Article
Reflections on the Future of Software Engineering Retreat
By invitation only
As AI moves into core business operations, it is exposing the limits of existing architecture, fragmented data foundations and rigid operating models. The challenge is no longer just about models or use cases. It is what happens when non-deterministic AI meets the reality of production environments, where systems must operate reliably and decisions carry real consequence.
In many organisations, AI is accelerating delivery while increasing system complexity and operational risk. This raises a more fundamental question:
If AI is doing more of the work of building and executing systems, where does engineering rigour, control and accountability now sit?
This session brings together senior architecture, AI, data and technology leaders to explore how these dynamics are playing out in practice. Through a discussion grounded in real-world experience, we will examine:
The breaking points: where AI initiatives stall or fail as they move from isolated use cases into production environments
The foundation gap: how existing architecture and data structures constrain scale, reliability and execution
The architectural rethink: how system design is evolving to support AI-driven decision making
The governance shift: how organisations are maintaining control, accountability and risk management in AI-enabled systems
You will leave with a clearer view of where your current systems and operating model may be holding you back, and what needs to change to enable AI that works in the flow of business operations.
Event details
Date: Thursday, 7 May 2026
Time: 5:30pm - 8:30pm
Venue: Sydney CBD location to be confirmed upon registration
The Digital Leaders Network session is curated for a select group of senior leaders to enable a meaningful, peer-level discussion. Register your interest and we will confirm availability.
Shayan Mohanty, Global Chief Data and AI Officer at Thoughtworks
Shayan works with leading organisations globally on the practical challenges of deploying AI at scale. His experience spans architecture, data and operating models, with a focus on what needs to change to move AI from experimentation into reliable, production environments.
Agenda
5:30pm to 6:15 pm
Registration and networking
Guests arrive, informal networking with drinks and canapés
6:15pm
Opening and context setting
Andy Nolan, Global Vice President of AI, Thoughtworks
6:30pm
Industry perspective: where AI meets reality
A candid discussion with senior industry leaders on how AI is behaving in production environments, including:
Where AI initiatives break down in production
What happens as use cases move beyond pilots into core operational systems
How architectural and data constraints surface
Where legacy systems, fragmented data and rigid boundaries limit scale, reliability and speed
What is proving hardest to change
The structural, technical and organisational barriers to evolving architecture and operating models
How control and accountability are maintained
Approaches to managing risk, governance and engineering rigour as systems become less deterministic.
7:00pm
Dinner and networking
7:20 pm
Architecting for AI that works in the business
Shayan Mohanty, Chief Data and AI Officer, Thoughtworks
Shayan Mohanty brings a global perspective on how organisations are moving from AI experimentation to reliable execution in production environments. Drawing on real-world case studies, he will “open the hood” on enterprise systems to show where AI initiatives encounter architectural constraints across platforms, data and workflows, and what has changed to make AI work safely within core business operations.
8:00 pm
Open discussion and audience Q&A
An interactive discussion with the room, building on the themes raised in the fireside and Shayan’s perspective.
8:30pm
Close and networking
Informal networking continues
Meet Thoughtworks' Agentic Development Platform
AI/works™ packs decades of engineering IP into a platform that changes the economics of building industrial-grade systems. With our technologists steering AI/works, you get higher quality systems, delivered at radically lower cost. Faster than you can say “algorithmic bias”.
