Conference Schedule
Daily seminars, 9:00-16:30
Or Ben David
Avi Zabary
Katia Halfon
Lucy Gotfryd
Hay Lugasi
Eran Waknin
Liat Shaked
Doron Nazaretsky
Gil Zilberfeld
Leonid Pevzner
Gabriel Ben-Harosh Hasson
Dikla Tavor
התוכנית שלכם ל-Oracle AI Week 2026
BUILD AI | AI Engineering & Software Development
Mix. Match. Build Your Own AI Agenda.
בעת הרישום ניתן לבחור מראש את המסלול המתאים: להתמקד בסמינר יומי מלא אחד, או להרכיב יום מותאם אישית באמצעות בחירת 3 הרצאות מתוך מגוון הסמינרים המוצעים.
Go Deep – בחירת סמינר אחד והישארות אתו לאורך כל היום.
Mix & Match – בחירת הרצאה שונה בכל חלון זמן ובניית יום אישי המשלב כמה עולמות תוכן
בחרו תאריך
בחרו תאריך נוסף
תוכנית הסמינר
BUILD AI | AI Engineering & Software Development
Coding Agents, Agentic Development, MCP, Multi-Agent Systems, Vibe Coding, AI Test Automation
AI for Test Automation
From Coding Agents to Reliable Agentic Workflows
תוכנית הסמינר 3 הרצאות
Claude Code for Test Automation
במודול זה נצלול ליסודות העבודה עם Claude Code: כיצד מנוהל ה-Context של הסוכן, כיצד מגדירים לו ידע קבוע על הפרויקט באמצעות CLAUDE.md, איך Tools מאפשרים לו לפעול בעולם האמיתי, וכיצד Skills, MCP, כלי CLI, Subagents ו-Agent Teams מאפשרים את הרחבת היכולות ואת הבניה של תהליכי עבודה מתקדמים יותר.
Building AI-Ready Test Automation
במודול זה נבחן כיצד AI Agents עובדים מול אפליקציות Web באמצעות כלים כמו Playwright MCP ו-Playwright CLI, וכיצד נכון לבנות AI-Friendly Test Architecture שמאפשרת לסוכן לנווט בקוד, למצוא יכולות קיימות ולמחזר אותן במקום להמציא תשתית חדשה.
Building Reliable Agentic Test Automation
במודול נלמד כיצד להפוך פעילות המבוססת על AI ל-Reliable Agentic Workflow.
נראה כיצד לפרק תהליך לשלבים מוגדרים, לשלב reasoning של LLM עם קוד דטרמיניסטי, לנהל State ו-Handoffs בין Agents, להגביל את רמת האוטונומיה שלהם, לייצר Observability ולבדוק את המערכת באמצעות Evals.
Beyond the Demo AI agent build for the real world
תוכנית הסמינר 3 הרצאות
The Agent Stack Behind Reliable Agentic Systems
Agents fail in production for reasons that rarely show up in a demo: lost context, duplicated work, runs that die halfway and start over.
The model isn't the problem. The harness is. The agent harness is the engineering layer wrapped around the model: it plans, fans work out, verifies results, checkpoints.
This session is a working tour of the harness's memory surfaces, the places where memory engineering decides whether an agentic application can be trusted with real work. Reliability lives in this layer, and every one of those capabilities resolves to a memory operation. progress, and decides what enters the context window.
Modern AI Agent Memory: Methods, Algorithms, and Challenges
In this session We will discuss the main challenges that agent memory is designed to address, the algorithmic layer used to improve memory efficiency and coherency, as well asexamples from several leading scientific publications.
We will also explore the key challenges currently facing this field.
Observability in the AI Era: From Telemetry to Trusted Action
In this session, we will explore how AI systems emit richer evidence and how AI transforms raw telemetry into operational intelligence.
Building MCP Servers
תוכנית הסמינר 3 הרצאות
Foundations: LLMs, Agents & MCP
A comprehensive overview of LLM foundations, agent loops, and tool-use architecture.
Learn why agents need external capabilities and how Model Context Protocol (MCP) standardizes agent-environment interactions.
Using Existing MCP Servers
A practical, demo-driven session focusing on connecting clients to existing MCP servers.
Through live demonstrations, participants will learn how to configure environments, discover tools and resources, execute multi-tool calls, and troubleshoot real-world connection issues.
