What happens when your AI gives the wrong answer? A production system can't simply say, “The model hallucinated.” You need systems around the model that can detect uncertainty, retrieve better information, escalate edge cases, and bring a human into the loop when necessary.

RAG isn't just “put documents in a vector database.” The difficult part starts after the documents are indexed. How do you chunk them? How do you retrieve the right context? How do you handle irrelevant results? How do you evaluate retrieval quality?

AI is not just a tool you call. It is a system you need to understand, build, test, and make work reliably. That is the gap between simply using AI and becoming an AI engineer.

I completely automated our QA testing process using Replay Here's how I did it: Replay QA finds what broke in my web app and share them on my GitHub issues. Check it out on Product Hunt: www.producthunt.com/products/re...

To land an engineering role at Kuda. To this: - Go to the Kuda website and apply - Study Kuda engineering culture deeply - Understand all stages of their interview process - DM and connect with Kuda engineers and ask them how work happens there

Caching Invalidation is one of the most difficult things in software engineering

I wrote an article about context engineering because it was paid for. But the lessons I learned from the research phase were crazy. For example: There’s something called “Lost-in-the-middle” problem. Which means LLM doesn’t process information evenly across context windows.

You’re in an AI Engineer interview. They ask: “What do you understand by context engineering, and how would you design a system that doesn’t hallucinate in production?” Here’s how to approach it:

I’m trying to package my bootcamp videos into a complete course. The process is crazy plus I have a very high taste in courses and how it should be structured. It’s becoming impossible. I guess, I will just launch it and let the internet decide.

Has anyone noticed the way Gemini misses context every time? Because right now I'm thinking it's only me I have reminded it that I need this image in 3D format a hundred times. It's time they switch to Context.dev

Context.dev: Web Scraping API for AI Agents & LLMs

Scrape any URL to markdown, crawl entire websites, and extract structured data. One REST web scraping API built for AI agents and LLM pipelines.

context.dev

I just solved context problems for my Claude Cowork employees. The content pipeline automation I created early on uses a library that makes everything powerful.

Context is the new moat. The more context is given to your LLM, the more personalised and contextual output it gives your team and customers. Context.dev is building for teams.

Context.dev: Web Scraping API for AI Agents & LLMs

Scrape any URL to markdown, crawl entire websites, and extract structured data. One REST web scraping API built for AI agents and LLM pipelines.

context.dev

If you want to stop being a junior developer. Do this: Get 10 real strangers, not your friends, to use something you built this month. Follow these steps: 1. Pick one small problem you actually have and build the smallest tool that fixes it.

If you want to stop being a Junior Developer. Do this: Ship one product completely alone in 30 days, from an empty repo to a real user who is not you. Follow these steps: 1. Pick one small problem you personally feel every single week.

If you've never maintained a product past the launch, you are still a junior. Do this instead: Own and maintain one real product for 90 days, from launch day to day ninety, without walking away.

You’re going to stay stuck if you don’t make the conscious effort to finish what you’ve started. Finish that project and launch it If you’ve not started, pick a project here: projects.masteringbackend.com

Interviewing skills is what gets you hired, not your technical skills. I said this before. Your Interviewing skills get you inside the house while your technical and soft skills keeps you. So which one do you need now? Practice technical interviews here: interviews.masteringbackend.com

After 2 nights of harness and millions of tokens burned. I finally automated our content pipeline with Claude Cowork. Here's the pipeline in case you want to replicate - Read data from our Google Search Console - Do deep research with our Ahrefs account for content gaps, competitors, etc

AI Engineering is the base foundational skill you need to do anything relating to AI and Engineering. It’s no only about build AI systems. With AI engineering, you can become a lot more. - AI Automation (not no-code) - AI researcher - AI Backend Engineer - etc You should acquire this.

What companies expect from AI Engineers before hiring in 2026

Building projects allows you to think above your comfort zone. When you start building, there’s a point it feels like you should stop and go do something else. Or it’s too hard. But if you have resilience and move pass that level. Then you’ve conquered your building fatigue.

Good morning engineers. What are you working on this morning. Share it to encourage others.

If you want to stop being a Junior Developer. Do this: Ship one product completely alone in 30 days, from an empty repo to a real person using it. Follow these steps: 1. Pick one problem you personally have and can explain in a single sentence.

If you want to stop being a Junior Developer. Do this: Get 10 real strangers, not your friends, to use something you built this week. Follow these steps: - Pick one thing you already built that solves a real problem.

While building with Claude Code. What if you could start your tasks with a single file instead of a series of chats in the chat windows with no context? JetBrains is building first-class support for agentic markdown in JetBrains IDEs Here's how it will work:

To stop being a junior developer and start building with confidence. Do this: - Decide on the area of business you want to focus on (FinTech domain) - Pick a project in the domain - Focus on and build it to completion - Acquire 2-5 users: 2 friends and 3 strangers - Fix all their feedback

You're in a backend interview. They ask: "Design a distributed workflow orchestration system that reliably runs 1M concurrent long-running workflows." Here's how to approach it:

To land an engineering role at Kuda. To this: - Go to the Kuda website and apply - Study Kuda engineering culture deeply - Understand all stages of their interview process - DM and connect with Kuda engineers and ask them how work happens there

You don't need another Python course. You need proof you can build. Most self-taught backend engineers fail to get hired not because they lack knowledge, but because they have nothing to show for it. Here's how to build a portfolio that gets interviews:

You can write Python. Loops, functions, classes, all of it. But ask you to build an API that handles 10k users, survives a restart, and doesn't leak data? Silence. That gap has a name. It's the difference between learning Python and engineering backend systems. 🧵