Confessions of a Recovering Consultant: Why "Perfect" Nearly Killed GYST

I spent 15 years in management consulting. I was paid to be perfect.

In that world, a typo in a footnote is a sin.

A strategy without a MECE framework is heresy.

You do not present until the slide deck is bulletproof.

The data is triple-checked and the narrative is unassailable.

Then, I founded GYST. And I learned very quickly that what got me promoted in consulting would kill my startup. The pursuit of perfection.

I recently read about Julius Bruch’s journey from McKinsey to AI founder.

It was like looking at a mirror. We both had to unlearn the same lesson.

In a startup, "perfect" is the enemy of "done."

Here are five times my "consultant brain" tried to sabotage us and how we survived.

1. The "Perfect Strategy" Trap or The False Assumption.

We vibecoded our MVP in April.

Tested it in May and June.

Built our Alpha by August.

We targeted the "Middle Class" of creators.

We assumed the Top 5% already had their shit together.

Surely, they had Enterprise tools and CFOs.

We were dead wrong!

A top creator saw our Alpha and told us:

"I have 20 people on my team, and I still can't get a P&L on a monthly basis."

In the creator economy, more resources often just equal more chaos.

He offered to invest and be a brand ambassador if we pivoted to serve the Top 5%.

We stopped trying to educate the middle class on why they needed BI.

We started selling water to the thirsty giants.

2. The "Perfect Code" Trap or Hackathons.

Traditionally, you build the software, QA it, polish it, and then show it to the client.

After realizing the Top 5% was our market, we tested the waters in October.

The CEO of a global talent management firm told us he had 55 people manually doing what our code did automatically

The demand was so hot that the traditional "build-then-ship" cycle was too slow.

We decided to "vibecode" in public via Hackathons.

We built tools with creators in the room to solve immediate pain points.

Then went back to the office to properly code them.

We set a target of 2 Hackathons between Nov and Christmas.

We did 6. And 4 of the participants are angel investing!

3. The "Perfect Feature" Trap or the Scope Creep Challenge.

Our MVP was too ambitious.

We added an AI Voice Agent.

In English and Portuguese.

And a Dynamic Brand Deal Pricing Calculator.

My consultant brain wanted the "Complete Solution."

Ironically, perfectionism helped here.

They weren't working to our standard during Alpha testing.

The AI Voice Agent didn't respond fast enough. And wasn't "intelligent" enough.

The Pricing Calculator didn't have enough data to be statistically significant.

We pulled them back.

Shipping a bad feature kills trust faster than a missing one.

We admitted we aren't the experts in everything.

We partnered with people who have deeper knowledge.

They're helping us reach the right level.

Not "Perfect". Just "Good Enough".

4. The "Perfect Data" Trap or the Onboarding Challenge.

My consultant brain said: "Data integrity is paramount".

To give creators true ROI, we need a single source of truth.

Users must authenticate into every platform upon sign-in to see verified revenue metrics.

It was a nightmare!

The majority of creators in our Alpha tests did not know their passwords. They used FaceID on their phones.

We created a massive drop-off at step one because we demanded high friction before showing any value.

So we broke the "perfect data" rule.

We changed onboarding to require only social media handles.

We immediately consolidated their engagement metrics.

Users saw the magic instantly.

We kept the revenue features behind the authentication wall.

Once they saw the initial value, they hunted down passwords.

Is it perfect data from second zero? No.

Do customers prefer it? Hell yeah!

5. The "Perfect Model" Trap or the Pricing Challenge.

We studied every "Agentic AI" pricing model in the market.

We looked at complex matrices, credit systems, and token usage fees.

We built a model that charged for an initial credit of tokens plus usage fees per additional token.

It perfectly mimicked our costs.

It was a beautiful financial model.

It was a user experience disaster.

Customers looked at the pricing page and...

They didn't understand our costs.

It created a gigantic adoption barrier.

We scrapped the "smart" model.

We went with the model that landed best: Plain Vanilla Monthly Subscription.

We will control our costs.

But we will keep the model as simple as possible.

Complexity is friction. It is the death of growth.

The Bottom Line

If I had stayed in my "consultant" mindset, GYST would have:

- A perfect password-protected login that no one used,

- A roadmap filled with half-baked features,

- A pricing model that required a PhD to understand,

- And zero customers.

We chose "Hell Yeah" over "Perfect".

We embraced the mess.

We found our investors.

Our market.

And our momentum.

What about you? What "perfect" habit are you unlearning this year?