World Congress 2026 Europe - Virtual Stage Jul 1, 2026 Session details

MAD About Software Design - When AI Architects Argue

Lior Schejter

Why rely on a single, hallucination-prone AI for software architecture? Discover how multi-agent debates pit specialized AI personas against each other to autonomously design and refine complex systems.

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#1 about 4 min

Moving beyond coding assistants to software system design

Addressing software engineering bottlenecks requires applying artificial intelligence to complex system architecture rather than just code generation.

#2 about 2 min

Challenges with prompt-based AI system design queries

Single-prompt interactions often fail for system design due to model hallucination, overconfidence, and early anchoring.

#3 about 2 min

Human team collaboration as a model for AI architecture

Structuring artificial intelligence interactions like human team discussions enables multiple perspectives to evaluate trade-offs and reach architectural convergence.

#4 about 2 min

The multi-agent debate pattern for autonomous technical decisions

Letting large language models critique and refine each other's proposals creates an autonomous mechanism for reaching cohesive architectural decisions.

#5 about 2 min

Defining agent personas, topology, and debate convergence mechanisms

Effective debate architectures require specific agent roles, defined communication pathways, and clear criteria for concluding discussions.

#6 about 2 min

Solving contradictory design constraints through adversarial AI debate

Adversarial pressure between agents forces models to highlight implicit assumptions and balance competing technical constraints.

#7 about 2 min

Automating architectural discussions using the Dialectic command tool

The Dialectic tool introduces specialized expert personas to propose, critique, and synthesize architectural drafts autonomously.

#8 about 3 min

Configuring agent debates and answering clarifying system questions

Allowing models to ask clarifying questions about user requirements dramatically improves the final system architecture.

#9 about 4 min

Evaluating AI debate quality against formal architecture katas

Systematic testing reveals that clarifications improve results while summarization and excessive debate rounds degrade design quality.

#10 about 3 min

Controlling design outcomes by adjusting specific agent personas

Adjusting the number of specialized advocates in a debate predictably shifts the resulting architecture toward desired qualities.

#11 about 4 min

Deploying debate skills on autonomous agentic coding platforms

Executing debate protocols within environments like Claude Code or Cursor streamlines integration but increases raw token consumption.

#12 about 4 min

Integrating debates into an autonomous software development lifecycle

Connecting automated architectural debates with coding agents and continuous deployment pipelines points toward fully autonomous system evolution.

#13 about 3 min

Applying multi-agent AI debate to everyday engineering workflows

Using multi-agent systems as automated private consultants helps engineers pressure-test drafts and uncover missing system considerations.

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Balancing developer autonomy with the adoption of coding agents

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Rethinking team structures around AI agent capabilities

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Architectural patterns for developing robust generative AI applications

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Discussion on AI hallucinations and practical developer workflows

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