Stop Building Steps. Build For States.

You have a certain project in hand. On some things there’s clarity, on other things you do some research. Then, you compile all of it into actionable steps, and design a roadmap with reachable milestones so getting it done is a guaranteed matter.

Simple, straightforward, and pragmatic, right?

The execution starts. First week runs smoothly, there’s motivation, there’s progress, and most importantly, the project is now alive.

On the second week, parallel duties start to drain the motivation and energy. Some of those are objectively more important and urgent at the moment. You still manage to keep the project alive, but surrounding context friction starts doing its thing.

On the third week, this reality has persisted, but the friction starts to compound in a way that corrodes the project’s performance. What was straightforward and clear on the initial planning now feels like a burden. The weight of urgent matters starts to acquire relevance in a way that truncates. The frustration kicks in, and the input of general duties carries this energy.

On the fourth week, the burden is now too much to handle. You now have to make a choice: getting important and urgent matters done OR continuing to execute your project as it demands to do so. The two options are no longer possible to maintain in parallel, you’ve tried so for weeks, and the result has been negativity, inefficiency, delays, and an overall sense of “this is not working out”. Your plan that once looked crystal clear on paper now faces a blurry reality. The conclusion after this cycle:

“I’m not able to do this. I tried and it didn’t work out”.

Most likely, you end up looking up for a new project. Fresh airs, more research, more initial clarity, and a new sensation that this is now a thing that you’ll be able to execute well. However, turns out that you are entering the same ol’ cycle, once again.

Why does this happen? Why something that make so much sense don’t work? Why does something that someone else did successfully, and I managed to capture the essence of their work, don’t work out for me? Is it luck? Is it timing? Is it skills?

The actual response is way simpler and separate to those reactive spirals of thought:

Systems don’t work in isolation. Context deeply affects the performance of the components that form a system, and therefore, its outputs.

The plan was originally designed without having the surroundings into account. The focus was so much about “How do I do this?” that it totally missed “Will doing it like this survive facing my current context?”. It may sound obvious in hindsight, but it’s rarely the first instinct that one focuses initially. Integrating the context load into a project’s course is more complex at entrance than just focusing on the project itself. It requires a macro perspective that is active when focusing on micro-level matters.

Let’s clarify the fact that:

Complex ≠ Hard

Simple ≠ Easy

The scenario described at the beginning of this article is about a person who leaned into the simple path: acquired a direction inspired by an external source, designed a roadmap that felt right, reached for a familiar shape of work, and never made the effort to calibrate using the reality itself.

This was a case of heuristic thinking:

• pattern-match
• intuition
• approximation
• lack of underlying logic and context

People naturally design and operate through heuristics. It’s simpler and more natural for the mind to operate like this. The fact is that this model of thinking is more than enough for the vast majority of daily actions and decisions. We naturally seek for low-effort mechanisms for a reason.

But, what happens with ambitious and demanding matters? We may end up working harder and provoking more friction if we don’t identify that saving time upfront leads to poor performance in the long run. There’s this conception about “Just doing it” that biases the complexity that we are willing to assume before starting out something. It’s not that the idea is wrong, but more about that a poor interpretation of it can limit the threshold of individuals to a certain level.

In practice, this is the threshold that has been passed by people that raise well educated kids, maintain a proper physique, overachieve in their careers, thrive in social environments, keep interesting and fulfilling hobbies, and they do it so in a sustainable way, all in parallel, with such a grace … like it’s a natural thing.

How is this even possible?

This is achieved by algorithmic thinking:

• Problems decomposed into smaller part
• Identification of relevant information and discarding irrelevant details
• Clear, non-ambiguous instructions with a sequential order
• Verification that the process works efficiently

People with the ability to execute this type of thinking at the right time is able to integrate new cogs into a much larger machine at will, and this comes from the fact that they deeply understand how the machine itself works. They know at what times of the day they are more efficient, how to execute a routine in a way that serves them and not the other way around, how long does it take them to get certain type of tasks done, how does a balanced day look like and how to get it with ease, and so on. For this level of thinking, it’s essential to be aware of what conforms a cycle that includes all of the aspects that you want to make part of your life.

A state is the condition you’re actually operating in during a given cycle. If we zoom back to the example given at the start of this article, you can see that the design was only ever built for week one, and the rest of it was a personal effort keeping it alive. The opening plan was a sequence that assumed week one would repeat, while a real algorithm branches on conditions, and those conditions are states.

Cycles are better measured in relatively short terms of time, and it takes a couple cycles before you can read your states reliably. These cycles typically are days, weeks, months, quarters, semesters, and years.

A state-based plan asks “what does this project look like when I’m at full capacity, at half, and at the minimum that keeps it alive?” The project never has to die. It just needs to change its shape with the state. This is what makes a system able to be executed with grace. The key is to know which version of each commitment fits the state you’re in.

But good news: this means that setbacks in execution are not a matter of capacity, but of a system’s flaw that can be corrected.

“I am not the problem. The plan couldn’t handle a state it was never designed for”.