Programme topic
Agent architecture
An agent is part model, part software system and part operating environment. Explore how teams structure context boundaries, tools, orchestration and interfaces so capability remains understandable as systems grow.
10 published talks
Talks about agent architecture
The Elephant and the Goldfish: Architecture Patterns for Cutting 70% of Agent Token Costs in Production
Tanya DixitForward Deployed Engineer, Google
LLM providers sell you a 2-million-token context window like an elephant that never forgets. If you actually build production agents that way, your latency explodes, your retrieval drifts, and your CFO will shut you down in 90 days. In production, the best…
From Prompt Rules to Structural Guarantees: The Harness Behind a Production Analytics Agent
Jiggy KakkadStaff AI Engineer, Quantium
Tinus WillemseExecutive Manager, AI & Data Science, Quantium
Checkout AI answers open-ended questions about retail sales data in natural language. It plans, calls analytics tools over MCP, executes Python in a sandbox, and returns a written analysis with charts. In a system like this, failure is rarely a crash: the…
Ontologies: AI’s Operating Manual For Your Business
Gareth WilliamsPrincipal Engineer, Wesfarmers
Tools churn. Factories commoditise. When everyone has the same models, the advantage goes to whoever gives their agents the clearest blueprint of how the business works - what exists, how it connects and the rules it runs on. That blueprint is an ontology. In…
It's time for a new kind of software
Rupert ManfrediHead of Design, Telepath
Applications package a predetermined interface, data model and set of capabilities around somebody else’s idea of a task. Generative models can now produce software on demand, but generative UI today either sits atop the existing application stack or replaces…
From REST to Agentic: Trusted APIs in the age of AI
Leigh WhitingPrincipal Engineer, Atlassian
Enterprise platforms don't get to start from scratch. When AI agents need to act on behalf of users, they inherit the API surfaces those users already depend on — surfaces evolved over many years for human-driven workflows, not autonomous reasoning. This talk…
How to Count to One Hundred
Hugo O'ConnorR&D Engineer, Anuna Research
Agents don't work well together in chat rooms: put a few in a channel and they talk past each other. Natural language and unrestricted JSON feed an open-ended pipeline of reasoning and tool calls with full Turing power. Deciding whether to accept a message…
My Agents broke APIs - Fixing Multi-Agent Systems with MCP
Anannya Roy ChowdhuryGenAI Developer Advocate, AWS
Modern AI agents struggle not because of reasoning limits, but because of interaction with tools on interfaces designed for humans. In agentic systems, this mismatch leads to incorrect tool selection, redundant calls, increased latency, & weak workflows that…
We Deleted Most of Our Agents. Everything Got Faster
Khang Nguyen HoangData Scientist, Hello Clever
The default advice is to add agents: specialised roles, an orchestrator, handoffs between them. We built that. It was a genuinely useful way to explore the problem space, and under real production traffic it was slow and expensive. When an agent system is…
Your website is a terrible API: serving agents a different page at the edge
Jack BearCEO Founder, Norg AI
Every enterprise site we work on was built for a human with a browser. When an AI agent fetches the same URL it receives navigation, cookie banners, client-rendered components and marketing prose, then has to guess at the facts underneath. Retrieval quality…
Does This Agent Make My Context Look Big? Right-Sizing AI Architectures for Production
Hamish SongsmithHead of Applied AI, Silicon Quantum Computing
All-in-one personal agent harnesses showcase the incredible potential of capability-rich AI assistants. But deploying a monolithic "do-it-all" agent into production often leaves teams struggling with context dilution, fragile tool calls, un-evaluable execution…