End Pipeline Bull$#*! — AI Is Counting on Us to Call It Like It Is

There’s a moment we kept seeing at ODSC East last week. Someone would be walking by, scanning booths like we all do at conferences—half-looking for free stuff, half-trying to avoid eye contact—and then they’d stop. Dead in their tracks. Not for a t-shirt. Not for a sticker. But for the words on our banner:

“End Pipeline Bull$#*!”

And we’d see it happen in real time: the smirk, the head tilt, the “yeah, actually…” look. It was visceral. Something about those words broke through. Because deep down, every data engineer, analytics lead, and architect walking by knows—it’s true.

Here’s the thing—it wasn’t the profanity that got them. It was the honesty. Everyone in this space is quietly frustrated by the state of their data infrastructure. It’s brittle. It’s over-engineered. It breaks if you breathe on it wrong. But it’s been around so long we’ve all just learned to tolerate it.

And normally, that would be bad enough.

But now? In 2025? With AI woven into every product roadmap and quarterly OKR?

Bad data pipelines aren’t just annoying anymore.

They’re dangerous.

We’re watching AI initiatives collapse under the weight of incomplete, inconsistent, untrusted data. Recent studies estimate that up to 70% of AI projects stall or fail, and again and again, the root cause isn’t bad models or prompts—it’s bad data. (source) Not bad models. Not bad prompts. Just data that was too hard to get, too hard to trust, or too late to matter.

That’s why this conversation matters.

That’s why it’s time to call BS.

So what are we doing about it?

At Matterbeam, we’ve been building around one core idea: pipelines shouldn’t exist the way they do today. They shouldn’t dictate how your data moves or when. They shouldn’t require weeks of upfront planning and constant backend babysitting. And they definitely shouldn’t slow down every experiment, integration, or insight your team is trying to deliver.

We’re building a data platform that embraces what we call data agility—a way to move, transform, and deliver data on demand, without the rigidity of traditional ETL.

Here’s what that looks like:

• No more pre-baking logic into brittle pipelines. With immutable, replayable streams, you can transform data when you actually need it—not when you guess you might later.
• No more ETL drift where your source-of-truth gets reshaped 10 times before it lands. We separate collection from consumption. Store once, shape infinitely.
• No more “ask engineering” delays. With late transforms, ops teams, analysts, and even AI systems can get exactly the data they need—without rewiring upstream flows.

The result? Less maintenance. More flexibility. Faster experimentation. And teams that actually get to focus on building value, not plumbing.

It’s not magic. Just a better way to think about data infrastructure—if we’re finally ready to stop accepting pipeline BS as the cost of doing business.

So yeah. Maybe a little profanity on a banner isn’t the most conventional conference move. But maybe that’s exactly what this industry needs right now: a reason to pause, laugh, and admit that it’s time for something better.

Want to see what we mean?

Watch our CEO, Michael Kowalchik, walk through a no-BS breakdown of how we’re flipping the data pipeline model on its head.

Ready to ditch the old way and embrace the new? Join us and transform your approach to data forever. Get started with Matterbeam today.