Proof of Concept Done Right: A Java Developer’s Guide
Why disciplined PoCs matter, how to scope them, and what Java teams should expect from vendors.
When I talk to teams about Proof of Concept (PoC) work, I always stress one thing: it’s not about building the final system. It’s about asking a sharp question and getting a trustworthy answer.
I’ve been through enough PoCs in my career—some that gave management confidence to invest, others that showed us early what not to do. The magic is in the discipline. A PoC is the developer’s way of telling the organization: “Before we bet the farm, let’s test this idea.”
What a PoC is (and isn’t)
It helps to clarify the difference between a PoC and other kinds of early software. A PoC is not a minimal viable product, it is not a prototype with end-user polish, and it is not a shadow production system waiting to be launched. Instead, a PoC is a limited, time-boxed experiment. It is a focused test of feasibility, risk, or value. And most importantly, it is a decision-making tool for stakeholders.
I often describe it as a flashlight. It won’t illuminate the entire road ahead, but it will show you whether you are even facing the right direction.
Suitable scope: keeping it sharp
The biggest mistake I see developers make—including myself years ago—is over-engineering PoCs. You don’t need authentication flows, reactive user interfaces, and a fully fledged CI/CD pipeline just to prove that Quarkus can connect to PostgreSQL with Dev Services.
A good PoC keeps its scope limited to a single question. For example, you might want to know if Quarkus can start in under 50 milliseconds as a native binary on edge devices. Or you might be concerned about integration risks and want to verify if LangChain4j can connect to a locally hosted model through Ollama while still respecting enterprise security policies. Sometimes the focus is on raw performance: can Hibernate Panache queries stay under thirty milliseconds when running with ten thousand concurrent requests? In other cases, the scope might be about compliance, such as checking whether Quarkus’s Micrometer and Prometheus metrics pipeline satisfies internal observability requirements.
What all these examples have in common is that they leave out anything unnecessary. There are no roadmaps, no polished front-ends, and no extras. Just enough code and measurement to answer the one question.
Different angles of PoCs
Not every PoC is about technical feasibility. Some of the most impactful ones explore other dimensions.
A technical PoC is the most familiar. It validates whether a framework, runtime, or library behaves as expected. For instance, you might compile Quarkus into a native image with GraalVM to see how small the memory footprint can be.
An architectural PoC looks at broader patterns. Here you might test whether an event-driven design with Kafka simplifies your system, or whether a polyglot persistence strategy is manageable. Quarkus helps in this space because Dev Services allow you to spin up Kafka, RabbitMQ, or databases in containers without effort, but the real test is whether the architecture still makes sense in production.
Some PoCs are about process. These are less about code and more about flow. For example, you could challenge your team to see whether they can ship a Quarkus microservice from commit to Podman in under an hour using GitHub Actions. The code may be trivial, but the learning is about automation and developer experience.
Others are business-driven. These check whether a feature aligns with customer needs. A simple chatbot powered by Quarkus and LangChain4j that answers FAQ-style queries from internal documents can show stakeholders whether conversational AI is even relevant.
Finally, there are theoretical PoCs. These don’t just validate a piece of code but test a bigger assumption, such as whether contextual retrieval improves user satisfaction. That kind of PoC may combine software experiments with surveys or metrics.
The point is that PoCs can be technical, architectural, process-oriented, business-focused, or theoretical. Each angle has different stakeholders. Architects tend to care about performance and compliance. Business sponsors want to know whether value is delivered. Developers focus on integration and experience. A strong PoC makes sure the right people get the right answers.
A simple PoC framework
Over time, I’ve found that a simple structure helps keep PoCs disciplined. I think of it as a five-step framework.
The first step is to define the question. Write it down as a single sentence, ideally in plain language. For example: Can Quarkus Dev Services start PostgreSQL automatically on developer laptops without manual setup?
The second step is to agree on success criteria. These criteria must be measurable. In the previous example, the criteria might be that the database must be available within five seconds, no manual commands should be required, and the connection should work with a Panache repository.
The third step is to time-box the effort. A PoC should last days or weeks, not months. If the work drags on, you are building an MVP rather than a PoC.
The fourth step is to strip it down. Remove every feature that is not directly linked to the question. That means no authentication, no extra user interface, and no “while we’re at it” tasks.
The fifth step is to document findings rather than polishing the code. A PoC repository does not need extensive test coverage. What it needs are clear notes about what worked, what failed, what assumptions you made, and what the next step should be.
Run this cycle, and then stop. Resist the temptation to let a PoC morph into a pilot product without conscious decision-making.
Best practices for running PoCs
Some habits make the difference between useful PoCs and wasted ones. One is to treat failure as a success. If a PoC shows that something will not work, that is still valuable. It saves the organization from betting on the wrong technology.
Another is to communicate early with stakeholders. Everyone should understand why you are testing, what the boundaries are, and when you plan to stop. This prevents scope creep and misplaced expectations.
It also helps to archive PoCs properly. Keep them in a separate repository or folder so lessons are preserved but so that unfinished code does not contaminate production projects.
Finally, always be mindful of hidden complexity. A PoC that makes a single REST call might prove integration is possible, but in production that call will need retries, resilience, and observability. Those gaps should be noted explicitly so nobody mistakes a working PoC for a finished system.
The role of software vendors
Enterprises rarely run PoCs in isolation. Vendors—whether Red Hat, IBM, or any other—are often involved. Their participation can be helpful, but it needs to be approached with care.
Vendors are at their best when they provide sample code and quickstarts, offer expert support to accelerate experiments, and share reference architectures tested in real deployments. They can also clarify licensing, support, and production-readiness boundaries that might otherwise cause surprises later.
But there are risks too. Vendors often provide polished demos that may not reflect your reality. Always adapt vendor samples to your own stack. They may also try to stretch PoCs into pilots without clear agreements. Be clear about scope and ownership. And watch out for lock-in pressure. A PoC should test flexibility, not only how well you fit into one vendor’s ecosystem.
I once worked on a project where the vendor provided a Quarkus quickstart for PostgreSQL. It was slick and ran in minutes, but our real database was Oracle with special security requirements. The PoC only became meaningful once we tested with those constraints.
PoCs as career accelerators
On a personal note, PoCs have often been where I learned the most and where I had the chance to show leadership. Explaining to a manager why Quarkus hot reload changes developer workflow is not just a technical pitch—it is an act of translation. PoCs force you to step back from perfect code and focus on the right questions.
That shift in mindset is powerful. It helps you think like an architect, a consultant, and even a business strategist. It is also an essential skill for senior developers who want to grow into broader roles.
Final thought: A PoC is not throwaway code. It is a disciplined experiment. With Java and Quarkus, you can run them fast, small, and focused. The real value comes from asking the right question, defining success clearly, and engaging both vendors and stakeholders with eyes wide open.