“CIOs are mandating AI to build apps faster, but many are realizing speed isn’t the bottleneck because more code doesn’t automatically create business value,” says Matt Healy, senior director of product strategy and marketing at Pegasystems. “Before developers write any code, organizations must understand customer needs, assess legacy systems, stay current with regulations and best practices, map enterprise architectures and integrations, and align business and IT.”
Consider three stages of understanding requirements. Once stakeholders set business value and intent, developers must first align on an implementation strategy and discuss performance, cost, and other trade-offs. Then, developers should reconvene with stakeholders and review implementation trade-offs. Healy adds, “On large projects, defining the solution and success metrics can take as much time as building it. Leaders aren’t just using AI to accelerate development, but to help executives, business analysts, product owners, and IT teams collaborate more effectively.”
The third stage is gathering the goals, user requirements, and implementation approach into a development-specific context. But we’re not done yet, because data requirements and operations considerations must also be included in the context fed to AI code generators.
