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XCurveAI

Agentic AI for Engineering Teams

ENG-101

AI-assisted delivery on real enterprise codebases. For software engineers and tech leads working with approved tooling, existing codebases and self-hosted or private models. Leave with a working agentic workflow and a team playbook for rolling it out.

Level
Practitioner
Duration
Two 4-hour sessions
Delivery
Live virtual, Private team
Language
English
Suitable for
IndividualsOrganisations
See upcoming datesTrain your team

Overview

AI-assisted delivery on real enterprise codebases

For software engineers and tech leads working with approved tooling, existing codebases and self-hosted or private models. You use AI coding assistants and agents on code like yours, not new demos, and put the guardrails around it that a regulated organisation needs.

You leave with

A working agentic workflow on a codebase like yours, and a team playbook for rolling it out.

Dates are set by demand. Register your interest and we will tell you when the first cohort is scheduled, or talk to us about running it in-house for your team.

What you will learn

  • Use AI coding assistants and agents on existing code, not just new demos
  • Put guardrails around AI-written code: review, tests and audit trail
  • Connect agents to internal tools and data using MCP
  • Run models on self-hosted or approved infrastructure
  • Measure the real effect on your team’s delivery

Who it is for

Software engineers and tech leads working with approved tooling, existing codebases and self-hosted or private models.

Prerequisites

Working experience as a software engineer or tech lead on a team codebase. No prior experience with AI agents is needed.

What's included

  • Working agentic workflowOn a codebase like yours
  • Team playbookFor rolling the workflow out to your team
  • Certificate of completion

Course outline

  1. Assistants and agents on existing code2 topics, 1 objective

    Topics

    • Coding assistants on a real codebase
    • When an agent is the right tool

    Objectives

    • Use AI coding assistants and agents on existing code, not just new demos
  2. Guardrails for AI-written code2 topics, 1 objective

    Topics

    • Review and tests for generated code
    • Keeping an audit trail

    Objectives

    • Put guardrails around AI-written code: review, tests and audit trail
  3. Connecting agents to internal tools and data2 topics, 1 objective

    Topics

    • MCP in practice
    • Permissions and boundaries

    Objectives

    • Connect agents to internal tools and data using MCP
  4. Self-hosted and approved infrastructure2 topics, 1 objective

    Topics

    • Running models where your data must stay
    • Open-weight and private models

    Objectives

    • Run models on self-hosted or approved infrastructure
  5. Measuring the effect on delivery2 topics, 1 objective

    Topics

    • Before-and-after measures
    • Your team playbook

    Objectives

    • Measure the real effect on your team’s delivery

Questions

Logistics

When does the course run?

Dates are set by demand. Register your interest and we will contact you when the first cohort is scheduled. The course can also be run in-house for your team.