31–40 of 81 posts
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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 A…
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,…
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.
Was able to build a personal MCP server that connects to the Jules API, letting me dispatch tasks to Jules, from Copilot Chat in VS Code. Video here: https://www.youtube.com/watch?v=RIjz9w77h1Q
From my experience Jules is the worst coding agent on the market.
Do people trust these kinds of things to effectively work async and unsupervised? My experience with coding agents leads me to believe using something like this will end up being more noise and work than ROI I suppose it could be effectively the same loop I use in VS Code, but then why would I want an external tool over an integration?
Do people trust these kinds of things to effectively work async and unsupervised? My experience with coding agents leads me to believe using something like this will end up being more noise and work than ROI I suppose it could be effectively the same loop I use in VS Code, but then why would I want an external tool over an integration?
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I hope they don't store any user data in their app. Trusting LLMs blindly is a bad idea.
Jules has access to the codebase, not the database. It doesn't see any user data.
It’s a shame Google picked the wrong system design for Jules. Claude Code’s system design is clearly superior at this point. Jules is going to simply be another vendor locked walled garden play.
The default installation for claude code is hilariously insecure and the only times I've used it is in a fully sandboxed VM.
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I hope they don't store any user data in their app. Trusting LLMs blindly is a bad idea.
Jules has access to the codebase, not the database. It doesn't see any user data.
It's pretty easy to introduce something like IDOR when asking LLMs to write the code.
Do people trust these kinds of things to effectively work async and unsupervised? My experience with coding agents leads me to believe using something like this will end up being more noise and work than ROI I suppose it could be effectively the same loop I use in VS Code, but then why would I want an external tool over an integration?
My experience with coding agents leads me to believe using something like this will end up being more noise and work than ROI I think that depends on how far out your horizon is. If you're only looking one task out, or maybe a few weeks out, then it's not worth investing the time yet. On the other hand, if you're looking at how your engineering team will work in 3 years time it's definitely worth starting to look at…
In 3 years time this won't be how these tools work. So it feels like you're saying we should invest time in something that doesn't work and will be redundant in 6 months.
Worse, your example is one that AI agents are notoriously bad at. Give them an error like that and they're more liable to break the existing functionality to fix it, after littering the code with tons of log statements.
When most of the time the actual fix is a silly little mistake that takes one line to fix.
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There is a human being (GP) reviewing the proposed code before merging. I wouldn't describe that as trusting the LLM blindly.
No, there is not
"Only if they're happy with the changes, I step in to review the code and press merge."