Satya Nadella (Microsoft CEO) recently made remarks about AI agents that sparked widespread discussion around the future of software-as-a-service and human–AI collaboration as a whole. Salesforce CEO Marc Benioff projected that agentic AI could drive a 30% productivity lift for his engineering team in 2025. These statements underscore a potential seismic shift in software, with AI agents poised to play a major role in industrial applications. Gartner predicts that Large Language Models (LLMs) will become the preferred interface to enterprise data. Consulting firms, such as Accenture, have announced specialized “AI refinery” solutions for industrial sectors, signaling their commitment to building out agent-based workforces. The question is: Is all the buzz around AI agents simply marketing hype, or is there real value to be gained by empowering humans with AI agents in thermal processing and related heat treatment industries?
The public release of ChatGPT (GPT-3.5) in November 2022 introduced Large Language Models to a global audience and reached 100 million users within just two months — a record-breaking adoption rate. Initially, these models appeared nearly magical, often producing convincing responses. However, they struggled with specialized or technical questions, leading to issues with accuracy and hallucinations. Despite these early limitations, new iterations and alternative solutions — both closed- and open-source — have driven improvements in accuracy. The latest top models include OpenAI o1, Deepseek-r1, Gemini 2.0, Claude 3.5, Grok 2.0, and Llama 3.1.
