Triple-Threat Orchestration System I got tired of AI tools that just do things. Build something, deploy something, write something — and then I find out three steps later that it made a bad assumption in step one that affects everything downstream. Triple-Threat is how I push back on that. It's a structured, gated workflow where three different AI systems each have a specific job, nothing moves forward without passing a gate, and I approve every gate before anything gets built. The coordinator is Hermes — an AI agent with a built-in learning loop that maintains state, enforces the stage sequence, and keeps everyone on task. I don't use it as a general assistant. It runs the workflow. Claude Code does the design and architecture work. Codex handles implementation review and builds the actual runbook. Antigravity (I call it agy) does an independent review of everything Claude Code decided — I make them disagree with each other on purpose, then I decide who's right. Any restart, configuration change, DNS update, secret rotation, or infrastructure action still requires my approval.

My apologies for being silent for the past few weeks. I was deep in the interview process for my dream job! Very excited to announce I'm now the very first and Founding Forward Deployed Engineer for n8n! I will be leading the charge for enterprise adoption of n8n!

Hey everyone, Before I flood this with content, I want to make sure it’s helpful to all of you! Quick poll: what do you want more of? Vote below and drop a comment if something’s missing from the list. The results drive what I build next.

Drop your answer in the comments. Tell me one thing you're trying to automate right now. It could be: - Something repetitive that's eating your time - A process you've started building but got stuck on - An idea you don't know how to approach yet Every Sunday I'll pick one submission and do a full deep dive: architecture, tool selection, flow design, and the decisions that actually matter. I'll post it here so everyone benefits. Drop yours below. — Mike

New build, short and practical: an AI product photo studio for a candle brand, about 6 cents a photo. The stack: - Mobile-first front end: pick a photo, choose layout + aspect ratio, type a one-line prompt. - n8n workflow: webhook fires, an agent expands the one-liner into a full prompt tuned for the image model. - Image model: Google Nano Banana 2, run through KIE.AI (a marketplace that resells model usage well below retail). - Poll until the job finishes, download the image, push it to a self-hosted open-source image server, serve it back to the app. - Approve to publish: the photo lands in a wholesale partner portal so retail stores can pull assets themselves. Cost breakdown: about 6 cents per image to generate, under a penny for the prompt expansion (GPT-4o mini). The second unlock here is the retail partner self service, no more sending photos to partners manually. Build for the whole workflow, not just the cool part. Want the template? Say so and I will post it. Built something similar? Show me.