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When AI Writes the Code, Who Designs the System?
AI coding tools can now generate functions, services, and sometimes entire repositories in seconds. Writing code is becoming easier and faster than ever.
But good systems are not just code.

Architecture โ€” defining system boundaries, data flows, failure modes, operational constraints, and long-term maintainability โ€” still requires engineering judgement and a holistic view of the system. In fact, as AI generates more code, architecture becomes even more critical. Missing context, unclear constraints, or weak guardrails can quickly lead to fragile systems at scale.

Title: From Prompt Engineering to Harness Engineering - We've Come Far. We're Not There Yet.
Speaker: Jaideep Khandelwal
Key Takeaways:

  • The discipline software engineering teams should follow in AI-enabled SDLC for collaboration
  • Building mental models for software engineering teams to drive AI-enabled SDLC
  • Gotchas to be cost-effective and not burn tokens :)

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Title: Architecting the Guardrails to climb up the steep steps of AI development.
Speaker: Subhrajit Dasgupta
Key Takeaways:

  • AI accelerates code production but not architectural judgment โ€” that gap is yours to fill.
  • Guardrails aren't bureaucracy; they're the infrastructure that turns AI speed into AI reliability.
  • Encode your team's intent into machine-readable rules โ€” what AI can read, AI can follow.
  • The steeper the climb (faster the pace), the more critical the guardrails become.
  • The modern engineer's craft is system design: shaping the boundaries, not typing the lines.

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Title: The Architect's Paradox: Why AI Makes Human Judgment More Valuable, Not Less
Speaker: Kiran Bagul

Lets have some fun discussions and networking over light food ๐Ÿฅณ

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