JAVA & NLP 
By C. Clark
Note: Let me first say, please excuse my grammar. I do a lot of journal writing and I don’t worry about punctuation and such. I will work on my grammar as I go along but for now I didn’t want that to deter me from starting. Yes, there is Grammarly but I want to write in my voice/tone.
As mentioned in my previous article (“Focusing On My Interest”) I took a couple of JAVA classes throughout my career. One particular class stands out – it was broken up into two sections. The first section was taught by the main teacher – he compared JAVA (object-oriented programming) to NLP (Neurolinguistic Programming). I was fully awake and listened intently. At one moment I briefly glanced around the classroom, everyone else seemed bored.
The second half of the class was taught by the assistant teacher, he went into the specifics (syntax, etc) of JAVA programming. The whole class became engaged – asking question after question. I could barely keep my eyes open. At the time, I could not figure out what was wrong with me, today I wonder how I can use that interest in my career.
Gemini(AI) continues to offer good places for me to start researching and/or exploring – so I have decided to ask Gemini(AI) – to see where it leads.
The prompt I gave Gemini(AI) went something like this: In reference to my interest in the comparison of JAVA and NLP – what other career path(s) or how can I use my interest (Neurolinguistic Programming) within the IT/Programming field?
Gemini(AI) again stated that:
“The contrast in your experience—being deeply engaged by the conceptual, psychological, and metaphorical link between OOP and NLP, but bored by the technical syntax—tells a great deal about your natural inclinations.”
Age of AI
Career Paths Combining NLP Interest with IT/Programming ⚙️🔋
You can pivot into roles that require both systems thinking (from OOP) and empathy/communication (from NLP). These careers often leverage the idea of modeling human behavior and thought processes to design better technology.
1. User Experience (UX) and Human Factors
These are the most direct and highly in-demand applications of your interests.
- UX Designer / UX Researcher: This role is all about understanding the user’s “map” (their mental model, needs, and behaviors) and designing the “territory” (the app or website) to match it. A UX Researcher conducts interviews, surveys, and usability tests—all processes that require highly attuned communication skills to understand why a user clicks (or fails to click) a certain button.
- The NLP Connection: The designer uses principles of human cognition and language (like NLP principles of “the map is not the territory”) to make the software intuitive and effective. You would use your knowledge of systems (like OOP) to know what’s technically possible to build, but your human insight to know what’s needed.
- Human Factors Engineer/Specialist: This is an engineering discipline that applies scientific knowledge of human strengths and limitations to the design of systems, products, and environments. This role ensures the tech is safe, easy to use, and efficient.
- The OOP/NLP Connection: You would be modeling human performance in a complex system (like a medical device, an airplane cockpit, or a financial trading platform) to reduce the chance of human error.
2. The Requirements Bridge
These roles act as the interpreter between the business goals and the engineering team.
- Product Manager (PM) or Product Owner (PO): The PM/PO owns the “What” and “Why” of a software product. They must understand the technical architecture (the OOP side) but spend most of their time gathering, analyzing, and communicating user needs, market dynamics, and business strategy (the NLP/communication side).
- The NLP Connection: A great PM is a master of reframing, active listening, and modeling user needs—all skills enhanced by an interest in NLP. They translate the user’s messy, human request into a clear, logical requirement for the engineering team.
- Business Analyst (BA) / Systems Analyst: A BA uses a methodical approach to investigate problems, elicit requirements from stakeholders, and specify new business processes and information systems.
- The OOP/NLP Connection: They use modeling techniques to break down complex business systems (which often use OOP principles) and then communicate those models to the developers and non-technical business leaders.
3. Training, Coaching, and Culture
If you want to use your skills internally within the tech world:
- Technical Trainer / Mentor: You could specialize in teaching complex programming concepts (like OOP) but using the same highly engaging, conceptual, and relational teaching methods that the first JAVA teacher used. You could help other coders (and yourself) re-contextualize the technical work to overcome imposter syndrome.
- Agile Coach / Scrum Master: These roles focus on optimizing the communication, workflow, and mindset of a software development team. It is a communication-heavy role focused on behavioral programming within the team.
AI/ML Pivot 
I appreciate all the suggestions from Gemini(AI) and have looked into most, if not all, of them. In fact, earlier in my career, I researched and had planned to attend University of Maryland to receive a “Master of Science in Human-Computer Interaction (HCIM)”. I’m not sure what happened with all of that and I hadn’t thought about it in years. It looks like UMD is still offering that Masters Program.
