A Surprise Software Breakthrough
In the race to implement AI solutions across industries, many companies have rushed to create flashy applications that ultimately deliver little value. My journey began similarly in 2023—evaluating large language models for industrial manufacturing with projects that, while technically feasible, would have been more show than substance.
The Shifting AI Landscape
Since those early explorations, we've witnessed a remarkable evolution in AI capabilities. Today's models are not only more powerful but also more accessible. The ecosystem has expanded to offer:
Simultaneously, I've been integrating AI into my personal workflow. The results have been transformative—my productivity has increased nearly tenfold, quality has improved, and errors have diminished. During my most productive periods, I can orchestrate multiple AI agents working across full-stack planning, creation, building, and testing processes.
The Unexpected Convergence
February marked a pivotal moment when several factors aligned perfectly:
I timed this chatbot development to coincide with the release of these more capable models. While I expected modest improvements, what we achieved exceeded all expectations.
The Breakthrough Moment
The true breakthrough came during post-delivery experimentation with these new models. I discovered they could comprehend far more than conventional programming languages:
We then implemented a multi-agent approach:
This creates a comprehensive view that connects the machine's actual behavior with what operators experience and documented issues that may contribute to problems. In some scenarios, this system outperforms human experts.
Real-World Impact
The implications for industrial automation are significant. Troubleshooting machine issues typically requires engineers to gather programs, variables, schematics, and other documentation—a time-consuming process when production lines are halted and downtime costs accumulate rapidly.
Our system can compress days of research and problem-solving into seconds, potentially saving companies thousands of dollars per incident. It can quickly identify issues that might otherwise require flying in specialists, only to discover something as simple as a misaligned limit switch.
A Genuine Innovation
What makes this breakthrough legitimate is not just the technical achievement but its timing and scope. The technology enabling this approach likely didn't exist until recently, and we appear to be among the first to deliver this capability to customers.
While many companies claim to offer intelligent assistants using cutting-edge technology, few if any integrate data analysis, documentation, schematics, and programming in a single orchestrated solution that provides a complete picture of technical issues. Most implementations stop short in one area or another.
We released our solution in late February. It was validating to notice that Tesla—typically at the forefront of technological innovation—released an assistant that analyzes current machine values on March 6th. For once, we may have beaten them to market in a specialized but important capability.
In a landscape filled with AI hype and exaggerated claims, it's deeply satisfying to create something that delivers genuine value—a system that wasn't possible before and that solves real problems in ways that matter.