Your AI Personal Secretary

Greetings, my fellow readers. Finally, after months of restraining myself, I’ve finally decided to try the new agent harnesses, OpenClaw-esque products that, theoretically, allow you to create your personal virtual assistant.

They are not exempt from issues and things to improve, but they work sufficiently well to the point that ignoring them is a disservice to you.

Thus, today, I’m going to explain:

How these agent harnesses, skills, and other crucial terms you have to be familiar with work, learning how, in fact, these are some of the simplest software to ever exist (don’t get me wrong, being simple is the feature),

How to use them (and how not to) by offering you my way (how I did it), which requires some technical savvy, and the easy, you-can’t-go-wrong way. Of course, I’ll explain my reasons for why I’m doing it my way.

And what this tells us about the future of software (spoiler: you are going to understand why software companies are really crashing).

By the end, you’ll have great intuition as to what this new form factor everyone is going crazy over is about. You’ll also learn what agents truly are; no jargon, no bloom, just what they are and nothing more.

And I’ll also show you how I’m automating my life using these agents, in particular, how I use Telegram to talk to my own AI and take care of the things my agenda prevents me from doing myself.

Let’s dive in.

It’s all Context Engineering

We’ve been hearing about this so-called agentic revolution for quite some time. Probably so have you.

And as I already explained in a recent post, agents have finally hit that point: they work. Kind of. But you know how this works; in two months’ time, I won’t be adding ‘kind of’ anymore, so I suggest you start paying attention today.

And this new page in the AI story has been written by a project called OpenClaw (although it’s not the one I’m using, as we’ll see later).

The Simple Agent

Agents are one of those things that people make look unbelievably complex despite being, in essence, outrageously simple.

It’s all marketing for what’s actually a simple runtime prompt modification. For that, let me demystify agents for you.

Our most powerful AIs, be that OpenAI’s GPT-5.3 Codex, Anthropic’s Claude Opus 4.6, or the soon-to-be-released DeepSeek v4 and GPT-5.4, which I both trust are going to be incredible, are all simple sequence-to-sequence stateless machines.

But what does that mean? Well, they take in an input sequence, normally text, and return a continuation to that sequence. They are mathematical functions (literally) that predict ‘what comes next’ in a sequence.

Source: Nano Banana 2

By themselves, they don’t have a persistent state, meaning every interaction is, by nature, new; they don’t remember previous interactions. Thinks of this as every time you talk to an AI model, it’s as if you were meeting them for the first time.

They are like Dory in Finding Nemo, an entity…

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