1. Keynote / Mainstage Tech Talk

Theme: The Reshaped Engineer: Why Fundamentals Matter More in the Age of AI

Format: 30–45 mins | Solo Presentation

Target Profile: Staff/Principal Engineers, VP of Engineering, Chief Architects, or recognized industry thought leaders with extensive experience leading large-scale software engineering organizations through major technological shifts.

Demonstrated Expertise:

• Proven track record of architecting distributed or enterprise systems at scale, with deep insight into software lifecycle economics.
• Experience evaluating or integrating AI tools across engineering teams at an organizational level.

Deliverable & Submission Requirements:

• Abstract & Narrative Arc: A clear, data-informed session outline demonstrating how engineering leverage shifts from code generation to systems governance.
• Thought Leadership Proof: Past public speaking recordings (conferences, internal summits, or podcasts) showing high-energy stage presence, executive storytelling, and an ability to address an audience of 1,000+ developers.
• Key Takeaway Deck / Rough Outline: Draft bullet points showing concrete economic data, case examples, or mental models that will be presented.

2. Panel Discussion

Theme: Who Is Responsible When AI Writes the Code? Accountability, Auditing, and Risk Management

Format: 60 mins | Moderated Panel (3–4 Panelists + 1 Moderator)

Target Profile: Engineering Directors, Head of Security/AppSec, Chief Risk Officers (CRO), Chief Information Security Officers (CISO), Legal Counsel in Tech, or AI Compliance & Governance Researchers.

Demonstrated Expertise:

• Direct responsibility for production deployments, compliance sign-offs, AppSec validation, or legal liability frameworks.
• Experience responding to real-world incidents or implementing strict organizational policy around automated tooling and IP/privacy risks.

Deliverable & Submission Requirements:

• Point of View (POV) Statement: A 2–3 paragraph summary answering: “Where does the ultimate liability stop when AI code fails in production?” to ensure panelists hold diverse, debate-worthy perspectives.
• Discussion Focus: Confirmation of which pillar they can speak to authoritatively (e.g., Security & Vulnerability Auditing, Institutional Sign-off & Policy, or Regulatory/Legal Liability).
• Panel Suitability: Prior experience in panel discussions, town halls, or roundtables, demonstrating concise responses and active conversational engagement.

3. Live Podcast / Media Track

Theme: Code Faster, Think Slower: Surviving the Transition from Pre-AI to Post-AI Engineering

Format: 60 mins | Fireside / Audio-Visual Conversational Setup

Target Profile: Senior/Lead Engineers, Tech Leads, Engineering Managers, or Veteran Developers (8+ years in the industry) who have navigated the workflow transition from traditional coding to AI-assisted workflows.

Demonstrated Expertise:

• Firsthand experience mentoring developers experiencing workflow shifts, tool fatigue, or cognitive retooling.
• Pragmatic, realistic mindset—neither an AI evangelist dismissing real risks nor a rigid skeptic refusing adaptation.

Deliverable & Submission Requirements:

• Vulnerability & Narrative Pitch: A brief personal synopsis sharing their own transition story, candid challenges, mistakes made while adopting LLM tooling, and daily sustainable engineering habits.
• Audio/Video Sample: A link to a previous podcast appearance, technical interview, or video demonstration verifying a conversational, authentic, and reflective speaking style. Topic Anchors: 3–4 specific talking points or controversial takes on dev culture, productivity metrics, and mental resilience.

4. Interactive Hands-on Workshop

Theme: Architecting with AI Without Losing the Craft: Code Review, Verification & System Auditing

Format: 60–90 mins | Hands-on Technical Lab

Target Profile: Senior Staff Engineers, DevSecOps Leads, Cloud/System Architects, or Technical Trainers with extensive hands-on code auditing, debugging, and pipeline automation expertise.

Demonstrated Expertise:

• Expert-level understanding of non-functional requirements (race conditions, memory leaks, concurrency, latency, prompt-injection boundaries).
• Proven ability to design and automate validation pipelines, guardrail frameworks, or schema-based constraints.

Deliverable & Submission Requirements:

• Curriculum & Lab Structure: A breakdown of the session timeline (e.g., 15 mins context/theory, 45 mins guided hands-on exercise, 15 mins debrief & verification analysis).
• Lab Artifact Plan: A description of the sample codebase or GitHub repo to be provided to attendees (including pre-configured buggy AI services, tests, or container setups).

Prerequisite & Setup Matrix: Explicit list of requirements for participants (e.g., local environment, IDE extensions, API keys, or Docker setup) to ensure zero drop-off on event day.

5. Lightning Talk

Theme: Real-World Engineering in the AI Era: Practical Case Studies

Format: 15 mins total (Strict 10-min Presentation + 5-min Q&A/Audience Wrap-up)

Target Profile: Practicing Engineers, Individual Contributors (Mid to Principal), Open Source Contributors, or Startup Technical Founders with a sharp, highly specific production lesson to share.

Demonstrated Expertise:

• Ownership of a concrete, shipped use case that aligns with the event's theme (e.g., automated refactoring pipelines, novel verification tests, or architectural lessons learned from AI code in production).
• No purely theoretical concepts—must be grounded in shipped reality.

Deliverable & Submission Requirements:

• "Problem–Constraint–Solution" Abstract: A tight summary showing "The exact production problem faced."
• Why standard AI generation failed or created architectural friction.
• The engineering pattern or framework applied to solve it.

Slide Deck Proof / Draft (Max 8–10 slides): A sample deck demonstrating conciseness, visual clarity, and respect for the strict 10-minute presentation window.

Single Core Takeaway: A definition of the single practical technique attendees can apply to their codebase immediately.