The cost incident that started this Three weeks after we put our chatbot into production, I opened the OpenAI billing dashboard on a Monday morning and stopped breathing for a second. One session — not one user, one session — had burned through roughly four times the daily budget for the entire app. Over a single afternoon. The session wasn't malicious. It was a test account someone forgot to lo
Why this list is different The "best" email API depends entirely on what you're building. A side project optimizing for the free tier needs different things than a Series B SaaS sending two million transactional emails a month. This post grades eight providers against the criteria that actually move the needle in production, and tells you which one to pick for which use case. Most roundups in th
We’ve been running a series of experiments using ChatGPT 5.4 integrated into a website chatbot across different environments: 🌐 a main website 🎯 Goal: simulate realistic user behavior and observe how the model responds over time. ⚙️ Test setup The chatbot is designed to (no self promo here, just context): 📌 answer strictly based on website content (RAG-like approach) Over time, we intentionally
If you want to Automate GitHub PRs, the real goal is not just adding another bot comment to a pull request. The goal is to give reviewers the context they usually have to gather manually: who owns the service, whether it is deployed, whether basic repository standards are in place, and whether the change looks safe to merge. A useful AI pull request workflow can do exactly that. When a PR opens, i
How I added LLM fallback to my OpenAI app in 10 minutes You're running a production app on OpenAI. One Tuesday morning it goes down. Your app returns 500s. You spend an hour refreshing status.openai.com. There's a better setup. Here's how to add provider fallback to any OpenAI-SDK app without rewriting anything. When you call OpenAI directly, you have one point of failure: from openai import Ope
OpenAI revenue is still the number people reach for when they want a leaderboard. But the cleaner frame is different: Anthropic appears to be building a different kind of AI business, one centered on enterprise customers, safety positioning, and less dependence on mass-market fame. That distinction matters because public discussion keeps collapsing three separate things into one scorecard: revenue
LLM Foundry: the boring stack that makes an LLM actually useful Most AI projects are built backwards. People start with the model and only later discover they needed a memory system, semantic retrieval, tool use, tests, and a fallback plan for when one provider decides to nap for no visible reason. That is the part I care about now. LLM Foundry is the workshop around an LLM — not the model itsel
On May 7, 2026 — five days from now — OpenAI removes the Realtime API beta. If you have a voice agent, transcription pipeline, or any WebSocket/WebRTC integration with gpt-4o-realtime-preview, you have a long weekend's worth of work to do, and most of it isn't the part the migration guide warns about. The loud failures are easy. The WebSocket returns 401, the WebRTC connection won't establish, you