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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

11 Jun 2026

What Fable 5 Means for Scrum Teams

What Fable 5 Means for Scrum Teams

Author: Rod Claar  /  Categories: AI Advanced Development, AI Augmented Scrum, Working Smarter with AI, AI Coding  /  Rate this article:
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A team at Stripe handed Claude Fable 5 a codebase migration. The job would have taken a whole team more than two months. Fable finished it in a day.

That wasn't a demo. That was a 50-million-line Ruby codebase in production.

Here's what that means for your Sprint cadence. When an AI agent can take a multi-month backlog item and complete it in 24 hours, your Sprint Planning conversation has to change. The questions shift from "who picks up this task?" to "which tasks should humans own at all?"

That's not a threat to Scrum. It's the next evolution of it.

Scrum Masters who understand AI-enhanced workflows are already rethinking their Definition of Done, their acceptance criteria, and how they coach Product Owners on backlog prioritization. They're not being replaced. They're becoming the people who know how to direct agents — and that's a completely different skill set.

The Scrum and Agile practitioners who adapt now will define what Agile looks like for the next decade.

Start building that skill set: https://AgileAIDev.com

#ScrumMaster #AIEnhancedScrum #AgileLeadership

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13 Jul 2026

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