Stop Using LLMs First! This AI Mistake Is Costing You

Most AI projects fail before they even start, and it’s not because of the model. Teams rush into LLMs, burn through budget, and still don’t get results. The real problem? They’re solving the wrong thing first.

Vit Lyoshin and Max Vermeir (VP of AI Strategy at ABBYY) break down one of the most common mistakes in AI and product development: starting with large language models instead of understanding your data and processes.

The conversation highlights why structured data, repetitive workflows, and clear ROI metrics should come before any AI implementation. It also explores how companies are struggling to define value and pricing in an AI-driven world.

For product managers, founders, and engineers, this is a practical framework for building AI solutions that actually deliver business impact.

KEY TAKEAWAYS
* Start with data: clean, structured inputs outperform raw LLM usage
* Focus on repetitive processes to unlock scalable AI workflows
* Define ROI early - if you can’t measure value, don’t build it
* Avoid burning tokens on problems that simpler tech can solve
* AI success comes from process clarity, not model complexity

🔗 Full episode: https://youtu.be/n9yEdajBnNQ

Connect with
* Website: https://www.abbyy.com/
* LinkedIn: https://www.linkedin.com/in/maximevermeir/

Connect with Vit
* Substuck: https://anhourofinnovation.substack.com/
* LinkedIn: https://www.linkedin.com/in/vit-lyoshin/
* X: https://x.com/vitlyoshin

To support our work, please check out our sponsors and get discounts: https://www.anhourofinnovation.com/sponsors/

For inquiries about sponsoring An Hour of Innovation, email iris@anhourofinnovation.com