Call for Presentations: AI Engineer Melbourne 2026

How to Submit a Winning Proposal

What We're Looking For

AI Engineer Melbourne 2026 seeks practical, experience-driven talks from people building real AI systems in production. We're not looking for sales pitches, theoretical concepts, or generic AI overviews. We want talks that share what you've actually built, what worked, what didn't, and what you learned.

Your talk should be built from:

• Real production experience and user data
• Concrete technical decisions and trade-offs
• Live demos or launches (we get millions of views online)
• Product-market fit stories
• Hard-won lessons from actual implementation

We will desk-reject talks that:

• Are thinly veiled product pitches with lazy titles
• Rehash content from generic AI conferences
• Focus purely on theory without practical application
• Simply promote your company without substantive technical depth

Conference Format

Talk Length: 18 minutes (no on-stage Q&A)

• Dive straight into content with minimal self-introduction
• The MC will introduce you with background
• Focus on delivering maximum value in a tight timeframe

What Happens to Your Talk:

• Professionally recorded and published on YouTube, X, and LinkedIn
• Optional follow-up interview
• Potential for millions of views (our talks reach massive online audiences)
• Screenshot essay version promoted alongside your talk

Multiple Submissions Welcome:
Don't try to guess what we want! Submit 1-5 topic proposals that represent different talks you could give. We'll work with you to refine titles and abstracts later. Just give us the rough direction and your vision for each talk.

Our Three Tracks

1. AI Engineering

For: Practitioners building AI systems and applications

What we want:

• Novel architectures and system designs for AI applications
• Innovative approaches to RAG, agents, and AI pipelines
• Real-world case studies with production metrics
• Open source launches and major tool releases
• Hard technical problems you solved (and how)
• Integration patterns and infrastructure challenges

Topics include:

• Retrieval, search, and recommendation systems
• Agent architectures and reliability patterns
• Voice AI and real-time systems
• Evals and testing strategies
• Model Context Protocol (MCP) implementations
• GraphRAG and knowledge graphs
• Inference optimization and deployment
• Generative media pipelines

What makes a great AI Engineering talk:

• Shows real user data and production learnings
• Includes live demos or hands-on examples
• Shares specific metrics and outcomes
• Discusses trade-offs you made and why
• Provides actionable takeaways for the audience

2. Software Engineering with AI

For: Developers using AI tools to build software

What we want:

• How AI is transforming your development workflow
• Productivity hacks with AI coding tools
• Real examples of AI-assisted development
• When AI tools work brilliantly and when they fail
• Integration of AI into software development lifecycle
• Building applications with AI-powered features

Topics include:

• Inner loop agents (Cursor, Windsurf, Claude Code, Copilot)
• Outer loop agents (Devin, Factory, autonomous code agents)
• Computer-using agents and browser automation
• Vibe coding tools (Bolt, Lovable, v0) and best practices
• AI-powered debugging, refactoring, and code review
• Custom configurations and productivity setups
• Voice-driven development workflows

What makes a great SWE with AI talk:

• Demonstrates significant productivity gains
• Shows before/after workflows
• Shares specific tool configurations or prompts
• Discusses where AI tools break down
• Live demos of AI-assisted development
• NOT just product demos from your employer

Special callout: If you've spent excessive time on .cursorrules or similar configurations, we want to hear about it. Power users welcome!

3. AI Leadership & Architecture

For: Senior technical leaders defining AI strategy

Who should submit:

• CTOs, VPs of AI, AI Architects at large organizations (500+ employees)
• The most senior AI person at your company
• Technical leaders who've built and scaled AI teams

What we want:

• How you're defining and executing AI strategy
• Building and scaling AI engineering organizations
• Real decisions about build vs. buy for AI infrastructure
• Organizational transformations driven by AI
• Compensation structures and career ladders for AI roles
• Compliance, partnerships, and legal considerations
• Multi-million dollar AI infrastructure decisions

Topics include:

• Hiring and scaling AI teams effectively
• Setting AI strategy that drives business outcomes
• Managing AI transformations and pivots
• Technical leadership in large-scale AI implementations
• Infrastructure decisions at enterprise scale
• Balancing innovation with governance
• Cross-functional collaboration (eng, product, legal)

What makes a great Leadership talk:

• Battle-tested experience from large-scale implementations
• Honest discussion of what worked and what failed
• Specific frameworks or mental models you use
• Quantifiable business impact
• Lessons that other leaders can apply immediately

How to Write a Winning Abstract

Study What Works

Before writing, review:

• Best talks from past AI Engineer conferences
• High-quality talks from JSConf, GDC, Goto, StrangeLoop
• The difference between practitioner talks and vendor talks

Your chances approach zero if you submit generic AI conference talks.

