Beat the rush and join us early for complimentary barista-made coffee and breakfast.

AI isn't just changing how code gets written, it's rewriting team structures, delivery processes and what engineering leadership actually looks like. This keynote is a strategic conversation for leaders wrestling with the real question: How do you actually use AI to ship faster without breaking everything that makes your organisation work? 

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We’ll cover: 

• How team shapes, roles, and hiring are changing as AI absorbs junior and middle-tier work. 
• What's actually working in AI-Accelerated delivery, beyond demos and dashboards
• The leadership decisions that separates organisations using AI as a tool into a multiplier

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AI agents are now writing code, deploying systems, and making real production decisions. But when things go wrong, model drift, data leaks, or outages, most organisations can’t answer three simple questions: Did we catch it? Who’s responsible? How do we prevent it next time?

This panel brings together engineering, platform, and security leaders tackling a new reality: AI is breaking both observability and accountability.

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We’ll cover:

• Why traditional monitoring misses AI failures  and what’s replacing it
• Where accountability sits when AI makes decisions
• How to design audit trails, guardrails, and escalation paths for AI systems
• Lessons from early AI incidents what was caught, what wasn’t, and who took responsibility
• What regulators, boards, and customers now expect

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Most companies are bolting AI onto businesses designed for a pre-AI world and struggling to prove the return. Joe is doing something harder: rebuilding Finder as a 100% AI-native business, where AI is the foundation, not a feature, and where ROI is measured at the level of the business model, not the pilot project.

In this keynote, Joe shares what AI-native really means in practice: the strategy, the platform decisions, the organisational shifts, and how to build a credible ROI case when AI moves from a productivity tool to the core operating model.

A frank, practitioner's view from a CTO making the bet in real time.

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• What "AI-native" really means and how it differs from "AI-enabled"
• The platform, team, and value-chain shifts that make the transition real
• How to measure and defend ROI when AI becomes the business, not a line item

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In this innovative session, attendees will be faced with a series of scenarios that they may face in their roles. Attendees will discuss the possible courses of action with their peers to consider the ramifications of each option before logging their own course of action.

Results will be tallied and analysed by our session facilitator and results will impact the way the group moves through the activity.

Will we collectively choose the right course of action?

Kubernetes promised scalability and flexibility. In reality, many teams ended up with cluster sprawl, inconsistent setups, and rising operational overhead.

At the same time, AI workloads are adding new pressure and not every use case actually needs Kubernetes.

This session explores how control was restored through platform engineering, standardisation, and automation and when it made sense to simplify instead.

• How to reduce cluster sprawl and restore consistency
• When Kubernetes isn’t the right choice and when to simplify
• How to balance flexibility, cost, and control as workloads scale

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Cloud costs were rising, but no one owned them. Engineers couldn’t see the impact of their decisions, and optimisation focused on infrastructure not behaviour.

This session shows how cost visibility, accountability, and platform controls were embedded into engineering workflows reducing spend without slowing delivery.

• How to make cloud cost visible and actionable for engineers
• Embedding cost controls into platforms and pipelines
• Shifting from reactive cost-cutting to proactive cost ownership

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Platform engineering has moved from a trend to a strategic bet. The organisations winning with AI, managing cloud spend, and scaling delivery all have one thing in common: they've treated their internal platform as a product. 

This panel brings together engineering leaders who've built platforms their teams actually use, and made the business case to fund them.

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What we’ll cover:

• Why platform-first is no longer optional for any engineering organisation above a certain size
• How to structure, staff, and fund platform teams as a strategic capability
• The hard parts: adoption, governance, and avoiding internal tooling sprawl
• Where data, environments, and developer experience intersect in a modern platform

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Select a topic of discussion and engage in an interactive roundtable discussion with a group of your like-minded peers.

Put your knowledge to the test in this fast-paced quiz covering real-world trivia, key concepts, and emerging trends. Compete for bragging rights - and a travel voucher - as the top scorer takes the crown.

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We've rebuilt Culture Amp's second largest product - Performance. It was acquired as a Series A company 5 years ago and currently has thousands of customers, with the largest having 77k users. Against conventional wisdom, we rebuilt it from the ground up on an aggressive timeline.

The underlying model was outdated, slow to iterate on, and not extensible. The monoliths were riddled with tech debt, tightly coupled, patched and band-aided many times, and couldn't take us toward the $3b global Performance market we're targeting.

That wasn't challenging enough already so I also used this opportunity to rebuild our engineering culture. We set a high bar for engineering standards and ways of working, hoping to improve engagement along the way.

In this talk, I'll share:

• How I came to this decision
• How we got buy in from Exec and the Board for a purely technical rebuild
• How we tried to set up for success, our principles and standards
• Where we failed and where we succeeded
• Lessons that could be useful for anyone thinking about rebuilding a product that's hampering speed and hindering your ability to innovate or deliver value to your customers.

Large organisations are cutting roles. Graduate pipelines are shrinking. AI is absorbing work that used to take teams of engineers. This is the uncomfortable conversation the industry isn't having openly yet. 

This interactive think tank puts these issues to the room. Participants vote live on the scenarios shaping the next five years of Australian engineering, explore the results together, and vote again as perspectives shift.

• What roles disappear, what roles emerge, and what stays the same?
• How should we train, hire, and develop engineers in an AI-native world?
• Is the junior engineer dead? What's the entry pathway now?
• What's the Australian engineering profession's responsibility to its own people?
• Where does this leave engineering leadership in 2030?

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Unwind with your peers for a couple of drinks on us!