“The past is the past.”
A simple statement but one I can finally get behind.

It’s been a while since I’ve written a blog post. Not because I’ve been too busy, but because nothing felt critical enough to say out loud. Still, I’m here. Still grinding. Still pushing. Still searching for that next role out in the world.

Lately I’ve been laser-focused on business intelligence and data analytics. And honestly? What fires me up is how many companies are chasing AI like it’s some magic bullet… while completely ignoring the fundamentals. You can’t build intelligent systems on top of chaotic data. You can’t conjure insights from a swamp. Yet that’s exactly what’s happening everywhere.

I spoke with an old coworker recently, and her team is still using outdated pipelines, manual processes, brittle system handoffs, layer after layer of testing just to coax data into a usable state. All the energy goes into cleaning, reconciling, validating. None into insight.

The job search grind

Day in, day out, I’m applying to roles left and right. Talking with recruiters. Reaching out to old coworkers. Positioning myself for something new.

Doing everything right doesn’t mean the right thing will happen.

I’m still getting leads for product quality and validation roles, work I no longer value. Meanwhile, other people are out there making double what I’m asking for… doing a worse job than what I bring to the table.

It’s a strange world.

Why BI matters now more than ever

Getting decisions into the hands of the right people has always been the goal. When transactional systems capture the heartbeat of a business, that information must be transformed into action.

AI and automation are not new dreams, they’ve always been the horizon. But without understanding the business, its direction, and the meaning of its data, none of it sticks.

That’s why BI matters now more than ever: it is the bridge between stored information and actual intelligence.

Companies chasing AI backwards

So many companies are putting the cart before the horse.

They implement AI directly on transactional systems.
They deploy spot-solution models to fix “critical path” bottlenecks.
They skip the middle steps, the ones that actually matter.

Most CIOs say data governance and accurate data stores are key to reliable AI. But knowing the phrase and knowing how to achieve it are very different things.

And honestly? A lot of people don’t know how to do BI correctly, or at all.

The coworker conversation

My coworker and I met at Bipbop, nothing fancy. It was great seeing her. I shared some personal details about my past roles and walked her through some BI principles she hadn’t heard before.

The truth revealed itself quickly: timing is everything.

She’s skilled. She’s capable. But the problems she described?
They were straightforward.

I was troubleshooting with her on the spot, no experience with her platform, just instinct and pattern recognition.

It reminded me of Baxter, working with senior data people who were brilliant in some areas but had glaring blind spots in others. Sometimes even the basics.

The hiring paradox

Talking with my family, I see it over and over again:

There are people in roles who shouldn’t be there…
and people out of work who would absolutely crush those roles.

I am one of those people.

I’m not a “10x engineer,” but I’m damn creative, and I find success in many directions. Yet hiring feels like a joke lately. The interview questions are shallow, they never tap into passion, drive, or depth.

That’s something I plan to change in my next interview. I want to steer the conversation toward what actually matters to me.

Moving forward with new clarity

I’m grateful for the people in my life, and especially for my old coworker, who helped clarify something important:

You don’t need to be perfect to succeed.
You just need to show that you have the mentality to succeed.

The past is the past.
And now it’s time to move forward.