Philipp Schmid

Beyond Chatbots: How to build Agentic AI systems

Is your AI stuck in a predefined workflow? Learn to build agentic systems that use an LLM to reason, plan, and execute complex tasks.

Beyond Chatbots: How to build Agentic AI systems
#1about 4 minutes

Tracing the evolution from language models to AI agents

The history of AI agents is traced from simple text completion models to complex, multi-step reasoning systems using frameworks like ReAct.

#2about 2 minutes

Defining the core components of an AI agent

An AI agent is a system where an LLM decides the application's control flow using reasoning, memory, and tools.

#3about 4 minutes

Exploring common design patterns for building AI agents

Several composable patterns like reflection, tool use, planning, and multi-agent collaboration provide structured approaches for building agentic systems.

#4about 1 minute

Why design patterns are crucial for scalable agents

Agentic design patterns are essential building blocks that provide structure, enable composition, and improve the testability of complex AI applications.

#5about 4 minutes

Evaluating agent reliability over model capability

Agent evaluation shifts focus from single-attempt model capability to multi-attempt reliability, requiring custom benchmarks to measure real-world task success.

#6about 3 minutes

Moving from prompt engineering to context engineering

Context engineering expands on prompt engineering by systematically providing the right information, tools, and memory to the LLM at the right time.

#7about 4 minutes

Building agents with Google Gemini and open source tools

You can build agents using Google Gemini through AI Studio, the native SDK, or integrations with open-source libraries like LangChain and CrewAI.

#8about 2 minutes

Predictions on the future impact of AI agents

Future agentic systems are predicted to enable zero-cost software creation, personalized multimodal interfaces, and accelerated adoption in robotics.

Related jobs
Jobs that call for the skills explored in this talk.

Matching moments

The evolution from chatbots to autonomous AI agents
04:47 MIN

The evolution from chatbots to autonomous AI agents

On a Secret Mission: Developing AI Agents

Understanding the core components of agentic AI systems
02:48 MIN

Understanding the core components of agentic AI systems

Agentic AI Systems for Critical Workloads

Understanding the core components of an AI agent
03:01 MIN

Understanding the core components of an AI agent

Agentic AI - From Theory to Practice: Developing Multi-Agent AI Systems on Azure

Tracing the evolution from LLMs to agentic AI
03:38 MIN

Tracing the evolution from LLMs to agentic AI

Exploring LLMs across clouds

Understanding the shift to the agentic era
01:31 MIN

Understanding the shift to the agentic era

Event-Driven Architecture: Breaking Conversational Barriers with Distributed AI Agents

The evolution from rule-based RPA to agentic AI
04:06 MIN

The evolution from rule-based RPA to agentic AI

The Deichmann RPA journey: Step by step with low-code automation to success

Understanding the evolution and autonomy of agentic AI
05:19 MIN

Understanding the evolution and autonomy of agentic AI

Supercharge Agentic AI Apps: A DevEx-Driven Approach to Cloud-Native Scaffolding

The evolution of AI from tool to assistant to agent
03:03 MIN

The evolution of AI from tool to assistant to agent

Should we build Generative AI into our existing software?

Featured Partners

Related Videos

See all videos
On a Secret Mission: Developing AI Agents29:03

On a Secret Mission: Developing AI Agents

Jörg Neumann

Agents for the Sake of Happiness39:11

Agents for the Sake of Happiness

Thomas Dohmke

Beyond the IDE: A new era of agent collaboration27:12

Beyond the IDE: A new era of agent collaboration

Ryan J. Salva

Agentic AI - From Theory to Practice: Developing Multi-Agent AI Systems on Azure26:35

Agentic AI - From Theory to Practice: Developing Multi-Agent AI Systems on Azure

Ricardo

Beyond Prompting: Building Scalable AI with Multi-Agent Systems and MCP25:32

Beyond Prompting: Building Scalable AI with Multi-Agent Systems and MCP

Viktoria Semaan

Agentic AI Systems for Critical Workloads30:01

Agentic AI Systems for Critical Workloads

Mario Fusco

Rethinking Workflows in the Agentic Era27:07

Rethinking Workflows in the Agentic Era

Eric Jadi & Rene Pajta

Building Blocks for Agentic Solutions in your Enterprise23:39

Building Blocks for Agentic Solutions in your Enterprise

Dennis Zielke & Rene Pajta

Related Articles

View all articles
CH
Chris Heilmann
WebMCP: Empowering Agents as First-Class Citizens of the Web
WebMCP is an exciting W3C proposal that just landed in Chrome Canary to try out . The idea is that you can use some HTML attributes on a form or register JavaScript tool methods to give agents direct access to content. This gives us as content prov...
WebMCP: Empowering Agents as First-Class Citizens of the Web
DC
Daniel Cranney
What is Agentic Programming and Why Should Developers Care?
Since the release of tools like ChatGPT and GitHub Copilot, the way developers work has shifted dramatically. What began as simple autocomplete in the early versions of Copilot has quickly evolved into agentic programming, where AI agents can take on...
What is Agentic Programming and Why Should Developers Care?
DC
Daniel Cranney
Stephan Gillich - Bringing AI Everywhere
In the ever-evolving world of technology, AI continues to be the frontier for innovation and transformation. Stephan Gillich, from the AI Center of Excellence at Intel, dove into the subject in a recent session titled "Bringing AI Everywhere," sheddi...
Stephan Gillich - Bringing AI Everywhere

From learning to earning

Jobs that call for the skills explored in this talk.