General Hill Climbing

Picture your goal as a hill and yourself partway up it. The next good move is the step that takes you higher. Hill climbing is the system doing exactly that, over and over: from wherever you are, find the move that closes the most gap, take it, then look again.

Why it exists

Big goals don’t get reached in one leap. You don’t cross from your current state to your ideal state in a single move, and any plan that pretends otherwise breaks the moment it meets reality. What actually works is a repeatable step: look at where you are, look at where you want to be, take the move that shrinks the distance.

Hill climbing exists because that step is general. It doesn’t care whether the hill is a bug you’re chasing or a book you’re two chapters into. The same move works on both. So the system doesn’t need a different method for every kind of goal. It needs one method it can apply again and again, and this is it.

There’s a second reason. A single step is small enough to check. You can look at one move and say whether it took you higher or not. That makes the climb honest at every point, instead of only at the end when it’s too late to fix.

How it works

On every interaction the system does one thing: pick the next move that reduces the gap between your current state and your ideal state. That’s the whole climb, run one step at a time.

The steps get better as you go. Memory compounds, so each session the system reads your current state more accurately than the last. Skills keep expanding, which gives it new ways to act on the gap. And some of the climb now runs on its own: hooks automate the routine moves so they happen even when you’re not watching. Each of those makes the next step land better than the one before.

The Algorithm is this loop made systematic. Where a quick reply might take one obvious step and stop, the Algorithm runs the full climb in phases and checks after each one whether it’s genuinely higher up the hill or just busy. Simple asks get a short climb. Hard ones get the whole ascent.

Where it fits

Hill climbing sits between the other two core ideas. Current State to Ideal State is the move the whole system makes. Hill climbing is how it takes each individual step of that move. Euphoric Surprise is how you know a step actually landed.

The Algorithm is where the climbing happens in practice, one phase at a time. Pulse is where you watch it: the dashboard shows how far up the hill a piece of work has come and what the next step is. Memory and skills are what make each step stronger than the last.

What it feels like

Think about the last time a huge goal felt frozen. It was too big to start, so you stared at it and did nothing. The size of the hill was the whole problem.

Hill climbing takes the hill off your shoulders. You never have to see the whole ascent at once, only the next move. The system holds the shape of the goal and hands you one step at a time, each one small enough to actually take. Progress stops feeling like a cliff and starts feeling like walking. You keep moving, and one day you look back and you’re most of the way up.