Do your tool integrations give your GenAI assistants a reliable way to call external systems every time?
As you connect LLMs to live APIs and services, your tool layer becomes the foundation for safe orchestration and monitoring—but it can quickly turn brittle and risky if not designed for change.
To win, your GenAI solutions need a resilient, well-tested tool layer that can evolve as systems and APIs change.
The Challenge
Without a strong approach to tool selection and integration, teams struggle to:
- Stitch together ad hoc function calls and schemas that are hard to reuse or govern.
- Keep pace with shifting APIs, auth models, and payloads without breaking assistants in production.
- Thoroughly test error paths, timeouts, and edge cases across tools and environments.
Weak tool layers will drive silent failures, operational risk, and slow, fragile GenAI delivery.
Our Solution
In this hands-on workshop, your team designs, validates, and implements a reusable tool layer for LLMs using curated notebooks, APIs, and example services. Areas of focus include:
- Structured Outputs & JSON Schema — Define strict, machine-readable contracts that keep tool calls predictable.
- Adapter & Shielding Patterns — Build stable adapters that insulate assistants from volatile upstream APIs.
- Sandboxing & Test Harnesses — Use mocks, sandboxes, and record/replay tests to safely exercise tools and failure paths.
- Interactive Labs & IDE Workflows — Explore tool behavior inside curated notebooks and IDE environments.
- Capstone & Expert Coaching — Assemble a full tool layer and refine design, failure handling, and tests with instructor guidance.
Skills You'll Gain
- Reliable Tool Layers — Design contracts and adapters that reduce incidents, retries, and silent failures.
- Faster Feature Delivery — Reuse integration patterns so new tools and workflows ship in days, not weeks.
- Risk-Aware Integrations — Isolate critical systems behind sandboxed, observable tool interfaces with well-defined access.
- Shared Platform Patterns — Align teams on schemas, patterns, and testing practices for tool usage across products.
- Future-Ready Foundations — Prepare for orchestration, security, and monitoring on top of a solid API and tool layer.
Who Should Attend:
Solution Essentials
Format
Virtual or in-person
Duration
4 Hours
Skill Level
Intermediate familiarity with APIs and basic Python recommended
Tools
Jupyter notebooks, reference LLM APIs, and example service endpoints
Explore the Remaining GenAI Tools Foundations Certification Workshops
Help your teams responsibly adopt and scale GenAI Tool Usage. Click below to explore the remaining workshops in the GenAI Tools Foundations certification series.
Data Handling, Validation & Security
Tool Chaining & Pipelines