel more cluttered than cursor. ### Timestamps 00:00:00 - Introduction: First look at Kiro, an Amazon Cursor competitor. 00:00:24 - First Impressions: Exploring the Kiro UI (Specs, Agent, Hooks, Steering). 00:01:17 - First Prompt: Asking Kiro to analyze the project and suggest a feature. 00:02:34 - Kiro's Suggestion: AI-powered file analysis and processing. 00:03:31 - Narrowing Scope: Deciding to implement content extraction from images. 00:04:26 - Starting a Spec Session: Kiro initiates a dedicated planning and specification process. 00:05:06 - Generating Requirements: Kiro creates a requirements document with user stories. 00:06:44 - Design Phase: Moving from requirements to technical design. 00:07:17 - Generating a Design Doc: Kiro outlines the architecture, schema changes, and API operations. 00:08:04 - Wasp Background Jobs: Discussing how Kiro's plan might integrate with Wasp's job queue feature. 00:10:33 - Simplifying the Plan: Telling Kiro to create a simpler, iterative implementation plan. 00:12:50 - Implementation Phase: Kiro breaks the work down into a detailed task list. 00:14:53 - Task 1: Update Database Schema: Kiro modifies `schema.prisma` and prepares for migration. 00:15:33 - Running CLI Commands: Manually running the database migration command. 00:18:03 - Task 2: Create Content Extraction Utility: Kiro starts creating the utility function to call the OpenAI Vision API. 00:18:19 - Kiro vs. Cursor: Initial thoughts on how Kiro's workflow compares to Cursor. 00:19:59 - Handling Errors: Kiro runs into compilation errors and attempts to fix them. 00:22:36 - Task 3: Create Server Operation: Kiro works on the backend operation for content extraction. 00:26:05 - AWS Issues: Skipping ahead after resolving AWS permissions issues manually. 00:26:27 - Live Demo: Demonstrating the completed feature by uploading an image and extracting text. 00:27:41 - Final Review: Overall impressions of Kiro, its strengths (spec/planning), weaknesses (bugs), and potential.