So 4 days ago I was asking for feedback on my app: https://realitymade.lovable.app which is an AI prompt builder. Here are the updates from just a 'chose your option' basic feel. Reality Made Update: What's New A lot has been added since I first shared the app. Here's what's live now: Added based on your feedback: - Tooltip descriptions next to dropdown options so you know exactly what you're picking: Silk Press, Coffin nails, Dutch Angle, and more are all explained inline - Shareable persona codes: load a persona someone else built using a short RM- code, no account required to try it (here's one to test: RM-G4P2UF) - Prompt history with a Remix button so you can rework any past prompt without starting over New features: - Sign up and log in, your personas and history now save across sessions - Save up to 1 persona on free, more on paid tiers - Pricing page is live at realitymade.lovable.app/pricing there are three tiers, free to start What's coming next: - Payment integration for Creator ($9/month) and Pro ($19/month) tiers - Custom domain - Video prompt generation (Pro early access) - Seasonal prompt packs Free to use. Go build something. Drop your RM- code below if you want to share a persona with the group.

This architecture diagram illustrates a state-of-the-art approach to automating technical incident response and resolution. It transforms traditional monitoring into an active, intelligent loop where alerts are not just notified, but analyzed, diagnosed, and resolved with minimal human intervention. Think of it as a super-powered "Self-Healing" system for your applications. Instead of a messy, manual triage process when an alert fires, this stack creates an autonomous workflow that can diagnose the root cause and even suggest code fixes. ⭐ Let's break down the journey from "Alert" to "Resolved": Phase 1: Alert Ingestion & Orchestration (The Brain & Nervous System) The process begins with an incident signal. ➡️ The Alert Sources: Monitoring tools like PagerDuty (for on-call orchestration and modern incident management) and Datadog (for comprehensive infrastructure and application metrics) detect an issue—perhaps an API latency spike or a high error rate. They fire an alert. ➡️ The Orchestrator: This is where n8n (an open-source workflow automation tool) steps in. An n8n workflow, acting as the "Webhook Trigger," is set up to receive this alert. This is the nervous system, immediately routing the incident data to the next step. Phase 2: Intelligent Analysis & Diagnosis (The Expert Consultant) Now that the system is aware of the problem, it's time to figure out why. ➡️ The Agent Runtime: The alert details are sent (via a POST request) to Manufact, a managed infrastructure platform designed specifically to provide a scalable and reliable runtime endpoint for AI agents. Manufact auto-scales to handle the compute demands of the AI. ➡️ The Brains (The AI Agent): Running on Manufact is a LangChain agent, a sophisticated AI application built with the LangChain framework. This agent isn't just a static script; it's a dynamic entity that can use tools and plan multi-step actions. The diagram shows it is programmed to: ➡️ The Tools of the Trade: To do its job, the LangChain agent needs specialized knowledge and access: