On June 9th and 10th, Dynaimix AI trainer Dan Callahan headed to Escondido, California for a two-day Intro to AI training at the headquarters of Associate Mechanical Contractors. AMC had a full house for both days, and the range of experience in the room made for a dynamic and productive session.
AMC has built its reputation on a collaborative approach to mechanical contracting, treating every project as an opportunity to develop lasting partnerships and deliver engineering solutions that serve all stakeholders over the long term. That same collaborative spirit showed up in how their team engaged with the training.
The session was conducted using ChatGPT as the primary platform, though the room was far from uniform in its starting point. A handful of participants already had a strong grasp of AI concepts and were applying them at a high level across their departments, with some actively using Claude in their day-to-day work. For others, access to ChatGPT had come recently, and most of their experience had been limited to its basic features. That spread in the room created something useful. The participants who were further along brought real examples and raised the level of the conversation, while those newer to the tools brought the kind of honest questions that keep a training grounded in practical reality.
Several strong collaborative use cases emerged from the group over the two days. One that resonated across the room involved ChatGPT’s Projects feature, specifically the ability to create shared project workspaces, invite colleagues, and populate them with source files. For a mechanical contracting firm managing multiple projects and teams, the idea of a structured, AI-accessible workspace where relevant documents and context live together landed as an immediately practical application.
Another use case came out of a smaller group working through a field challenge that many contractors will recognize. Handwritten notes from the field and rough hand drawings are a persistent documentation headache, hard to read, harder to share, and often inconsistent in how they get interpreted back in the office. The group found that ChatGPT handled transcription and cleanup of handwritten field notes and drawings with impressive results, turning rough inputs into clean, usable documentation in a fraction of the time it would take manually. It was one of those moments in a training where a use case clicks because it connects directly to a real problem the team already has.
The capstone exercise on day two introduced participants to ChatGPT’s newest agentic capabilities. Each person in the training built their own Chief of Staff agent, a workspace agent configured to send a personalized morning briefing that pulls together emails, calendar activity, and Teams chats into a single daily summary. The feature is brand new and still being refined, but the exercise gave every participant a working first version of something genuinely useful and a clear picture of where agentic AI is headed. Getting hands on a new capability before it becomes standard practice is exactly the kind of early advantage that training is designed to create.
AMC came into the two days with a team that was ready to engage, and they left with practical tools, a set of use cases built around their own work, and a clearer sense of how AI fits into the way their firm operates. It was a strong two days with a sharp group, and a good example of what happens when a mechanical contracting firm decides to invest in its people rather than wait for AI to figure itself out on its own.