Building Your Own MCP Server
A step-by-step live demo on building a custom MCP server in Python.
Participants will observe project scaffolding, custom tool and resource implementation, and client integration with error handling.
Engineering for Reality: Cloud Automation, Production Failures & Resilience
תוכנית הסמינר 3 הרצאות
Infrastructure as Code: Automation Without Losing Grip
“Create another environment exactly like production.” Which version of production?
An urgent console fix, a copied configuration and a script that stops halfway can quickly turn infrastructure into a guessing game. Automation helps—but how do we make changes repeatable without losing visibility, ownership and control?
This session follows the journey from manual work → scripts → Terraform → Terragrunt → a full GitOps ecosystem. Through practical examples and guided walkthroughs, we’ll explore reusable infrastructure, environment management, drift detection and controlled execution with OCI Resource Manager. We’ll then connect infrastructure provisioning with Helm and Argo CD, examining how GitOps changes deployment, reconciliation and recovery.
We’ll also discuss Karpenter for OCI and Crossplane, focusing on the ownership boundaries needed when multiple controllers manage infrastructure.
Audience: DevOps and platform engineers, SREs, cloud architects and developers responsible for infrastructure. Familiarity with cloud fundamentals is recommended; Terraform and Kubernetes knowledge is helpful.
Failure Occurs Only in Production
The servers are green. The customer is still waiting. What do you investigate first?
Production brings together traffic, dependencies, configuration and timing in ways that testing rarely reproduces. When something fails, more dashboards do not automatically lead to a better explanation.
Using an illustrative production incident, this session connects metrics, logs and distributed traces to investigate competing explanations, identify bottlenecks and verify recovery.
We’ll examine how an apparently slow database operation can actually be time spent waiting for a shared resource - and what evidence separates those possibilities.
Product walkthroughs and screenshots show where OCI Application Performance Monitoring (APM), Oracle Log Analytics and OCI Monitoring fit, alongside OpenTelemetry, Prometheus, Grafana, Loki, Tempo and Jaeger. We’ll also translate user expectations into service indicators, service targets and error budgets.
Audience: Developers, DevOps engineers, SREs, DBAs and architects involved in diagnosing production systems. Basic familiarity with APIs and cloud applications is recommended.
Resilience by Design: Building Resilient Applications on OCI
When critical applications go down, the impact goes far beyond IT. Resilient platforms keep critical services running, protect data, and enable rapid recovery when disruption occurs.
This seminar explores how resilience is designed across the OCI stack, covering high availability, networking, data protection, RPO/RTO, and cross-region disaster recovery, followed by a live OCI Full Stack DR demonstration.
Audience: Cloud and infrastructure architects, application architects, database administrators, DevOps and platform engineers, and IT professionals responsible for service availability, business continuity, and disaster recovery.
No mandatory prerequisites; basic familiarity with cloud concepts is required.
Engineering Production Multi-Agent Systems
An Enterprise Case Study Masterclass
תוכנית הסמינר 3 הרצאות
Single-Agent Bottlenecks
Focus: Understanding single-agent mechanics, tool overload, and basic state graph architecture.
Scaling with Multi-Agent Patterns and Middlewares
Focus: Sub-agent orchestration, handoffs, skills routing, and state interceptors.
Advanced Multi-Agent Engineering
Focus: Deep LangGraph workflows, full architectural refactoring, and cost/context optimization.
Vibe Coding- From Concept to Deployment
תוכנית הסמינר 3 הרצאות
From Concept to Prototype
היכרות עם גישת Vibe Coding והפיכת רעיון ראשוני למוצר דיגיטלי מתוכנן ומעוצב.
Full-Stack AI Development
פיתוח מוצר מלא מקצה לקצה במהלך ההרצאה, החל מהגדרת הדרישות ועד למערכת פעילה הכוללת ממשק משתמש, לוגיקה, נתונים וחיבורים לשירותים חיצוניים.
Integrations, Automations & Cloud Deployment
חיבור המוצר למערכות חיצוניות, יצירת תהליכים אוטומטיים והעלאתו לסביבה חיה בענן.
What Developers Using AI Still Need to Know About Programming
תוכנית הסמינר 3 הרצאות
From Writing to Judging: Software Engineering in the Age of AI Code Execution
Topics Covered:
• The New Bottleneck.
• The "Confidence Trap".
• Critical Code Review for Machine Output.
