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AI-DLC: One integrated workflow
AI coding already works. The problem is that every engineer is running it differently, with no shared context, process, or ownership. This session covers the engineering patterns that fix that, and what changes for the humans in the loop.
Agenda
- Human & AI, not Human vs AI
- The shadow AI problem
- Building a shared engineering context
- Engineering in continuous loops
Coding, testing, and review as one cycle - Applying AI across deployment, monitoring, and maintenance
- The golden era of the second brain: new roles, new skills
- Conclusions and Q&A
Key topics
- how AI accelerates software delivery but doesn’t replace engineering discipline;
- why every engineer building their own skills, context, and way of working quietly costs the org more than the productivity it appears to buy;
- how a shared, organization-wide context, and standardized workflows improve planning, implementation, and collaboration;
- why coding, testing, and code review stop being three stages and become one tight loop that human and AI re-enter together, pass after pass;
- practical patterns for integrating AI into the entire software development lifecycle;
- how roles, skills, and engineering leadership evolve when AI becomes part of the software delivery lifecycle.
Speaker
Claude Code 
KiroAI-driven development lifecycle
AI-Powered SDLC with Claude Code & KiroAI-DLC redesigns the software development lifecycle around AI-powered execution with human oversight. Instead of typing code and testing, engineers spend their time on architecture, product thinking, and review, while AI handles the mechanical work.
Interested in seeing AI-DLC perform inside your own organization? Get in touch, and we'll help you put Claude Code or Kiro to work for your team.
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