Start with the friction, not with the tool.
The shiniest stack means nothing if it solves the wrong problem. I watch how people actually work, write down where they curse, then pick the simplest thing that makes the cursing stop.
I'm Arnaud - Product Operations, builder-side. Currently right hand to the founder at HelloBible, scaling from 15k to 140k downloads in 14 months. I find the friction. I ship the system that removes it.
Open to your next ops hire - coffee on me if you're in Paris
Five case studies - each a real friction I found, a real system I shipped, a real outcome I can show you.
The strongest demo of my method is the site you're on. I'm not a dev. I orchestrated Claude through every line of code, every visual decision, every trade-off. Here's how, and why it matters.
I built a pipeline that ships Bible reading plans on YouVersion in 1 second instead of 50 minutes - and turned those plans into a top-of-funnel acquisition channel that feeds HelloBible. 220 plans shipped, an undocumented API reverse-engineered, an entire publishing-to-acquisition loop automated.
4 scattered feedback channels (Zendesk, WhatsApp, Play Store, App Store) - 2,020 customer verbatims classified across 27 business-specific themes - for $1 in API calls. Built with Python and Claude Haiku. Runs monthly from a single command, with checkpoints so an interruption doesn't cost a re-run.
Daily-driver tools I built end-to-end to solve my own friction: a second-brain memory bot, and a tech-watch satellite bot that surfaces what matters without doom-scrolling.
I built a Zendesk + RevenueCat integration that flags premium subscribers in real-time - what the official connectors couldn't do. Result: 3,200+ tickets resolved, 80% macro coverage.
The shiniest stack means nothing if it solves the wrong problem. I watch how people actually work, write down where they curse, then pick the simplest thing that makes the cursing stop.
Clarity is a deliverable. Every system I ship comes with a short Loom, a one-pager, or a back-of-envelope diagram - because a tool nobody understands won't be maintained, and won't be trusted.
I'll pick n8n over custom code when it gets the job done. Google Sheets over a "real" database when the team is three people. Compounding reliability beats showing off - every time.
I'm Arnaud Duflot. I do Product Ops at HelloBible - a consumer app I helped scale from 15k to 140k downloads in 14 months.
My actual job: I find operational friction, design the AI workflows that remove it, ship. A 50-minute manual task becomes 1 second because I built the right pipeline.
This site exists for one reason: generate 1 to 2 conversations a month with founders or CPOs who have the same problems I have at HelloBible, at different scales. Early-stage startup, scale-up structuring its ops, AI team inside a larger company - the size doesn't matter. What matters is that there's a real ops problem to solve.
What makes me different: I'm not a dev. I'm a Product Ops who orchestrates AI agents to ship technical solutions beyond my individual skill ceiling. This site itself - WebGL, adaptive animations, custom design system - I didn't write the code. I piloted Claude through it. The four other case studies are the same story at different scales.
If your team believes AI will transform its ops but no one can actually ship it, let's talk.
Product Ops, AI Design Workflow, AI Automation Engineer, Chief of Staff, and adjacent operations roles - at startups and scale-ups where one person can still see the whole picture and ship across the stack. Paris-based, remote-friendly.