Value starts with understanding
As AI takes over more of the implementation work, the challenge shifts. The critical question becomes less “How quickly can we build it?” and more “Do we understand what we should build – and why?”
That requires more than technology expertise. It requires understanding the business, the industry and the environment in which the solution needs to work. An energy company optimizing grid operations faces very different realities from a public authority improving citizen services or a manufacturer reducing production downtime.
AI can accelerate development in all three. But it can't decide which business problem matters most.
Understand. Specify. Verify.
AI can accelerate every stage of value creation: understanding the problem, specifying what good looks like, implementing a solution and verifying the outcome. Using AI across the whole process gives us the opportunity to increase the total throughput of value, rather than focusing only on coding speed.
At Twoday, we see three disciplines becoming increasingly important as AI becomes part of software engineering:
Understand the problem. Use AI to explore business context, clarify needs and identify constraints and risks.
Specify what good looks like. Use AI to turn business rules, requirements and acceptance criteria into clear direction.
Verify the outcome. Use AI to help check whether the solution works technically, operationally and from a business perspective.
The objective isn't more process. It's less waste and more value.
From development speed to business impact
This is where AI-assisted engineering becomes interesting. Imagine an energy company using AI to accelerate the development of a solution for grid operations. The interesting metric isn't how much code an AI agent produces.
It's whether the solution helps operators make better decisions, reduces manual work or allows the company to use its existing capacity more effectively.
The same principle applies across industries. AI gives us an opportunity to spend less time on implementation and more time understanding the problems worth solving.
And that makes domain expertise more important, not less.
Ask a better question
The organizations that get the most from AI won't necessarily be those producing software the fastest. They'll be the ones combining AI, engineering expertise and deep industry understanding to solve the right problems.
So instead of asking: How much faster can AI help us build software?
Perhaps we should ask: How much faster can AI help us create business value?
About Simo Roikonen
Simo is a Global Principal Architect in Global Digital Engineering at Twoday, with over 20 years of experience designing and building resilient, evolvable software systems. He joined Twoday in Finland in 2020 and works across teams and business units in hands-on architect and advisor roles, leading modernization efforts and solving complex technical challenges. Simo has a strong focus on Domain-Driven Design and on designing distributed backends that deliver low latency and scale, while also contributing to global initiatives that strengthen engineering excellence and modern software development across Twoday.
Simo Roikonen, Global Principal Architect