Create Your First AI Personal Assistant Today

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Create Your First AI Personal Assistant Today

I hope you have a couple of hours to play because today is an important day.

Using a tool that requires no coding, you will build your very first AI-powered email assistant. It will read your emails, categorize them, and, using combinations of different models and tools, create ready-to-read Notion articles for daily reads on the latest news in the AI industry.

In addition to offering new daily content for you, you will:

Understand why the time is now, not tomorrow, to start with agents, understanding key terms such as “context engineering”, key agentic capabilities, and complex context management systems.

Learn several best practices being applied by incumbents, from Anthropic to Moonshot, for agentic applications

Understand exactly how I built one from scratch, including the configuration of all individual pieces, prompts, and strategies.

And did I mention no coding required?

Let’s dive in.

Setting the Stage. Why Now?

We’ve been talking about agents for months, so why only now am I putting my money where my mouth is?

They Finally Work.

Well, before, this industry was all talk, no action, a concoction of empty promises about different elements that sounded great individually but did not work well in combination.

But now, finally, I can safely say agents work. Let me first explain to you why now is the time, and then we’ll discuss our assistant in detail.

It’s all about “Context Engineering.”

When you hear the term ‘AI engineer,’ you must immediately think of context engineering.

Yes, no more prompt engineering; the new trendy term (and much more accurate, really) is ‘context engineering.’ Or as the saying in the industry goes, “everything is context engineering.”

The reason is that, well, it’s the only thing AIs need, actually.

In fact, I believe AIs are going to eat more and more pieces of the cake, meaning that a lot of the ‘scaffolding’ or ‘harness’ (technical terms to describe everything that is built on top of an AI model to make it work, the raison d’être of most of AI startup these days), will soon be not necessary.

In this interview, Noam Brown, Head of Reasoning at OpenAI, the Diplomacy world champion and one of OpenAI’s most valuable researchers shares this precise view, too, so my bearishness is not a wild hunch, the people at the bleeding edge of the technology are screaming it at you (and to clueless VCs).

Thus, to me, the future of humans in knowledge work jobs will resort to two things:

Set goals as a user,

Ensure the AI has the necessary context to solve the task.

What I’m implying is that most of the economic value will accrue to model-layer companies, and I genuinely believe application-layer startups (most AI startups) are simply living on borrowed time except for those that have understood that the only place AIs will consistently require external help is in ‘deterministic bubbles’ (areas of your business workflow where AI probabilistic prediction is…

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