Automation

AI Auto-Blogging Demo Site

100%
automated flow
ai blog autoposting illustration

A working demo that shows how AI-driven autoposting can keep a website fresh without manual effort. Visitors can see how content is generated and published automatically — a practical proof-of-concept for future client automation flows.

Olga LescuyerFrontend Developer,SEO specialistNatalia MelnovaUX/UI designer &Automation Strategist

About Project

  • Scope of Work

    / Development / Automation

  • Timeline

    / 1 day

  • Website Building

    / 30 min

  • Automated Flow

    / 100%

  • Tech

    / React / Next.js / TS / Vercel / Airtable / API RESTful / Make

Team / Credits

  • Automation

    Natalia Melnova

  • Development

    Olga Lescuyer

Client

This project is an internal prototype developed as an experimental proof-of-concept. No client content or personalization was used; it demonstrates the technical flow only.

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Behind this demo is a simple idea: technology should take away the repetitive tasks and leave more space for creativity. We built it as a proof of concept, but also as a way to explore how digital can feel more effortless, sustainable, and meaningful.

For us, it’s not only about showing what’s possible — it’s about rethinking how people and technology work together to make the web a little better every day.

/ Goals

AI Autoposting: What We Set Out to Prove

The main objective was to build a functional prototype that demonstrates end-to-end AI autoposting. The goal was to test how AI-generated drafts can be pulled, formatted, and published automatically — saving time and ensuring blogs never sit empty.

Key goals included:

  • Automate repetitive blog posting tasks
  • Validate API reliability and content quality
  • Prove seamless integration with a modern front-end stack
  • Test real hosting and deployment performance
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/ Challenges

Managing AI Output and Workflow Stability

Building an auto-blogging system involves more than just generating text. The biggest challenges included controlling the consistency of AI output, handling unexpected API errors, and ensuring published drafts follow a clean structure.

Specific challenges were:

  • Normalizing inconsistent AI responses
  • Avoiding duplicate or irrelevant posts
  • Keeping performance high while querying APIs
  • Managing deployment stability for always-on posting
/ Result

Demonstrated Impact of Automated Content Publishing

The final prototype proves that a simple autoposting system can work reliably and save significant manual effort. While not personalized yet, it shows how a business can keep its blog alive with minimal input.

The demo site demonstrates:

  • Fully automated draft creation and publication
  • Clear, maintainable code structure for future scaling
  • Insight into potential time savings (~20 hours per month)
  • A foundation for adding approval workflows and content styling later
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/ Summary

Key Takeaways from the AI Blogging Prototype

This project validates the concept that AI + automation can solve the “empty blog” problem for businesses with limited time to produce fresh content. It shows that even a basic setup can handle routine posting while leaving room for human edits or approvals.

Main lessons:

  • Start simple: test workflows before scaling AI usage
  • Always plan a human approval step for production use
  • Maintain clean, modular code to adapt to different CMS or front-ends
  • Expect AI output to need formatting rules for consistent quality

Key Numbers:

  • 30-minutes prototype build
  • ~20 hours saved per month (estimated)
  • 0 manual publishing once the flow runs

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