• Practical Failure Modes.
Concurrency, Algorithms & Architecture Where AI Fails (and You Need to Rescue It)
Topics Covered:
• Tests as the Leash.
• Behavior vs. Implementation.
• Evolving Agile Processes.
• Modern AI Workflow Lifecycle.
The AI Leash Building an Enterprise Safety Net and Rethinking Development Processes
Topics Covered:
Tests as the Leash.
Behavior vs. Implementation.
Evolving Agile Processes.
Modern AI Workflow Lifecycle.
Agentic Automation: Claude, MCP and n8n in Practice
AI-Native Development Practices for Modern Developers
Beyond Code Generation: Backend Performance with AI
Agent Development in Practice with TypeScript: A Deep Dive
Building AI Agents with Node.js: The Claude Agent SDK Workshop
Testing AI Features: Defining Quality in the AI Age
Modern Data Science & AI for Developers
Practical API Design
מ-QA ידני לאוטומציה חכמה עם AI ו-Vibe Coding
Agentic AI with N8N for DevOps
Event-Driven Reactions, Alert Intelligence and Controlled Remediation
Agentic Engineering in Practice: Atlassian AI Workshop
From Methodology to Execution: Deploying Autonomous Agents in Your SDLC
Design Patterns and Advanced Software Architecture: How to Combat AI Software Decay
How to build RAG applications with langchain
Multi-Repo Agentic Development: Scaling AI Coding Across Teams
16.11.2026
Claude Code for Test Automation
במודול זה נצלול ליסודות העבודה עם Claude Code: כיצד מנוהל ה-Context של הסוכן, כיצד מגדירים לו ידע קבוע על הפרויקט באמצעות CLAUDE.md, איך Tools מאפשרים לו לפעול בעולם האמיתי, וכיצד Skills, MCP, כלי CLI, Subagents ו-Agent Teams מאפשרים את הרחבת היכולות ואת הבניה של תהליכי עבודה מתקדמים יותר.
The Agent Stack Behind Reliable Agentic Systems
Agents fail in production for reasons that rarely show up in a demo: lost context, duplicated work, runs that die halfway and start over.
The model isn't the problem. The harness is. The agent harness is the engineering layer wrapped around the model: it plans, fans work out, verifies results, checkpoints.
This session is a working tour of the harness's memory surfaces, the places where memory engineering decides whether an agentic application can be trusted with real work. Reliability lives in this layer, and every one of those capabilities resolves to a memory operation. progress, and decides what enters the context window.
Foundations: LLMs, Agents & MCP
A comprehensive overview of LLM foundations, agent loops, and tool-use architecture.
Learn why agents need external capabilities and how Model Context Protocol (MCP) standardizes agent-environment interactions.
Infrastructure as Code: Automation Without Losing Grip
“Create another environment exactly like production.” Which version of production?
An urgent console fix, a copied configuration and a script that stops halfway can quickly turn infrastructure into a guessing game. Automation helps—but how do we make changes repeatable without losing visibility, ownership and control?
This session follows the journey from manual work → scripts → Terraform → Terragrunt → a full GitOps ecosystem. Through practical examples and guided walkthroughs, we’ll explore reusable infrastructure, environment management, drift detection and controlled execution with OCI Resource Manager. We’ll then connect infrastructure provisioning with Helm and Argo CD, examining how GitOps changes deployment, reconciliation and recovery.
We’ll also discuss Karpenter for OCI and Crossplane, focusing on the ownership boundaries needed when multiple controllers manage infrastructure.
Audience: DevOps and platform engineers, SREs, cloud architects and developers responsible for infrastructure. Familiarity with cloud fundamentals is recommended; Terraform and Kubernetes knowledge is helpful.
Single-Agent Bottlenecks
Focus: Understanding single-agent mechanics, tool overload, and basic state graph architecture.
From Concept to Prototype
היכרות עם גישת Vibe Coding והפיכת רעיון ראשוני למוצר דיגיטלי מתוכנן ומעוצב.
From Writing to Judging: Software Engineering in the Age of AI Code Execution
Topics Covered:
• The New Bottleneck.
• The "Confidence Trap".
• Critical Code Review for Machine Output.
• Practical Failure Modes.
