u/creo_offica

I’ve been building CRÉO, a workspace for creators that combines analytics, content planning, audience intelligence, and AI-assisted recommendations.

But I’ve realized something while building it:

An AI saying “your audience will like this” isn't particularly useful if it can't explain why.

So I’m working toward a different approach:

Data → Evidence → Analysis → Confidence → Recommendation → Experiment → Result

For example, instead of:

>

CRÉO should eventually be able to say:

>

And if the recommendation turns out to be wrong, that result should feed back into the system.

I'm still early in building this, so I'm curious:

What would make you actually trust an AI-generated recommendation about your own content?

Evidence? Confidence scores? Sources? Showing the reasoning? Something else?

I’ve been building CRÉO, a creator intelligence workspace, almost entirely with AI-assisted development.

For a while, I thought the hard part was getting the product built.

It isn’t.

The hard part is knowing whether what you built is actually good.

Recently, someone on Reddit gave me a pretty brutal evaluation of CRÉO.

His criticism was basically:

>

That hit hard.

Because he was right about something important: an impressive UI and a functioning app don't prove product quality.

So instead of defending the product, I’m treating the criticism as part of the build process.

The current plan:

• Finish the product UI properly
• Identify the two biggest product weaknesses
• Define what “good” actually means for each core feature
• Learn the underlying analytics/content strategy instead of blindly trusting the LLM
• Build measurable evaluation criteria
• Stress-test the AI outputs instead of assuming they're correct
• Then expand the feature set

CRÉO shouldn't just look like creator intelligence.

It needs to earn that description.

I'm still early, still learning, and definitely not pretending I have everything figured out.

But that's probably a better place to build from than pretending the first version is already perfect.

Building in public. One uncomfortable lesson at a time.

#buildinpublic #indiehacker #SaaS #AI #creators #productdevelopment

I've been building CRÉO, a creator intelligence workspace.

I've spent a lot of time recently working on the UI — and honestly, the visual side is starting to come together exactly how I wanted.

But while discussing the product with someone who works closely with LLM systems, I got hit with a much more uncomfortable question:

How do you actually know your AI is giving good advice?

Not:

>

But:

>

That changed how I'm approaching the next stage of CRÉO.

The current product can work with real creator information and manually entered analytics. But I'm now working toward a proper evaluation framework instead of letting the model decide everything implicitly.

The goal is eventually:

Creator data + content history + audience + external signals

→ analysis
→ evidence
→ recommendation
→ explanation

Rather than:

Prompt → AI opinion → trust me

The UI is getting finished first.

Then comes the much harder part: making the intelligence underneath it something I can actually defend.

That's probably the most important thing I've learned while building this.

I've been building CRÉO for a while, and today we finally clarified something important:

I don't want CRÉO to be another wrapper around an AI model that simply generates content.

The direction is becoming:

Creator Memory → Create → Analyze → Learn → Improve → Grow

The first major analytics version will let creators provide performance data for their content and have CRÉO turn that into understandable graphs, insights, explanations of what worked/failed, and recommendations for what to do next.

Later, the system could connect directly to social platforms and automatically collect that information.

We're also planning future capabilities around thumbnail effectiveness, deeper creator intelligence, smarter AI assistance, and eventually collaboration/team infrastructure.

I'm deliberately not building everything immediately. The current priority is getting the core product polished, useful, and actually in the hands of creators.

I'd genuinely appreciate feedback from other creators/builders:

Would a system that remembers your creative process AND learns from your content performance actually be useful to you?

I've been building CRÉO for a while, and today we finally clarified something important:

I don't want CRÉO to be another wrapper around an AI model that simply generates content.

The direction is becoming:

Creator Memory → Create → Analyze → Learn → Improve → Grow

The first major analytics version will let creators provide performance data for their content and have CRÉO turn that into understandable graphs, insights, explanations of what worked/failed, and recommendations for what to do next.

Later, the system could connect directly to social platforms and automatically collect that information.

We're also planning future capabilities around thumbnail effectiveness, deeper creator intelligence, smarter AI assistance, and eventually collaboration/team infrastructure.

I'm deliberately not building everything immediately. The current priority is getting the core product polished, useful, and actually in the hands of creators.

I'd genuinely appreciate feedback from other creators/builders:

Would a system that remembers your creative process AND learns from your content performance actually be useful to you?