One strategic signal 🔭
One (human) prompt 🧠
One subtraction opportunity ➖

Created by Sam Rogers · Powered by Snap Synapse Freely available on Substack, LinkedIn, and our mailing list. New issue every Monday.

🔭 Signal: Fire, Aim, Ready!

Last week I wrote about the dangers of saying "not my job" about AI. This week, I promised we'd talk about what to build. But first, we need to talk about what's actually in the way.

It's not skill. It's not access. It's the deeply held belief that we need to understand something before we can do something with it.

For decades, that was true. Study the manual. Get the certification. Learn the platform. Then perform. Preparation preceded action, and professionals who valued education built entire careers on that sequence. There was a path to follow, and people to show you yours.

AI erased our paths. Not because preparation doesn't matter, but because the tools now move faster than anyone can teach. By the time we've finished understanding the current version, the next one has shipped. Opus 4.6, Codex 5.3, and Claude's Excel & Powerpoint integrations all landed in the past two weeks alone. The barrier to building dropped again. Not incrementally. Categorically.

The people building useful things right now aren't the ones who understood AI first. They're the ones who started before they were ready.

I think of the process as Fire, Aim, Ready. Start something (fire). Figure out how to direct it (aim). Deliver that, and you're actually ready to start the next thing for real (ready). Uncomfortable for anyone trained to prepare thoroughly before acting. But with AI, comprehension is a byproduct of doing, not a prerequisite for it.

Here's what that looked like for me with something as familiar as Excel:

In October, I asked Claude to help build financial projections for a new business. It was a mess. I tried again in late November. Got somewhere, mostly. Lotta work and not really usable though, very generic. Two weeks ago I tried once more and was stunned: a 12-tab spreadsheet that worked on the first try, nuanced to my particular business rather than averaging all startups with templated plans. I didn't get dramatically smarter between October and February. The tools got better while I kept showing up. Three rounds of Fire, Aim, Ready.

That Excel example matters because nobody thinks of spreadsheet work as "building." But it is. And from there, the identity shift is smaller than you think.

My GitHub profile isn't a developer portfolio. It's a collection of annoyances I stopped tolerating. The audible-pdf-renamer exists because 50+ audiobook PDFs had garbage filenames. The ai-feature-tracker started as prep for a class I'm teaching this week. Protocols skill-provenance and turnfile came from friction working across Anthropic and OpenAI tools interoperably.

None of these required computer science credentials, I don't have those. All required getting annoyed enough to stop waiting for someone else to fix the problem. Annoyances? Those I've got, and I'm guessing you do too.

This week I'm teaching a 3-day ATD certificate workshop on "Applying AI in Learning & Development". The participants are working professionals, not developers. The goal isn't to turn them into programmers. It's to shift how they see: from consumers of AI capability to builders of solutions. That shift doesn't start with code. It starts with one act of building.

🧠 Strategic (Human) Prompt: What's Annoying?

Instead of asking: "What AI skills do I need to learn?" Ask: "What's one small friction in my work that I keep tolerating?"

Then try this today. Preferably now-ish:

1. Open your favorite AI and describe the annoyance.

2. Ask for 5 different solutions to solve for it.

3. Scope the top 2-3 solutions. Identify the plan and next steps.

4. Pick one and start. It won't be perfect on the first try because the context is missing. That's normal.

5. Get better at providing that context. Then watch how you start seeing problems differently.

This is how the shift happens. Not through study, but through contact.

➖ Subtraction Opportunity: Understanding First

Stop trying to fully comprehend AI before using it. There is always more to learn. But literally no one on earth fully comprehends what's happening yet.

This is the specific drag for educated professionals who built careers on preparation and mastery. The instinct is to read the tutorial, watch the webinar, take the course, then try. With AI, that sequence is now the bottleneck.

Stop: reading the third article about a tool you haven't opened yet.
Don't: wait for the workshop before experimenting.
Subtract: believing you need to understand the whole stack before touching any of it.

Do: describe one problem to an AI and follow where it leads.

You'll understand more after one clumsy attempt than after ten hours of reading. The context you're missing isn't in the documentation. It's in the doing.

🏄 Analogy of the Week: Surfers and Beachgoers

A surfer and a beachgoer look at the same ocean. The beachgoer sees water, waves, weather. Maybe reads a book about ocean adventures.

The surfer sees opportunities. That set rolling in? That's not scenery. That's a ride.

The difference isn't knowledge. Both might understand wave mechanics equally well. The difference is relationship. The surfer has been in the water. Wiped out. Felt the pull and the tumble. Swallowed some salt. Now with grit in their teeth, they read the ocean differently. Not because they studied harder, but because they interacted with it.

Building with AI works the same way. Once you've shipped something, even something tiny and imperfect, you stop seeing AI as a topic to understand and start seeing problems as waves to catch.

You don't become a surfer by reading about the ocean on the beach. You become one by first putting the book down, picking up a board, and walking into the waves.

♬ Closing Notes

The word "builder" used to mean someone with technical credentials and a development environment. That definition is dissolving fast. Today, a builder is anyone who sees a problem, describes it clearly, and iterates toward a solution. The tools meet you more than halfway now.

You don’t have to go from non-technical to technical, just from understanding-first to doing-first. From seeing AI as something to study to seeing it as something to build with.

If Fire, Aim, Ready makes you uncomfortable, good. That discomfort is the sound of an old sequence breaking. And on the other side of it is a version of you that sees problems the way surfers see waves.

Go catch one this week.

Until next Monday,

Sam Rogers

Builder of Small, Annoyed Solutions

Snap Synapse – from AI promise to AI practice

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