Most async APIs commit to one thing: starting your job. They return 202 Accepted, hand you a job ID, and that's where the contract ends. The rest is your problem. I do something different. I make one promise: When your job is done, I'll tell you accurately. Until then, I'll keep retrying. That's the entire contract for everything I've ever shipped. It sounds small. In practice, it's the only thing
We have reached a small but important milestone for DondeGo API. The first working use case is already live: we are using our API to power daily event selections for two local projects: https://x.com/HoyBcn https://x.com/EnMadridHoy The idea is simple: every day, the system uses DondeGo data to select some of the best events happening today in Barcelona and Madrid. Instead of manually searching ac
Originally published at ffmpeg-micro.com You need a thumbnail from a video file. Maybe you're building a video gallery, generating preview images for a CMS, or creating social media cards from uploaded content. The usual advice is to install FFmpeg on your server and write extraction scripts. That works until you need it in production. FFmpeg can extract a single frame from any video using two fla
Picking a screenshot API feels binary until you start integrating, then the edges show: one service has a Python SDK but no async queue, another has webhooks but charges extra for authenticated pages, a third makes you wire up an S3 bucket yourself. This post walks through how Rendershot and Urlbox compare across the dimensions that actually hurt to change later. Upfront: I build Rendershot, so tr
The first article on this blog explained how it was built in 30 minutes with Claude Code. Naturally, a blog needs comments. Same constraints: no database, no external dependencies, no Disqus tracking visitors. Just PHP + JSON files. Built in one session with Claude Code — the interesting part wasn't the code, it was the security audit that followed. A comment system without a database seems trivia
When building applications with large language models (LLMs), one of the most overlooked costs is how structured data is represented. Most systems use JSON. And JSON is inefficient for LLM input. KODA (Knowledge-Oriented Data Abstraction) is a schema-first data format designed to reduce token usage when sending structured data to LLMs. It works by: Defining structure once (schema-first) Encoding v
I kept seeing the same GPT Image 2 questions in different places: Is it actually available yet? Is API access live? Does ChatGPT access mean API access too? What will it cost? Can I test image-to-image workflows somewhere? Annoying, but fair questions. Model rollouts are messy. One page says a feature is announced. Another post says it is rolling out. Someone on Reddit says they can see it. Someon
Telegram has become the de facto communication platform for crypto projects, brand communities, and market intelligence teams. With over 950 million monthly active users and channels routinely exceeding 100K subscribers, Telegram is where breaking information surfaces first — often hours before it hits Twitter or Discord. If you're building any kind of monitoring pipeline in 2026, Telegram channel