Pick Non-Boring Titles

• Avoid: "Introduction to [technology]"
• Avoid: "How [company] uses AI"
• Good: "Why our RAG system failed at 10M users (and how we fixed it)"
• Good: "Building a $2M ARR AI product with 2 engineers"
• Good: "I replaced our entire test suite with AI evals - here's what happened"

You can change titles later - we'll work with you on refinement.

Write from Experience

Your abstract should answer:

• What specific problem did you face?
• What did you build to solve it?
• What were the key technical decisions and trade-offs?
• What metrics or outcomes can you share?
• What would you do differently next time?

Consider Screenshot Essays

We encourage submitting "Screenshot Essay" versions of your talks - mini-blogposts that promote your talk and reach wider audiences than the talk itself. See examples here.

The Selection Process

Expert Review: Our selection committee carefully reviews all submissions for:

• Technical depth and originality
• Production readiness and real-world experience
• Presentation quality and speaker delivery
• Fit with conference tracks and audience needs
• Diversity of perspectives and topics

Timeline:

• Submissions reviewed on a rolling basis
• Earlier submissions have advantage in speaker selection
• We'll work with promising submissions to refine proposals
• Final speaker confirmations will include talk refinement calls

Benefits of Speaking

Global Exposure:

• Present to 600+ AI engineers, technical founders, and leaders
• Establish thought leadership in the emerging AI engineering industry
• Join the ranks of AI Engineer's globally-recognized speaker network

Career Impact:

• Professional video recording published on major platforms
• Potential for millions of views and ongoing industry visibility
• Opens doors to consulting, advisory, and leadership opportunities
• Expand your professional network dramatically

Company Visibility:

• Showcase your company's technical excellence
• Attract top AI engineering talent
• Position your team as innovation leaders
• Generate business development opportunities

Community Contribution:

• Help advance the state of AI engineering practice
• Share hard-won knowledge with peers
• Build the AI engineering community in APAC
• Shape the future direction of the field

About You: What We Want to Know

When you submit your proposal, we need to understand who you are and why you're the right person to give this talk. Here's what matters to us:

Your Relevant Experience:

• What have you actually built or shipped related to this topic?
• What's your role and how long have you been working in this area?
• What production systems have you been responsible for?
• What scale of problems have you tackled? (users, requests, data, team size)

Why You're Qualified to Speak on This:

• What makes your perspective unique or valuable?
• What direct experience do you have with the specific problem/solution?
• What companies or projects have you worked on that relate to this talk?

Your Speaking Experience:

• Have you given conference talks before? If so, which conferences?
• Links to recordings of previous talks (if available)
• Have you done internal company presentations, meetup talks, or podcasts?
• Are you comfortable presenting technical content to a technical audience?

Note: Prior speaking experience is NOT required. We welcome first-time speakers with great stories to tell. However, if you have spoken before, sharing links to previous talks helps us understand your presentation style.

What We're NOT Looking For:

• Marketing titles or job descriptions without substance
• Generic expertise claims ("10 years in AI")
• Speaking experience without relevant technical depth
• Company credentials without personal contribution details

Keep It Real:
We'd rather hear "I'm a senior engineer who spent 6 months debugging our RAG hallucination problem in production with 500K daily users" than "I'm a Distinguished AI Architect with extensive experience in enterprise AI solutions."

Bio Guidelines:

• 100-200 words maximum
• Focus on relevant technical experience
• Include current role and company
• Mention specific projects or systems you've built
• Link to GitHub, blog posts, or previous talks if available
• Be honest about your experience level - we value authentic voices at all career stages

How to Submit

Prepare:

1. Read this guidance thoroughly
2. Review past AI Engineer talks to understand quality bar
3. Draft 1-5 talk proposals (title + 200-300 word abstract each)
4. Write your speaker bio (100-200 words) highlighting relevant experience
5. Note any live demo or launch you're planning

Submit:
Submit your proposal through our portal →

Questions?
Contact speakers@aiengineer.melbourne

Final Reminders

✅ DO:

• Submit multiple proposals if you have several strong topics
• Share specific technical details and real metrics
• Propose live demos or product launches
• Be honest about challenges and failures
• Focus on practical, actionable content
• Submit early for best consideration

❌ DON'T:

• Submit generic product pitches
• Rehash talks from other AI conferences
• Focus on theory without practical application
• Use vague, boring titles
• Hide your best insights to "save for the talk"
• Wait until the last minute

AI Engineer Melbourne 2026 is the ONLY AI engineering conference in Australia. We're building a community of practitioners solving real problems with AI. Your experience matters. Your lessons learned matter. Share them with us.

Submit your proposal today.

Code of Conduct

For over a decade, we've worked hard to create inclusive, fun, inspring and safe events for the Web Industry.

As part of our commitment to these values, we've adopted a code of conduct for all involved: ourselves, our speakers, our partners and our audience.