AI Gives You Plenty of Free Weights. Snowflake Gives You the Gym.

My wife Emily and I are regulars at our gym here in North Carolina. We also both happen to work in the world of data and AI.

You have a lot of time to think at the gym. And this past week, it occurred to me that those two worlds have more in common than you might think.

Walk into a modern gym and you have choices. There’s a free-weight area filled with dumbbells, barbells, benches, plates and racks. And then there are rows of purpose-built machines, each designed to help you perform a particular movement in a controlled, repeatable way.

You can get a great workout with either one.

But they put very different demands on you.

And as enterprises rush to put AI to work, I see organizations facing essentially the same choice.

AI Gives You Plenty of Free Weights

Free weights are incredibly versatile. Give an experienced lifter a barbell, some plates and a rack, and there isn’t much he or she can’t accomplish.

But versatility comes with responsibility.

You need to know which exercises to perform. You need to select the appropriate weight. You need to understand proper form. You have to control the movement. And sometimes you need a spotter.

Get those things right, and free weights are fantastic.

Get them wrong, and the results can range from an ineffective workout to an injury.

That’s a pretty good description of the AI landscape today.

Organizations have access to an extraordinary collection of AI models, APIs, open-source frameworks, development tools and cloud services. If you have the expertise, you can assemble those components into almost anything.

But somebody has to assemble them.

Somebody has to determine where the data lives and how the AI gets access to it. Somebody has to write and maintain the code. Somebody has to integrate the different technologies. Somebody has to manage security, permissions, governance, infrastructure, monitoring and costs.

And every time you move data from one environment to another, you’re introducing another consideration that has to be managed.

The problem isn’t that the free weights don’t work.

The problem is that you’re responsible for making all of it work.

Snowflake Gives You the Gym

Now walk over to the machine section of the gym.

Each machine has been designed for a purpose. The mechanics are already engineered. The movement is more controlled. The weight system is integrated. Adjustments are built in. You don’t have to construct the equipment before you start exercising.

That doesn’t eliminate the need to know what you’re doing. But it eliminates a lot of unnecessary complexity between you and the result you’re trying to achieve.

That’s increasingly how I think about Snowflake.

Snowflake has evolved well beyond being a place to store and query data. With capabilities such as Cortex AI, organizations can access LLMs, build AI applications, work with structured and unstructured data, and develop agents within the Snowflake environment. Snowflake describes Cortex AI as allowing organizations to build and reason within the security perimeter their data already trusts, with integrated governance and access controls.

Think of those capabilities as the machines already installed on the gym floor.

Instead of pulling data out of Snowflake, sending it somewhere else, processing it through another technology and bringing the results back, many AI workloads can be brought to the data.

That distinction matters.

Snowflake Native Apps, for example, can run inside a customer’s Snowflake account rather than extracting the customer’s data for processing elsewhere. Snowflake’s existing role-based access controls and governance policies can continue to apply to the data the application is permitted to use.

Likewise, Cortex AI incorporates access controls and governance capabilities within the Snowflake environment.

In gym terms, you aren’t carrying the weights across town every time you want to perform another exercise.

The equipment comes to the weights.

Fewer Moving Parts Matter

This is where I think the analogy becomes especially important.

Imagine a gym where every exercise required you to assemble your own machine.

You grab a bench from one corner. A cable system from another. Some plates from another room. Then you fabricate a bracket to connect everything. Before every workout, you check that all the pieces still fit together.

Could you do it?

Absolutely.

But why would you do that if a properly designed machine already existed?

We see something similar in enterprise AI architecture. It’s easy to become enamored with what can be built and lose sight of what actually needs to be built.

Every additional component potentially means another integration to maintain, another dependency to monitor, another security question to answer and another piece of code somebody owns.

Custom development will always have a place. There are problems for which the flexibility of a highly customized architecture is exactly what’s required.

But custom shouldn’t automatically mean better.

Sometimes it simply means more things you are responsible for.

Having a Great Gym Doesn’t Give You a Great Workout

There’s another side to this analogy that I think is even more important.

You can join the best gym in North Carolina, walk through the door and have absolutely no idea what to do next.

Should you use the leg press? The cable machine? The treadmill? How much weight? How many repetitions? In what sequence? And what are you actually trying to accomplish?

The equipment doesn’t answer those questions.

Your goals do.

That’s where the trainer comes in.

A good trainer doesn’t begin by showing you every piece of equipment in the building. The trainer starts by asking what you’re trying to accomplish.

Lose weight? Build strength? Improve mobility? Train for a race?

Only after understanding the desired outcome does the trainer determine the right program and select the right equipment.

That’s also how we think about Snowflake at Evolution Analytics.

Snowflake is the gym. Cortex AI and the rest of the platform give you an increasingly powerful collection of equipment. Evolution Analytics is the trainer.

Our job isn’t to get you to use every machine.

It’s to understand what your business is trying to accomplish and determine the most effective way to get there.

Start With the Outcome, Not the Equipment

This is where technology initiatives often go sideways.

Imagine walking into a gym and announcing:

“My goal is to use the leg press.”

That’s not really a goal. It’s an activity.

Yet the technology equivalent happens all the time.

“We need generative AI.”

“We need an agent.”

“We need an LLM.”

“We need to implement this new AI tool.”

Those are technologies and activities. They aren’t business outcomes.

I’d rather start with questions like:

Can we resolve service incidents faster?

Can we help an adjuster process more claims without sacrificing quality?

Can we identify problems before they become expensive failures?

Can we eliminate hours of repetitive manual work?

Can we make better information available to an employee at the exact moment a decision needs to be made?

Now we have something to train for.

From there, we can determine which Snowflake capabilities, AI models, applications and architecture make sense.

Sometimes that means using a purpose-built machine.

Sometimes it means picking up the free weights.

And sometimes it means combining both.

You Still Have to Do the Work

There’s one final part of the gym analogy worth mentioning.

Machines don’t make you fit.

They simply provide an environment designed to help you work more effectively toward your goal.

Snowflake doesn’t magically create business value either.

You still need good data. You still need sound architecture. You still need governance. You still need people who understand the business problem. And you need the discipline to measure whether what you’ve built is actually producing the intended result.

That’s why we talk so much at Evolution Analytics about ROI on Snowflake.

The objective isn’t to use more technology. It’s not to use every new AI capability that becomes available.

The objective is to produce a measurable business result.

My wife and I don’t go to the gym because our goal is to spend more time using gym equipment.

We go because of what we want that equipment to help us accomplish.

Your Snowflake investment should be viewed exactly the same way.

AI gives you plenty of free weights. Snowflake gives you the gym.