Chapter 1: Can you code with AI agents without being technical?
Can you code with AI agents without being technical at all? Today, we're gonna go through if you actually could do that. This is an episode based on an article I read by Ben Tossall.
Chapter 2: What is Ben Tossel's workflow for building with AI agents?
He is just a master of communicating how non-technical people can use AI. And he wrote this incredible guide. It got 3.8 million views on X, and we're gonna go through it together to basically take all those insights. He talks about what he's actually shipped
Chapter 3: How does Ben set up his AI coding agents?
as a non-technical person how he actually works what his setup is how he codes on the go and more all the insights that he has we're going to go through it together i started reading this frankly and i was like this is so so much sauce that i need to go through it with everyone here together because i think that the people that stay to the end of this episode are going to have an unfair advantage because he just he explains it so simply so let's let's get right into it
He starts by saying, I've spent three billion tokens in four months. Every single one of them through a terminal watching an agent write code I couldn't write myself.
Chapter 4: What skills should non-technical builders focus on?
He actually started a no-code company that was acquired by Zapier. So this is his guide to learning how to program. So he shipped a bunch of things. He shipped a personal site. He says, I revamped my personal site and made it look like a terminal CLI tool. He built a feed.
Chapter 5: How can you learn from AI agents as your teacher?
So he built a simple social tracker for mentions of Factory. That's the company he works at. Factory on Twitter, GitHub issues, posts from the subreddit. It's open source. He built Factory Wrap, which was a first version of his wrapped product.
Chapter 6: What is the mindset shift needed for working with AI agents?
Showed it to the team and they loved it and they wanted to bake into the actual product themselves. So even if you don't want to actually build a and you want to just get promoted at your job, learning how to actually use AI agents is helpful.
Chapter 7: Why is 'vibe coding' considered a new technical class?
Custom CLIs, I've created a few CLIs, like Python CLI, which then has been picked up by the team with customer support queries. He created a crypto tracker that predicts positive, negative, or neutral signals and dynamic data.
He created Droid Miss, 12 Days, 12 Experiments, or games that touch the different themes people are talking about on Twitter, memory, context management, vibe coding, and things of that nature.
Chapter 8: How can you embrace failure and keep building with AI?
He created an AI-directed video demo system. He gives it a prompt to create a video. It opens up Ghosty, runs the command, and can open up other windows like a browser, recording the screen, basically acts as its own director, producer, and editor. He even created a Telegram bot powered by Droid Exec.
So he can have local repos synced on a VPS and about 50 other things I'm not mentioning here are left to die. So if you're interested in building things like this, this episode is for you. So let's see how he actually works. So he says he uses CLI exclusively, terminal over web interfaces always. It's just more capable as a general agent and I get to see it work.
A lot of people listening to this are non-technical and they're probably using web versions of Clode, they're using web versions of Lovable and products like that. This is your reminder, kick.
you know pat to actually go and use cli because if he can do it you can do it too this is what he does he says if i have an idea for something or there's an issue with something that i feel like could be solved with code basically everything these days i'll spin up a new project in droid which is factory cli so i have no affiliation with factory at all um but i i
And I've actually never used the product, but he's talking about this. So turn scripts into agent armies, DevEx budget multiplier, fail-safe permission. So probably worth playing with. When I was reading this, I was like, okay, I need to make a note to actually play with this. So you might want to do that too.
I generally just talk to the model a couple times to start feeding in context about what I'm trying to do and then I'll switch into spec mode and start getting a plan on what I want to build. In spec mode I'll basically question a bunch of things. Like I don't understand what this is or why would we need that over this? Can't we do it this way?
I thought this was an interesting insight which is approaching it as almost like a philosopher asking questions. So I made a mental note to do that. Thank you so much. So I kind of build ahead of myself first. I try and just build the thing. And then all the gaps and all the issues that I run into are the opportunities for me to learn.
Is that a thing that is part of the system that I've seen across other repos that I should build up a sort of templated system handle? Should this go into an agents.md that actually follows me around and does the same thing on all other repos I'm going to be working on? So Agent MD, Agents MD, is a simple open format for guiding coding agents. So it's used by over 60,000 open source projects.
You can think of agents.md as a readme for agents, a dedicated predictable place to provide the context and instructions to help AI coding agents work on your projects. So you can see there's a little why, like why it should exist. But basically it's giving it a clear, predictable place for instruction. It keeps a concise focus on human contributors. And there's some examples on the website here.
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