I've been using AI coding agents since the very early days of Aider and I think this is not quite true.
There's a place for async agents. There's a place for collaborative agents. Collaborative agents may even soon be delegating off to multiple async agents and picking best results. There's so much complexity here and we haven't even begun to explore a corner of the possible design space. We're still trying to plug AIs into human-shaped holes instead of building around their interesting/weird capabilities.
Would you be willing to point me to a primer of how I can get started with building agents?
This week I experimented with building a simple planner/reviewer “agentic” iterative pipeline to automate an analysis workflow.
It was effectively me dipping my toes into this field, and I am so floored to learn more. But I’m unsure of where to start, since everything seems so fast paced.
I’m also unsure of how to experiment, since APIs rack up fees pretty quickly. Maybe local models?
There are a number of free and cheap LLM options to experiment with. Google offers a decent free plan for Gemini (get some extra Google accounts). Groq has a free tier including some good open weight models. There's also free endpoints on OpenRouter that are limited but might be useful for long running background agents. DeepSeek v3.2, Qwen3, Kimi K2, and GLM 4.6 are all good choices for cheap and capable models.
Local models are generally not a shortcut to cheap and effective AI. It's a fun thing to explore though.
