Robert Soares is a technology leader with over 17 years of experience building enterprise systems and AI-powered products. He previously served as CTO of Business Wire, a Berkshire Hathaway company, where he led the technology that powers press release distribution for Fortune 500 companies worldwide.
His work in AI began with GPT-2 and has continued through the development of several AI products, including FreeAdCopy and DatBot.AI. He's also known as the co-creator of Trism, an award-winning mobile game that was featured at Apple WWDC and nominated for Best Mobile Game in 2008.
Robert writes about artificial intelligence, machine learning, and their practical applications for marketing and sales professionals. His articles focus on explaining complex AI concepts in accessible terms and providing actionable guidance based on real-world experience.
Subject lines, personalization, send time optimization. What delivers results, what's marketing theater, and what experienced email marketers actually think.
An honest assessment of AI content creation based on real workflows and practitioner experiences. What AI excels at, where it fails, and the workflows producing results.
Quick wins for improving AI prompts when you don't have time to become an expert. The minimum changes that make the maximum difference.
Honest breakdown of the four major AI model families. What each one actually does best, verified user experiences, and when to switch between them.
Objets, personnalisation, optimisation de l’heure d’envoi. Ce qui donne des résultats, ce qui relève du théâtre marketing, et ce que pensent vraiment les spécialistes de l’e-mailing.
What AI actually helps with in sales, what it fails at, and how to get started without the vendor BS. Real experiences from sales professionals who've tried these tools.
What tokens really are, why context windows limit AI memory, and why your AI assistant loses track of conversations. A look at the mechanics behind AI forgetting.
No jargon, no hype. Learn what large language models actually do, why next-word prediction creates surprisingly capable AI, and where the technology falls short.
AI hallucinations aren't bugs. They're the inevitable result of how language models work. Understanding the architecture explains why confident wrong answers will always be part of the equation.
A maioria das avaliações de fornecedores de IA ignora o que importa. O que profissionais aprenderam de verdade ao escolher ferramentas, rodar testes reais e evitar as armadilhas que desperdiçam meses de trabalho.