No AI compromise: How were shipping faster with AI

At Vemi, we've seen how AI can accelerate delivery, but only when combined with solid engineering practices.

The classic trade-off

“Time, Quality, Cost. Pick two”

How many times have we had that difficult conversation? But what if this equation is starting to shift?

As engineering leaders, our mission has always been to optimise for efficiency without sacrificing quality. We’ve dedicated our efforts to removing constraints in complex socio-technical systems, introducing dev-ops practices, refining agile processes, re-organising teams… all in pursuit of incremental gains on efficiency.

Lately, AI has been positioned as the silver bullet that will remove these constraints entirely. The narrative set high expectations, but the reality, enforced by the hype around 'vibe coding', has been underwhelming for many. So much so, that the AI hype cycle now seems to already be in the disillusionment stage and AI is being written off by many engineering leaders.

Dismissing AI code generation could be a big mistake.

At Vemi, we're already realising the potential of AI, helping us deliver faster without compromising on quality. We recently launched the first version of our app: a mobile frontend supported by an event driven backend microservice architecture, built to our standards and aligned with engineering best practices. The pace at which we achieved this would simply have been impossible without AI.

I believe the path out of the disillusionment phase of this hype cycle is grounded in the very same engineering best practices that experienced leaders have relied on for years. We've seen first hand, that when AI is supported by effective process, clear standards and experienced engineers, it not only accelerates delivery, but can shift team dynamics and even reshape business strategy.

That’s why, more than ever, establishing solid engineering practices isn’t just important, it’s essential. At Vemi, AI has not replaced our need for this structure, it's amplified it. We’ve been able to achieve the same outcomes in less time because of the way we break down work, write specifications, follow established architectural patterns, review code, and invest in developer experience.

But we're still at the start of the journey. We have not automated everything and we're still learning, still discovering how we should use these emerging tools in real world scenarios. The gains aren't hype, and we're not vibe coding, we're a very small team, delivering faster without compromising on quality - we know it can be done.

What's next..

In the coming weeks, I’ll be sharing more posts that dive into specific practices, tools, and lessons we've picked up along the way. If there are particular challenges or topics you'd like to see explored, I’d love to hear suggestions.