THENEW_DEFAULT
Back to designing
The Waterfall Paradox: Speed Through Detailed Planning0m 16s
DESIGNINGCLIP

The Waterfall Paradox: Speed Through Detailed Planning

Detailed specs accelerate delivery: invest more up front so AI halves build time and avoids costly misalignment.

Sep 29, 2025 0m 16s

Chris Rickard

Expert Insights

Chris Rickard sees AI as opening up a new paradigm in software development where precise requirements can be implemented swiftly.

Chris argues that with AI assistance, we can drastically reduce the time spent on developing software by quickly converting voluminous, specific requirements into functional applications or platforms.

Listen to him discuss:

  • The transformative potential of AI-assisted software development for rapid execution of detailed plans and requirements.
  • How AI can fundamentally change the time balance between planning and execution stages of design.
  • The idea of a new software development paradigm where speed and detail are no longer inversely proportional.
What does this new world look like when we can spend five minutes putting together 68 highly detailed requirements, and then we can spend an hour building that out? I think it's a new paradigm.
— Chris Rickard, Founder, UserDocs

THE NEW DEFAULT angle

Here's how development teams can maximize efficiency through AI-assisted planning and development:

  • Consider Process Reengineering: If the planning stage takes a significant amount of time, investigate how AI can be used to expedite the development of detailed requirements.
  • Manage Expectations: With AI-assisted development, it's important to recalibrate expected time frames for design and execution stages. Ensure all stakeholders are aware of the shorter development timeline.
  • Keep Dynamics in Check: The speed of AI-enabled development could lead to changes in team dynamics, responsibilities might shift, and individual roles may need to be redefined.
  • Prepare for Quality Assurance Changes: As development speed increases due to AI implementation, teams will need to adjust their quality assurance and testing procedures to keep up with the rapid output.
  • Monitor Evolution: Continually assess how these changes impact workflow, efficiency, and team dynamics, to fine-tune the process as your team gains experience with AI-enabled development.