Practical guides on AI agent deployment, model selection, and lead-generation automation for indie hackers and solo founders.
Most explanations of no-code AI agents are written for marketers. This one is written by an architect. Here is how they actually work, and why the abstraction layer is the hardest part to get right.
I started with one question: which model do I use? Then I hit two more I didn't expect. Which model survives an agentic loop, and how do I actually deploy this? Here is what I learned answering each one in production, and how it shaped the platform I ended up building.
Building an AI-powered recommendation engine meant making a critical decision: which LLM to use. Here's why Claude Sonnet 4.5 was the Goldilocks choice: not too simple, not too expensive, but just right.
Pick a template, connect Telegram, and your AI agent is live in 60 seconds. No Docker, no servers.