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We talked with Vinicius Goncalves, Software Engineer, about the moments and mistakes that shaped his growth. Vinicius walks us through the project that gave him a front-row seat to the full product lifecycle, the bug that taught him to slow down before making high-impact decisions under pressure, and how his approach to learning new technologies has shifted now that AI is part of the toolkit.
Knowing you’ve grown
For Vinicius, the clearest sign of progress wasn’t a promotion or a performance review. It was becoming the person teammates started turning to. “I realized my growth when I became a reference within my team for multiple topics, not just development,” he says. When colleagues start pulling you into strategic conversations rather than just technical ones, that’s usually a sign you’ve leveled up.
The project that did the most to shape his career was building a credit-like solution for investors from the ground up. It was a crash course in how software actually gets built. “I experienced the full product lifecycle, from an initial idea to an MVP, and eventually to a robust platform,” he explains, and that exposure gave him a feel for product thinking, architecture, and scalability all at once, rather than just one slice of the job.
What the mistakes taught him
Ask Vinicius about the hardest bug he’s faced, and he won’t point to a specific one. “I’ve learned that the toughest bug is always the next one,” he says. His method is consistent: try to work through it independently first, and only then bring in help. “There is no issue in asking for help, as long as you have made a genuine effort,” he adds, and he’s found pair programming to be one of the most effective ways through genuinely thorny problems.
Not every lesson came from a bug, though. One mistake still sticks with him: blocking IP addresses to stop what looked like a DDoS attack, only to accidentally lock out legitimate customers in the process. The cause was simple but costly, query filters that hadn’t been validated carefully enough under time pressure. “The key lesson was that decisions made under pressure can be unreliable,” he says. Since then, he treats high-impact actions differently, making a point to validate them with peers or a team lead whenever he can.
If there’s one skill that moved the needle on his career and wasn’t strictly technical, it’s troubleshooting. Not debugging in the narrow sense, but something broader. “It involves understanding the full context, including system behavior and sometimes even user behavior,” he says, and that wider lens has changed how he approaches problems across the board.
Interviewing, hiring, and what actually matters
Vinicius’s take on interview prep comes down to one thing: knowing your own experience well enough to talk about it plainly. “Confidence in your own experience is key. When you truly understand what you are talking about, it naturally reduces nervousness,” he says, adding that honesty matters just as much, since trying to bluff your way through rarely works.
Reflecting on his own hiring experience at Dev.Pro, he points to two things that stood out as green flags: a clear explanation of the role and what was expected of him, and a hiring process that felt structured and transparent from start to finish.
Learning in the age of AI
The way Vinicius picks up new skills has changed a lot over the years. Early on, it was mostly trial and error. “Early in my career, I relied heavily on trial and error and long learning curves, often without a clear direction,” he recalls. Experience taught him to filter signals from noise, to focus on what’s actually useful rather than chasing theory for its own sake.
These days, AI plays a real role in how he learns. “AI has significantly accelerated my learning process. I can generate structured study plans, simulate real scenarios, and quickly clarify doubts,” he says, though he’s careful not to rely on it alone, still leaning on video courses and material from experienced professionals to round things out. His current approach, as he puts it, is a balance of speed, depth, and practical validation.
Time estimation is another area that’s transformed for him. Where he used to underestimate tasks simply because he hadn’t yet encountered all the unknowns, he now builds in room for them. “I include time for research, edge cases, and validation when planning tasks,” he says, which has made his delivery far more predictable and his communication with the team a lot clearer.
Looking back at where he started, his advice is this: don’t wait to feel ready. “You will never feel one hundred percent prepared, and that is normal,” he says. Most of the real learning, in his experience, happens by doing.
These days, his growth strategy is fairly deliberate, he gravitates toward online courses and cloud certifications, picking a specific skill gap and then validating it through certification or hands-on application.
The AI prompts he swears by
Asked for his most useful trick, Vinicius didn’t hesitate, it’s a prompt pattern he leans on constantly for code review:
“Act as a senior software engineer. Analyze the following code and context. Identify potential bugs, performance issues, edge cases, and scalability risks. Suggest improvements following best practices and explain the reasoning behind each recommendation. If applicable, propose a cleaner architecture.”
For debugging trickier issues, he uses a similar approach to generate and rank hypotheses:
“Given this behavior and logs, list possible root causes ranked by likelihood and suggest how to validate each one.”
One caveat he’s careful to flag: when logs or sensitive data are involved, he sticks strictly to enterprise-approved AI tools, to stay on the right side of IP and security policy. The payoff, he says, is real, this approach speeds up delivery while also pushing the quality of his decisions to a higher level, since he’s not just solving problems but validating them as he goes.
Closing Thought
What comes through clearly in this conversation is that Vinicius’s growth was built on a DDoS-style mistake that reshaped how he handles pressure, a willingness to ask for help only after genuinely trying, and a constant recalibration of how he learns. As he puts it, you never feel one hundred percent prepared, and that’s normal. The real work happens by doing, by being honest about what you don’t know, and by treating every tough bug as practice for the next one.