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Learning Path

AI on a Development Team

Who it’s for: Developers, testers, and tech leads who want practical, sprint-ready ways to use AI to build faster without sacrificing quality.

Outcomes

  • Use AI to turn vague work into clear, testable stories and acceptance criteria the team can build from.
  • Accelerate coding with guardrails: prompts that reinforce TDD, code review quality, and consistent patterns.
  • Improve delivery reliability by using AI for risk surfacing, edge cases, and “definition of done” readiness checks.

Path Steps

Work through these steps in order. Each one links to a specific EasyDNNnews article/video post.

8 steps
1
Step 1: How AI fits into a dev team (without chaos)

You’ll learn where AI helps most (planning, building, testing, reviewing) and how to keep the team in control.

Do this List 3 recurring “time sinks” in your sprint and pick one to target with AI assistance first.
5
Step 5: Code generation with guardrails

You’ll learn how to constrain AI output to your architecture, conventions, and security requirements.

Do this Create a “project rules” snippet (stack, patterns, naming, linting) and reuse it in every coding prompt.
7
Step 7: Test data, mocking, and troubleshooting with AI

You’ll learn how to generate realistic test data and isolate failures faster with structured debugging prompts.

Do this Paste a failing test + stack trace and ask AI for the top 3 hypotheses with “how to prove/kill each.”

Steps - Free

Steps - Members

 
 
✓ Featured Content

AI Coding Videos

A curated playlist of specific YouTube content.

Search Results

24 Feb 2026

Picking a Model for Your Team and Product March 23, 2026.

Author: Rod Claar  /  Categories: Picking a Model for Your Team or Product  /  Rate this article:
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Event date: 3/23/2026 2:00 PM - 5:00 PM Export event

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  • Price: $99.00 - $349.00
$99.00 - $349.00
March 23, 2026 | 2:00 PM – 5:00 PM PST

Course Overview

Selecting the right development model is critical to delivering value effectively. This interactive live session examines common Agile and hybrid approaches and helps you determine which model best aligns with your team’s structure, product type, stakeholder expectations, and organizational constraints.

Participants will explore the trade-offs between frameworks such as Scrum, Kanban, and hybrid implementations, learning how to evaluate complexity, uncertainty, regulatory needs, and team maturity before committing to an approach.

Key Learning Objectives

  • Assess your product and team context to determine appropriate delivery models
  • Compare Scrum, Kanban, and hybrid approaches with clarity
  • Identify risk, uncertainty, and compliance factors influencing model choice
  • Align stakeholder expectations with delivery structure
  • Apply decision criteria to avoid “one-size-fits-all” thinking
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20 May 2026

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