Factur-X 2026 : guide d'implémentation pour les PME du BTP Depuis 2020, la facture électronique Factur-X est obligatoire pour les entreprises françaises de plus de 250 salariés. En 2026, l'obligation s'étend à toutes les PME et ETI, qu'elles soient client ou fournisseur. Pour les petites entreprises du BTP, cette transition n'est pas optionnelle — c'est un défi technique et administratif immédia
Despite scrolling at approximately 5 frames per second in a crowded inbox, billions of people use Gmail every single day without mass-migrating to a “faster” email client. This should indicate something uncomfortable about how we spend our time as engineers. We treat performance like a moral virtue. A slow app is a bad app, built by lazy developers. A fast app is a good app, built by craftspeople.
A walkthrough of prompt injection attacks against OopsSec Store's AI assistant, bypassing its input filters to extract a flag from the system prompt. OopsSec Store has an AI support assistant with a secret embedded in its system prompt. The only thing standing between us and the flag is a regex blocklist. Spoiler: four regexes are not enough. Initialize the OopsSec Store application: npx create-os
TL;DR — One API call subscribes a customer endpoint. Centrali signs each delivery with HMAC-SHA256, retries 5 times over ~40 minutes on failure, logs every attempt, and exposes a one-line replay endpoint. No queue. No retry logic. No Svix. The whole subscribe call is right below — scroll to it if you just want the shape. Your customers want webhooks. You know the checklist: A queue so user request
In Chapter 1 I claimed our entire Auth Gateway is built on top of one NGINX directive: auth_request. This chapter is a deep dive into how that directive actually works, and the four or five sharp edges that bit us before we got the config right. If you already know auth_request cold, skim to "Sharp edge 1" near the bottom — that's where the real war stories are. auth_request actually does Drop t
Most text analysis solutions fall into one of two problems: Too expensive — OpenAI API costs money for every call Too complex — Hosting your own Hugging Face model requires infra, GPU, maintenance I built TextAI Pro — a lightweight REST API that does the job without the overhead. Two endpoints: POST /analyze Sentiment: positive / negative / neutral Confidence score (0–1) Top keywords Word count PO
You ask Claude to "add caching to the user profile endpoint," and 30 seconds later you ship something that looks fine in review: SET user_42 <json> — flat key, no namespace, collides the moment a second service shares the cluster. No TTL — the entry lives forever until maxmemory evicts your hottest keys. KEYS user_* in a cleanup job — single-threaded Redis stalls every other client for hundreds of
Let's start with a controversial opinion: API documentation, as we know it, has failed. Think about it. Docs are: Static: They can't adapt to your specific question or use case. It's time for a new paradigm: Interactive API Intelligence. Instead of pulling information from a dead document, what if we could query the knowledge in a conversational way? This isn't just a theory. I've spent the last f