Building AI-Ready Test Automation
במודול זה נבחן כיצד AI Agents עובדים מול אפליקציות Web באמצעות כלים כמו Playwright MCP ו-Playwright CLI, וכיצד נכון לבנות AI-Friendly Test Architecture שמאפשרת לסוכן לנווט בקוד, למצוא יכולות קיימות ולמחזר אותן במקום להמציא תשתית חדשה.
Modern AI Agent Memory: Methods, Algorithms, and Challenges
In this session We will discuss the main challenges that agent memory is designed to address, the algorithmic layer used to improve memory efficiency and coherency, as well asexamples from several leading scientific publications.
We will also explore the key challenges currently facing this field.
Using Existing MCP Servers
A practical, demo-driven session focusing on connecting clients to existing MCP servers.
Through live demonstrations, participants will learn how to configure environments, discover tools and resources, execute multi-tool calls, and troubleshoot real-world connection issues.
Failure Occurs Only in Production
The servers are green. The customer is still waiting. What do you investigate first?
Production brings together traffic, dependencies, configuration and timing in ways that testing rarely reproduces. When something fails, more dashboards do not automatically lead to a better explanation.
Using an illustrative production incident, this session connects metrics, logs and distributed traces to investigate competing explanations, identify bottlenecks and verify recovery.
We’ll examine how an apparently slow database operation can actually be time spent waiting for a shared resource - and what evidence separates those possibilities.
Product walkthroughs and screenshots show where OCI Application Performance Monitoring (APM), Oracle Log Analytics and OCI Monitoring fit, alongside OpenTelemetry, Prometheus, Grafana, Loki, Tempo and Jaeger. We’ll also translate user expectations into service indicators, service targets and error budgets.
Audience: Developers, DevOps engineers, SREs, DBAs and architects involved in diagnosing production systems. Basic familiarity with APIs and cloud applications is recommended.
Scaling with Multi-Agent Patterns and Middlewares
Focus: Sub-agent orchestration, handoffs, skills routing, and state interceptors.
Full-Stack AI Development
פיתוח מוצר מלא מקצה לקצה במהלך ההרצאה, החל מהגדרת הדרישות ועד למערכת פעילה הכוללת ממשק משתמש, לוגיקה, נתונים וחיבורים לשירותים חיצוניים.
Concurrency, Algorithms & Architecture Where AI Fails (and You Need to Rescue It)
Topics Covered:
• Tests as the Leash.
• Behavior vs. Implementation.
• Evolving Agile Processes.
• Modern AI Workflow Lifecycle.
Building Reliable Agentic Test Automation
במודול נלמד כיצד להפוך פעילות המבוססת על AI ל-Reliable Agentic Workflow.
נראה כיצד לפרק תהליך לשלבים מוגדרים, לשלב reasoning של LLM עם קוד דטרמיניסטי, לנהל State ו-Handoffs בין Agents, להגביל את רמת האוטונומיה שלהם, לייצר Observability ולבדוק את המערכת באמצעות Evals.
Observability in the AI Era: From Telemetry to Trusted Action
In this session, we will explore how AI systems emit richer evidence and how AI transforms raw telemetry into operational intelligence.
Building Your Own MCP Server
A step-by-step live demo on building a custom MCP server in Python.
Participants will observe project scaffolding, custom tool and resource implementation, and client integration with error handling.
Resilience by Design: Building Resilient Applications on OCI
When critical applications go down, the impact goes far beyond IT. Resilient platforms keep critical services running, protect data, and enable rapid recovery when disruption occurs.
This seminar explores how resilience is designed across the OCI stack, covering high availability, networking, data protection, RPO/RTO, and cross-region disaster recovery, followed by a live OCI Full Stack DR demonstration.
Audience: Cloud and infrastructure architects, application architects, database administrators, DevOps and platform engineers, and IT professionals responsible for service availability, business continuity, and disaster recovery.
No mandatory prerequisites; basic familiarity with cloud concepts is required.
Advanced Multi-Agent Engineering
Focus: Deep LangGraph workflows, full architectural refactoring, and cost/context optimization.
Integrations, Automations & Cloud Deployment
חיבור המוצר למערכות חיצוניות, יצירת תהליכים אוטומטיים והעלאתו לסביבה חיה בענן.
The AI Leash Building an Enterprise Safety Net and Rethinking Development Processes
Topics Covered:
Tests as the Leash.
Behavior vs. Implementation.
Evolving Agile Processes.
Modern AI Workflow Lifecycle.