When Engineers Build Their Own Tools: Lessons from the VIKTOR AI Builder Beta

Over the last few months, I had the opportunity to explore the VIKTOR AI Builder through its beta program. While it positions itself in the no-code/low-code space, I wasn’t interested in buzzwords. I was exploring a deeper question:

What happens when engineers are given access to tools to move fast? Whilst capturing critical know-how before they retire or walk out the door, cutting development cycles by 10x, and breaking free from endless handovers and bottlenecks?

It started, honestly, with a bit of envy and curiosity.

I had just seen a case study from McDermott on how they built their ReCo Tool using VIKTOR, an internal app that spots errors in P&IDs and helps engineers optimize workflows.

My first thought: This is exactly the kind of tool we could use.

My second: But good luck getting that idea through the usual layers.

So I stopped waiting. I decided to test it myself.

I come from a mechanical engineering background, but I’ve spent years bridging the gap between field expertise and modern tools. Instead of just clicking through the interface, I pushed the AI Builder with structured prompts and ROI framing, trying to see how far I could go without writing a full spec or involving a dev team.

Beyond Speed: Building for Flow

In one case, I rebuilt a pump sizing calculator, an internal tool I’d seen take two developer days, into a working app in under 20 minutes. Less than 100 lines of logic. No infrastructure setup needed.

Figure: Screenshot of the pump sizing app built in under 20 minutes using VIKTOR’s AI Builder. It includes real-time performance analysis charts and exportable engineering-grade reports.

That’s not a scientific benchmark, but it was a meaningful signal: when engineers can build directly, cycle time drops dramatically.

The experience reframed how I think about internal tools. It’s not just about faster development. It’s about removing friction so engineers can stay in flow and focus on solving real problems, not chasing support.

Where Prompt Engineering Meets Process Engineering

To accelerate results, I combined the AI Builder with prompt-based logic generation (using GPT). This allowed me to define edge cases, iterate logic structures, and reduce development cycles even further.

The impact wasn’t in automation for its own sake, but in how it augmented domain knowledge. When engineers can test assumptions quickly, with structure and support, they build better tools.

This combination worked because of three factors:

• VIKTOR’s visual interface handles deployment, security, and structure.
• Engineering expertise defines the logic and parameters.
• LLMs reduce iteration drag and help engineers stay focused on solving, not coding.

Efficiency Through Enablement

This opened up a new model:

🌟 Pair young, tech-savvy engineers with senior experts.

🌟 Turn critical Excel tools into internal apps.

🌟 Capture engineering knowledge before it walks out the door.

🌟 Enable small teams to collaborate directly on domain-specific apps.

In my experience, this led to more than just speed. It created ownership. Engineers went from proposing improvements to implementing them.

Trade-Offs and Considerations

No tool is perfect, and VIKTOR is no exception. While the AI Builder removes many traditional bottlenecks, it still benefits from Python familiarity, especially for more advanced apps.

Integration into legacy systems may require support from IT, and teams working with massive datasets or strict enterprise governance might need to layer in additional capabilities. There are many use cases in engineering where a system, platform, or service, such as Autodesk Construction Cloud (ACC), where a user cannot connect it by themselves, and VIKTOR is working on improving this to allow for more of these complex cases to be automated by anyone; however, there will always be edge cases.

That said, VIKTOR shines when used for fast iteration, rapid internal tooling, and empowering engineers who understand the problem space deeply. Together with their internal consultants, you can quickly ideate and build the tools that would otherwise take weeks or months to complete.

Amplifying Engineering Teams

We don’t need to wait for external approvals or funnel every good idea into a ticketing system.

Sometimes, the best tools come from the people who understand the problem best, if we give them the scaffolding to build.

This isn’t about bypassing IT or replacing developers. It’s about enabling bottom-up innovation. VIKTOR provides structure and governance out of the box: user access, versioning, cloud deployment, so technical leads can prototype confidently without compromising compliance.

Naturally, some organizations will need to consider how this fits within their broader IT architecture. But in many cases, the trade-off favors early prototyping over early perfection.

In a world where many internal tools never get built because the process is too heavy, tools like VIKTOR shift the economics. They don’t just make building faster. They make starting feasible.

Final Reflection

This wasn’t just about what I built. It’s about what this experience unlocked:

Faster iteration. Less friction. Stronger retention of engineering know-how.

If you’re responsible for digital transformation in an engineering-driven organization, ask yourself:

What are we equipping engineers with to let them innovate and prototype faster than others?

You might find, as I did, that the real ROI isn’t just speed. It’s momentum. And if you’re skeptical? Try building something small.

Explore the VIKTOR Community Edition to get started and see where it takes you.

Gheorghe Iuga is a Senior Project Manager with a mechanical engineering background, now working as an AI consultant focused on bridging industrial know-how and emerging tech. He partners with engineering teams to turn process knowledge into scalable, smart tools.