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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

16 Apr 2025

Nvidia faces $5.5bn hit from Trump clampdown on AI chips

Nvidia faces $5.5bn hit from Trump clampdown on AI chips

Author: SuperUser Account  /  Categories: AI Finance  /  Rate this article:
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Nvidia said it expects to take a $5.5 billion hit as President Trump clamps down on the sale of powerful artificial intelligence chips to China.

The US chip designer at the centre of the AI boom said the US government was introducing new restrictions on its chip exports over fears they could be used to help China build a supercomputer.

Supercomputers are the engines of a type of data centre created for the sole purpose of powering AI.

The US had already imposed export restrictions on more powerful Nvidia chips, including the Blackwell, to prevent them reaching China where they could be used for military applications and breakthroughs in AI.

However, Nvidia said the US government will now require licences for exports to China of its H20 chip, the most advanced Nvidia chip presently available in China.

Nvidia announced the $5.5 billion charge in a regulatory filing on Tuesday, sending shares in the company down almost 6 per cent in after-hours trading.

The latest government crackdown on chip exports comes after Chinese companies reportedly placed at least $16 billion in orders for Nvidia’s H20 chips in the first three months of the year.

ByteDance, Alibaba Group and Tencent Holdings are among companies that have been buying up the most advanced Nvidia artificial intelligence chips that are legally available in China under US export controls, The Information reported earlier this month.

The high demand for Nvidia’s H20 chips is believed to be driven by the Chinese start-up DeepSeek’s AI models.

Nvidia said the US government informed it on April 9 that the H20 chip would require a licence to be exported to China and on April 14 told Nvidia that those rules would be in place indefinitely.

Nvidia’s filing did not indicate how many of those licences the US government could grant.

The chipmaker said on Monday that it was planning to spend as much as $500 billion building supercomputers for artificial intelligence entirely in the US over the next four years.

 

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