_beta

HartmannSoftware Group

Technology Changes. The Challenge Is Knowing What to Do With It.

Since 2002, Hartmann Software Group has worked at the intersection of technology, business and education. During that time, we've watched programming languages rise and fall, software-development practices change, cloud computing transform infrastructure, data become central to nearly every organization, and artificial intelligence move from a specialized research field into tools that millions of people can use every day.

The technology changes constantly. Many of the underlying business problems don't.

Organizations still struggle to decide which technologies are worth adopting, how to introduce them without creating unnecessary complexity, how to train people effectively, and how to translate a promising technology into something that actually improves the way people work.

Those are the subjects that interest us.

More Than Learning Software

Hartmann Software Group has spent more than two decades teaching technology to professionals in industries ranging from banking and insurance to manufacturing, construction, transportation and government. We've taught programmers, database professionals, analysts, managers and people whose jobs increasingly require them to understand technology even though they would never describe themselves as technologists.

That experience has taught us something important: knowing how to operate software is only part of becoming good at using technology.

A person can learn the syntax of SQL without understanding what question should be asked of the data. Someone can learn Excel functions without understanding whether the underlying business assumptions make sense. A manager can learn the terminology of ITIL without understanding why a particular workflow repeatedly fails. And today, almost anyone can ask an artificial-intelligence system to generate an answer without knowing whether the answer is useful, appropriate or even correct.

The most valuable training happens when the technology becomes connected to the problem someone is actually trying to solve.

That's why our best classroom discussions often begin when someone stops following the course material for a moment and says, “Here's what we're actually dealing with at work.”

Now we're getting somewhere.

Technology in the Real World

Technology rarely fails because someone forgot where a button was located.

Projects fail because expectations were unrealistic. Systems are built without understanding the people who will use them. Business and technology teams solve different versions of the same problem. Processes accumulate unnecessary steps because nobody asks why those steps exist. Organizations buy sophisticated tools and then reproduce the same inefficient practices they had before.

Artificial intelligence doesn't eliminate these problems. In some cases, it magnifies them.

AI can generate code, analyze data, summarize documents, create presentations and recommend solutions at extraordinary speed. That makes technological capability increasingly accessible, but it also places greater responsibility on the person asking the question.

A machine can produce an answer.

Someone still has to determine whether it's the right answer to the right problem.

What Experience Teaches

After more than two decades in technology and technical education, we're increasingly interested in the lessons that don't fit neatly into a course outline.

Why do technically impressive projects fail?

Why do organizations continue using inefficient processes when everyone involved knows they're inefficient?

What separates someone who understands a technology from someone who merely knows how to operate it?

How should artificial intelligence change the way we educate people?

When should an organization automate something, and when would automation simply make a bad process run faster?

What happens when an experienced employee knows something important that has never been documented?

These aren't questions with answers that fit neatly on a certification exam. They're questions answered gradually through experience—by building things, teaching people, watching projects succeed, watching others fail and paying attention to why.

Training Built Around the Client

Hartmann Software Group continues to provide professional technology training, but our most useful engagements increasingly extend beyond simply delivering a standardized class.

Organizations have their own terminology, workflows, systems and problems. When appropriate, we incorporate those realities directly into the training.

A discussion about IT service management can use the client's actual incident or request workflow. A data class can address the kinds of information employees work with every day. An AI workshop can explore tasks participants actually perform rather than demonstrating artificial examples that will be forgotten as soon as the class ends.

The objective isn't merely to finish the course material.

It's for someone to return to work understanding something they didn't understand before—and knowing what to do with it.

Why We Write

This Notems site is where Hartmann Software Group shares some of what we've learned along the way.

We'll write about artificial intelligence, software development, data, technology education, business processes, project failures, changing careers and the relationship between people and the increasingly powerful tools they use.

Some articles may come from experiences in the classroom. Others may examine an industry development, challenge conventional technology wisdom or revisit lessons learned from decades of building and teaching software.

We don't expect every reader to agree with every conclusion.

But after more than twenty years working with technology, we've accumulated observations worth examining, experiences worth sharing and occasionally a few assumptions worth challenging.

Technology will continue changing.

Understanding what to do with it remains the harder problem.