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World Congress 2024 • Aug 20, 2024 • Session details

Bringing the power of AI to your application.

Krzysztof Cieślak

Integrating LLMs doesn't require complex machine learning. Learn practical AI prototyping using advanced prompts and RAG. Master the shift from deterministic coding to probabilistic AI.

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#1 about 5 min

Introduction to prototyping and building practical AI applications

How to prototype software applications that sit between raw machine learning models and scaled production systems.

#2 about 3 min

Understanding the evolution and nature of large language models

How modern large language models differ from earlier specialized systems by functioning as general, probabilistic predictors.

#3 about 6 min

Steering model behavior through effective prompt engineering techniques

Applying personas, structured outputs, and chain-of-thought methods effectively guides probabilistic models toward accurate code generation.

#4 about 3 min

Integrating customized context with retrieval augmented generation approaches

Enhancing model prompts with personalized developer context requires varied retrieval mechanisms rather than generalized single-vendor solutions.

#5 about 4 min

Evaluating and observing large language model performance at scale

Measuring AI application accuracy demands offline evaluation frameworks and production telemetry instead of traditional test assertions.

#6 about 5 min

Designing user experiences defensively against AI application failures

Building intuitive intuitive workflow interfaces keeps developers in meaningful control while anticipating system latency and probabilistic generation errors.

#7 about 7 min

Comparing user interface patterns and the limitations of chat

Overcoming the unreliability of open-ended conversational interfaces involves implementing multi-step structured workflows that permit manual plan validation.

#8 about 3 min

Assessing the real world implications of AI integration

Questioning the assumed necessity of artificial intelligence within critical business systems prevents negative practical consequences for human users.

Matching moments

4:32 min

Audience Q&A on tooling choices and AI application prototyping

MIlan Todorović MIlan Todorović · WWC Europe 2026

2:21 min

Transitioning from AI co-pilots to AI-native products

Jordan Tigani Jordan Tigani · WWC Europe 2026

3:16 min

Driving developer productivity with AI in automotive tech

Mike Butcher Mike Butcher +3 · WWC 2024

1:48 min

Exploring AI integrations in modern agile development workflows

Markus Walker Markus Walker · WWC 2023

1:12 min

Enhancing conversational intent through modern large language models

Nathaniel Okenwa Nathaniel Okenwa · WWC 2025

2:13 min

Designing an agentic intent architecture for AI interactions

Precious Osaro Precious Osaro · WWC Europe 2026

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