Play the Whole Game

I've been learning Spanish for almost a year.

But the moment I truly felt like I was learning a language — not just studying one — wasn't when I memorized a batch of vocabulary or hit a new Duolingo streak. It was after my first lesson on iTalki with a real person from Mexico. We stumbled through twenty minutes of broken conversation, I hung up the video call, and my heart hadn't quite settled yet.

I booked that lesson on day three of learning Spanish.

I could barely string a sentence together. But I knew that if my goal was to actually talk to people when I travel, I needed to understand as soon as possible what the whole game looked like. And the whole game was the conversation itself.

What Does "Play the Whole Game" Mean?

The idea comes from educator David Perkins. In Making Learning Whole, he makes an observation that stuck with me: most of what we learn in school consists of fragmented sub-skills, with no one ever showing us what the complete game looks like when those pieces come together.

Think of a kid learning baseball. If all they ever do is practice their swing in isolation, and they never actually play a real inning, they don't really know what they're training for.

Perkins argues that learning should involve the whole game from the very beginning — even a simplified, beginner-friendly version of it. That's far better than endlessly drilling parts in isolation.

I keep coming back to this framework because of what it quietly implies: until you've seen what the destination looks like, you don't actually know which road you're on.

Two Examples That Stayed With Me

Learning Spanish. My goal isn't to pass a DELE exam or read One Hundred Years of Solitude in the original. It's specific: travel to Spanish-speaking places and have real conversations without relying on Google Translate. So my whole game is real conversation.

That's why I booked my first iTalki lesson on day three. Not because I was ready — I wasn't — but because I needed to feel what a real conversation was like before I could understand what I was actually missing. And before I could figure out what to work on next.

Training for HYROX. HYROX is an indoor race that combines running and functional fitness: eight running segments alternating with eight workout stations. If my goal is to compete in two official races this year, the whole game is completing the full race format.

So from day one of training, I started attending dedicated HYROX classes at Savage that run through the full sequence every week. Not "build all the foundations first, compete when ready." Just simulate the race, discover weaknesses in the process, then target those specifically.

Both experiences gave me the same feeling: you have to run it once to know what the race is.

What Does This Have to Do With AI?

Lately I've been building a few small automation workflows with AI tools. And I've noticed a pattern in how people (including past me) tend to approach it:

First, learn prompt engineering. Then research the right framework. Then read case studies. Then decide you need to understand a bit more before starting…

And nothing gets built.

But if you apply the whole game logic to AI, the first move is clear: can you build a rough prototype that actually runs, as fast as possible?

It doesn't need to be polished. It doesn't need to be complete. It doesn't even need to look good.

It just needs to run — so you can click through it, feel it, and understand what this whole game actually looks like.

Say you want to use AI to automatically summarize a weekly industry report. Step one isn't researching RAG architecture or comparing LLM API pricing. Step one is: before you finish work today, manually run the process once. Use Claude or ChatGPT to process one report, paste the output into a doc.

That's your v0.

Once you've run it, you'll immediately find the real problems — maybe the output format is wrong, maybe key information keeps getting dropped, maybe you don't even know what "done" should look like. None of these show up during the research phase.

But more importantly: you now know what the game is.

The direction for every iteration after that becomes obvious.

Why Are We So Reluctant to Run It First?

I've thought about this for a while.

Part of it is psychological: running it first means exposing your gaps. You'll discover you know less than you thought. You'll fail. It'll feel awkward.

But there's another part — a false belief that more preparation reliably produces better results. That if we just get ready enough, we'll be protected from the discomfort of not knowing.

Sometimes that's true. But often, preparation is just a way of postponing the moment we'll eventually have to face anyway: actually doing the thing.

One run-through beats a thousand drills.

So.

The next time you want to start something new — learn a language, train for a race, build something with AI — ask yourself first:

What is the whole game here?

Then go play the simplest version of it today.

Even if it's only twenty minutes. Even if you're not ready. Even if the result is a mess.

You'll know more about what to do next than any amount of preparation could have told you.