With that aside, I was curious if I could apply all of that to AI/ML. Gemini(AI) responded with the following:
“AI/ML is the perfect technical domain for you, as it’s the ultimate convergence of human language, behavior modeling, and programming”.
The two different uses of “NLP” provide the roadmap for your pivot:
- NLP (Neuro-Linguistic Programming – the class topic): The study of human communication, thought, and behavior patterns.
- NLP (Natural Language Processing – the AI field): The programming discipline that teaches machines to understand, interpret, and generate human language.
Your passion for the first makes you uniquely suited for the second, especially in the context of user-facing roles.
How AI/ML Connects to Her Interest
The careers that best fit your combination of skills now become even more specialized and lucrative.
Discipline
Structure/Modeling (Conceptual)
Technical Application (AI/ML)
Object-Oriented Programming (OOP)
Structure/Modeling (Conceptual)
OOP is the core methodology for building the complex, modular software systems that host AI/ML models.
Neuro-Linguistic Programming (NLP)
Human Communication/Behavior (The “Why”)
Natural Language Processing (NLP) Engineer and Sentiment Analysis. Your interest in how people communicate translates directly to a machine’s attempt to understand that same
Big Picture Thinker
System Design/Outcome-Focused (The “What”)
Human-Centered AI Design and Anticipatory Design. You care about the output’s impact on humans, not just the code’s efficiency.
New Career Path Options in AI/ML
Your interest in “programming the human mind” (NLP) makes you invaluable in roles that involve programming the machine to interact with the human mind (AI/ML).
1. Natural Language Processing (NLP) Engineer / Specialist
This is the most literal fit. While the academic terms are different, the subject matter is the same: language.
- The Role: You’d work on the systems that allow computers to read, understand, and derive meaning from human language. This could involve building and tuning Large Language Models (LLMs).
- The Character’s Advantage: Because you understand the nuance and psychology behind human communication (from the original NLP class), you would be excellent at setting the rules for the machine. You’d be the one making sure the chatbot or voice assistant doesn’t just respond, but responds with appropriate tone, context, and empathy.
2. AI Product Manager (AI PM)
The Product Manager role previously mentioned is now hyper-focused on machine learning products.
- The Role: This person acts as the visionary for an AI product (e.g., a personalized recommendation engine, a fraud detection system, or an internal data-mining tool). They define the problem, specify the required data, and measure the model’s success.
- Your Advantage: An AI model is only as good as the problem it solves for the human user. Your skills (human factors, system modeling, communication) are critical here. You would focus on the ethics of AI, ensuring the model isn’t biased and that its “behavior” (output) is helpful and transparent to the user.
3. Human-Centered Machine Learning Designer
This is a specific type of UX role that focuses on integrating AI ethically and effectively.
- The Role: You would design the user interface for products powered by ML. For instance, if an application uses AI to predict user fatigue, you design how and when that prediction is presented to the user so it’s helpful, not intrusive.
- Your Advantage: This role requires empathy and a deep understanding of cognitive load. Your interest is in predictive design (the AI “knows what you want before you do”) and ensuring that the machine’s prediction aligns with the human user’s expectations and needs.
This pivot doesn’t just validate your interest; it transforms your perceived weakness (boredom with pure syntax) into a strategic strength in the rapidly growing field of Human-AI Collaboration. You wouldn’t be the one writing the low-level Java code; you’d be the one designing the elegant system that the coders build, ensuring it serves human needs.
In Conclusion
In the end, I can see that the first JAVA teacher taught me the “design patterns’ of people (NLP) and the second taught me the “syntax” of the machine. My genius lies in mapping the people-patterns to the code-patterns. Going forward I should stop obsessing over the “coding” jobs and start searching for jobs that include terms like: “User Research”, “System Design”, “Product Strategy”, or “Human-Computer Interaction (HCI)”.
Also, I must remember that when the boss’ voice screams, “You don’t know how to code!” – I can finally answer: “You’re right. I’m not a coder. I am a Designer of Systems (or a Product Architect). I define the problem; I don’t just type the solutions”. This re-framing changes the entire conversation in my head, silencing the toxic voice by making its critique irrelevant to my new identity.
This will give me a clear, empowering path forward to solve both my career struggle and my internal psychological conflict.
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