From Prompt to Production: How CIOs Can Scale AI-Built Tools with Confidence

AI may be generating code, interfaces, and even product ideas, but it’s CIOs who are accountable for turning all of that into something tangible, reliable, and scalable. So, how do you bridge the gap between AI’s potential and the realities of delivery?

That’s the question we explored with several members of Slingshot. What emerged was a candid and practical conversation about what works, what doesn’t, and what CIOs need to consider as they adopt AI-driven development at scale. Here’s what we learned.

The Real Draw: Speed, Scale, and a Little Bit of Magic

AI-driven development has generated considerable excitement. For many, these tools offer more than just efficiency; they offer empowerment.

Steve Anderson, a Principal Developer at Slingshot, shared how tools like Cursor and GPT-based copilots have fundamentally changed the way he works: “Just sitting down and saying ‘walk me through this new code base so I can orient myself’ was incredibly helpful.”

Doug Compton, also one of Slingshot’s Principal Developers, put it even more bluntly: “Just being able to tell somebody else what to do and have them do it, that’s exciting.”

And for Chris Howard, Slingshot’s CIO, the upside goes beyond code: “It’s like having a brilliant friend sitting there with you. I feel like the result is more sophisticated, better thought out, and I can do it faster.”

At its best, AI supercharges productivity and brings new energy to cross-functional leaders who toggle between strategy, execution, and communication.

These Tools Are Smart, But They Still Need Supervision

Where are we on the maturity curve? Somewhere around “middle school,” said Steve. “They’re more mature than they were… maybe we’re at the middle school level”.

That metaphor resonated throughout the group. These tools are fast and capable, but they’re not autonomous. They require oversight and strong prompts, and still produce hallucinations or errors when left unchecked.

Doug warned, “It’s definitely worth putting into production in your workflow, but it still needs guidance.” In other words, AI is a collaborator, not a replacement. Especially when quality and security matter.

Productivity vs. Precision: What AI Gains and What It Gives Up

One of the most significant benefits of prompt-based tools? Throughput. Developers are moving faster. Non-technical leaders can contribute more directly. Anderson described generating over 10,000 lines of unit test code in under two hours, a task that would typically take days without the aid of AI.

But it’s not all upside. These tools make development quicker; “It’s probably 60% faster,” said Doug, “but the quality of output in the end has gotten a little bit worse, requiring the developer to do some cleanup.”

That trade-off is especially relevant for CIOs, who are responsible for ensuring velocity doesn’t compromise stability. Which leads to a more challenging question: are these tools production-grade?

Tool Sprawl Is the New Tech Debt

One of the most pressing concerns voiced by the group was the sheer volume of tools and the rapid pace of change in the landscape.

“You don’t know exactly what tools you should be using,” said Doug. “Right now, the hot thing is Cursor, but I’d be surprised if Cloud Code or something else replaces it within six months”.

Tool churn can lead to fragmentation, lost time, and difficulty training teams at scale. For CIOs, it introduces a new kind of tech debt: short-term convenience that may not hold up in long-term architecture.

The takeaway? Select your stack intentionally and revisit it frequently.

The Lie of “Anyone Can Build Software Now”

Many AI platforms promote a “no-code, anyone can build” promise. The reality? It’s not quite that simple. As Doug put it simply: “Software is hard.”

Even with the right prompts, developing a real product still requires domain knowledge, architecture skills, UX empathy, and security awareness. The group described AI-generated apps that failed basic authentication, stored passwords in plain text, or were unable to integrate backend services without human intervention.

In other words, while AI can help your team accomplish more, it still requires human oversight to produce a quality product. 

Surprising Upsides (That No One Talks About)

Beyond speed and ideation, AI tools are introducing some subtle behavioral shifts. One that stood out? Fewer Google searches.

“I rarely Google anything anymore,” said Chris. “It kind of happened overnight; I realized I don’t search like I used to”.

Steve shared how these tools enable him to multitask more fluidly: “While I’m having it generate stuff, I flip over and do Slack messages or admin work. It doesn’t interrupt my flow.”

In this sense, AI isn’t just helping us write code; it’s changing how we work, prioritize, and collaborate.

What CIOs Must Get Right to Scale with Confidence

So what should CIOs do with all of this? How do they navigate risk, train teams, and choose tools in a world that’s moving faster than their procurement cycles?

Chris Howard offered this: “The CIO’s job is carving out time and space, and providing resources to make sure their team’s ready”.

This process involves creating space for training, encouraging experimentation, and investing in internal champions who are proficient in prompt engineering and architectural best practices.

Doug Compton emphasized foresight: “They need to know where it’s good right now, so they can guess where it’s going. I’m fine if they don’t make a move today, but they’ve got to be ready to move soon.”

Final Word: Curiosity is a Competitive Advantage

AI will not replace developers. But CIOs who fail to prepare for AI, who don’t experiment, don’t train, and don’t plan, might find themselves outpaced by those who do.

Yes, these tools are still in their early stages. Yes, they require oversight. But they also unlock new possibilities for speed, productivity, and innovation.

The teams that win won’t be the ones with the most automation. They’ll be the ones with the most adaptation.

So here’s the challenge: Where could AI shave a week off your roadmap? What could it free up your team to do better? And how will you scale those wins, safely?

The next move is yours.

Slingshot