I Built an AI Tool to Generate SEO Blogs & Pages - Here’s What I Learned

Source: Dev.to

Introduction

As developers, we love automation but content creation is still painfully manual for most teams.

I kept seeing the same problem across founders, indie hackers, and agencies:

• Writing SEO blogs takes hours
• Landing pages are repetitive
• Social content is inconsistent
• Existing AI tools feel fragmented or overcomplicated

So I decided to build a tool to solve my own workflow problem first and that project became Minineo.

This post isn’t a promo. It’s a breakdown of what I built, what worked, what didn’t, and what I learned along the way.

The Original Problem

My goal was simple: go from keyword → published content with as little manual work as possible.

Most tools:

• Generate raw text only
• Don’t respect SEO structure
• Break when you try to scale
• Leave publishing & formatting to you

I wanted something developer‑friendly, predictable, and automatable.

The Approach I Took

Instead of one big AI prompt, I split the system into clear stages:

• Intent‑first content planning
• Strict structure enforcement
• Usage limits handled server‑side
• Publishing treated as a pipeline, not a button

That design decision saved me weeks later.

Architecture (High Level)

• Next.js for the app layer
• Supabase for auth, data, and RPCs
• Server Actions for usage enforcement
• AI models only handle generation, not business logic

Key rule I followed

• Never trust the client for usage limits
• Always enforce limits via server‑side RPCs

This made the system production‑safe early on.

Content Generation Strategy

Instead of “write a blog about X”, the AI receives:

• Fixed heading hierarchy
• Explicit SEO constraints
• Word‑count bounds
• Section responsibilities

This dramatically reduced:

• Hallucinations
• Fluff
• Rewrites

The output became predictable enough to automate publishing.

Media Was Harder Than Text

Text was easy. Media wasn’t.

Problems I hit

• Hotlinking external images (bad idea)
• WordPress rejecting uploads
• Social platforms requiring different auth models

Solution

• Download → upload → replace URLs at publish time
• Treat media as a post‑processing step, not generation

This separation kept the core clean.

What Didn’t Work

Being honest, a few mistakes:

• Trying to support every social platform early
• Over‑engineering UI before workflows were stable
• Letting AI decide structure (never again)

Each rollback made the system simpler and more reliable.

What Worked Surprisingly Well

• Strict prompts > “creative freedom”
• Build‑in‑public feedback
• Treating content like data, not prose
• Shipping small, testable pieces

Why I’m Sharing This Here

Dev.to helped me countless times while building this.

If you’re:

• Building an AI SaaS
• Automating content workflows
• Enforcing usage limits properly
• Publishing to platforms programmatically

I hope something here saves you time or mistakes.

What’s Next

Next on my list:

• Smarter media enrichment
• Better scheduling reliability
• Even stricter content validation

Still learning. Still iterating.

If you’ve built something similar or hit the same challenges, I’d genuinely love to hear:

• What broke for you?
• What scaled unexpectedly?
• What would you do differently?

Happy to answer technical questions in the comments.