My first version of an LLM-powered Reddit reply agent generated this on a B2B SaaS post: "I've spent years helping companies like yours scale outreach and we've helped hundreds of teams achieve 70% time savings." Every word of that is fabricated. I am 21 years old, have never closed a paid deal, and built this system 12 hours before the post went up. The next 24 hours were spent making it not lie.
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
The Problem: We Were Flying Blind At Refer, we're on a mission to enable talented individuals to fulfill their professional potential by helping them pursue their ideal job. Behind the scenes, that means a lot of microservices, and recently we decided to consolidate everything into a mono-repository. If you've ever migrated dozens of microservices into a monorepo, you know the drill: contracts b
The Problem If you are building AI applications with LLMs, you know the pain: raw HTML is useless for training data. You need clean, structured Markdown. Most solutions like Firecrawl or Crawl4AI require setup, dependencies, and often paid plans. You could write your own parser: import re import urllib.request def html_to_markdown(url): html = urllib.request.urlopen(url).read().decode()
Hi, we are back again. Previously, I created a simple Google Cloud VPC and then improved the configuration by introducing variables. This time, I want to continue with another Terraform concept: outputs. But, we will not be using the previous code, because adding outputs for one vpc is too simple. So, I made the lab slightly more practical. In this lab, I will create: a custom VPC network a subnet
In Part 1 of this series, I enumerated a few obstacles for engineers taking vibe coding from side projects to production. Part 2 looked at AI usage from the manager's perspective: measuring adoption, understanding the gap, coaching to fill the gap. Both of those were "Day 1" problems: getting started, getting people on board, figuring out the tools. This article focuses on what comes next: the vib
This technical post walks through the design and implementation of Secure Playground: a local web app that simulates prompt-injection attacks against large language models and demonstrates simple defenses. Provide a minimal, reproducible environment to test payloads and defensive strategies. Make it easy to add new providers and run mutation-based red-team experiments. Offer a leaderboard and scor
If you've worked with Entity Framework Core in real-world architectures, you've probably written commands like this: dotnet ef migrations add InitialCreate \ --project src/MyApp.Infrastructure \ --startup-project src/MyApp.Api \ --context AppDbContext And maybe this worked fine... Until your architecture started growing. Suddenly you have: multiple APIs worker services separate infrastructu