Expert Insights

Oji Udezu brings attention to the transformative shifts in software development powered by real-time ideation and development.

He emphasizes an emerging context where conventional methodologies like Agile might not fit as effectively. The agility and speed of AI-assisted development, helping teams deliver prototypes while still in a call with a client, challenge the applicability of traditional approaches.

Hear Oji explain:

  • How AI-assisted real-time development blurs the lines between ideation and implementation.
  • The potential incongruities between traditional Agile methodologies and the speed of AI-powered software development.
  • The significance and need for real-time ideation and development in today's fast-paced, AI-driven world.

Quote

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REL specifically told me that sometimes they will take a call from a client and they start coding during the call, and in four hours they have a prototype ready. How does Agile fit into that? Like it's real time...quotation-marks icon
Oji Udezu ,
Co-Author, ProductMind

THE NEW DEFAULT angle

Here are the practical takeaways delineating the shift towards real-time, AI-assisted software development:

  • Embrace immediacy: Seek opportunities to reduce development cycles where feasible with AI-assisted tools, even embracing concurrent ideation and implementation where possible.
  • Revisit Agile principles: Evaluate the fit of Agile methodologies in the context of faster, real-time development. Adapt or supplement Agile practices to align with swift AI-powered workflows.
  • Prepare for a paradigm shift: Foster a team culture that embraces rapid iteration and quick deployment. Adjust current processes to fit the pace of AI-assisted software development.
  • Educate and align: Ensure all team members, from business analysts to developers, understand the implications and possibilities of immediate prototyping and coding with AI in real-time.
  • Track the transition: Measure the impacts of transitioning to real-time development, considering metrics such as speed to prototype, feedback response time, or quality of immediate outputs.
  • Rebalance responsibilities: With AI taking on part of the hands-on coding, team roles may shift towards oversight, customization, and quality control. Plan accordingly.