Go 0 to 100 with Agents Today

AGENTS & OPEN-SOURCE

Welcome back! Today, I want you to ‘feel the AI.’ For once, it’s not about reading about it but actively using it in ways you did not know were possible.

I’ve been championing open-source and covering agents for a long time, so it’s about time I provided you with the means to see it for yourself.

By the end of this piece, with a few simple steps, you will have built the following systems:

“Chat with your Local LLM”: The basics of running open-source, including having your first LLM installed on your computer and talking to it, using tools like Ollama and Codename Goose.

“Chat and Act on your Local System”: Using Goose and ChatGPT, you will do things like rearranging your local folders or an AI that can traverse through your files and see what's in them, like checking whether it’s an invoice and extracting the invoice value, to find what you need in seconds. Your personal smart searcher.

“Agentic Gmail”: Using Goose and Zapier, you will have your first ever MCP interaction, where you instruct an LLM to draft an email for you and store it in your Gmail account.

“Play your Creation.” Finally, we will create a quick snake game you can run on your computer.

And did I mention that all this will be done with exactly zero lines of code or any technological expertise required?

We will also cover the broad theory behind why all these works, giving you my best shot at visualizing what the future of software will be.

And even if you’re a business executive or investor who isn't particularly interested in running local models, by the end of this post, I will have opened your mind to what’s possible with AI with minimal effort on your part.

In the AI era, success won’t be a matter of intelligence but of high agency—the willingness to just do things.

Let’s dive in.

The Future of Work

If you’re subscribed to this newsletter, I assume you are at least mildly convinced of the importance AI will have in our future. But by the end of this post, you will be fully convinced.

But first, let’s establish the foundations of the future of work from a clear and understandable perspective: from tokens to agents.

Tokens.

To understand what we’re dealing with, to understand the ‘AI economy,’ we need to understand the most basic component: tokens.

Most AI models you interact with today are neural networks with a very particular structure: most of them, if not all (at least all Generative AI models), are sequence-to-sequence models.

But what is an ‘AI model’?

An ‘AI model,’ or more specifically, a ‘generative AI model,’ is just a map between inputs and outputs that takes in a sequence of words, a sequence of pixels (images/video), or spectrogram frames (audio), and returns you another sequence of words, pixels, or spectrogram frames.

Not all AI models are generative, but most AI models you read about these days are,…

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