For decades, software development methodologies evolved incrementally—Waterfall to Agile, long release cycles to sprints, time estimates to story points. Each shift made us faster. But we are now entering the Agentic Age, where AI agents autonomously plan, reason, and execute complex workflows. This is not incremental change. This is a fundamental disruption.
Traditional methodologies are being rendered obsolete by a new paradigm: AI-Driven Development Life Cycle (AI-DLC).
Originally developed by AWS (Raja SP, Principal, DevTx APJ) and documented in the AI-Driven Development Life Cycle blog, AI-DLC reimagines the software development lifecycle with AI as a central collaborator. Rather than weeks-long iterations, AI-DLC operates in Bolts—rapid cycles measured in hours or days. Multi-orchestrated agentic workflows enable teams to develop and validate software at unprecedented speed.
Why Two-Week Sprints No Longer Work
When AI-enabled development produces working prototypes in hours, a two-week sprint is no longer rapid iteration—it is ceremony compliance. When concept-to-code happens within hours, waiting 10-12 days to reach a sprint boundary serves no purpose.
Solving the Context Engineering Problem
One of Agile's biggest challenges is context loss between sprints. Knowledge becomes tacit, decisions go undocumented, and teams face resource dependency. AI-DLC solves this through Specs and Memory Bank—a structured context repository that AI agents can reload across sessions. This provides persistent traceability between requirements, designs, and decisions—eliminating context loss largely and improving knowledge management.
memory-bank/
├── intents/ # What we're building
├── bolts/ # How we built it
├── standards/ # Project decisions
└── operations/ # Deployment contextWith AI-DLC, AI drives the conversation.
There are 3 key changes that we are witnessing with AI-DLC - 1/Near-Instantaneous Code Generation, LLMs enable rapid generation of quality code 2/ Natural Language as primary interface for engineers and 3/Human roles shift from being creators to becoming sophisticated validators.
The Role of the Software Engineer
The Role of the Software Engineer changes drastically in the Agentic age. With traditional Agile, humans plan and use AI tools to assist with coding and testing. In AI-DLC, humans define intent, and AI proposes decomposition, design, and code. AI leads execution; humans validate.
AI: "I've analyzed your intent. Here are 4 Units I propose,
with 16 user stories. I have 5 clarifying questions
before we proceed. Since you haven't specified your preferences yet, let me offer two options:
Option 1: I can proceed with my professional judgment and create the user story that:
Targets a broad tech leadership audience
Balances thought leadership with educational value
Maintains the key insights while improving clarity and flow
Properly incorporates the comparison table
OR
Option 2: You can answer the questions I asked earlier about tone, audience, and emphasis for a more customized approach.
Which would you prefer?
Human: [validates, approves, or redirects]The question hence is no longer, whether AI will transform software development. The question is: Are you ready to abandon legacy methodologies and embrace the next paradigm?
This is not about retrofitting AI tools into your existing software engineering processes anymore. It about reimagining software engineering using first principles for the Agentic Age.
#SoftwareEngineering #AgenticAI #AIDLC #AgileTransformation #DevOps #FutureOfWork #AI-Driven Development Life Cycle (AI-DLC).
