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Quick Guide & Tips

💻   Accessing Utils File and Helper Functions

In each notebook on the top menu:

1:   Click on "File"

2:   Then, click on "Open"

You will be able to see all the notebook files for the lesson, including any helper functions used in the notebook on the left sidebar. See the following image for the steps above.


🔄   Reset User Workspace

If you need to reset your workspace to its original state, follow these quick steps:

1:   Access the Menu: Look for the three-dot menu (⋮) in the top-right corner of the notebook toolbar.

2:   Restore Original Version: Click on "Restore Original Version" from the dropdown menu.

For more detailed instructions, please visit our Reset Workspace Guide.


💻   Downloading Notebooks

In each notebook on the top menu:

1:   Click on "File"

2:   Then, click on "Download as"

3:   Then, click on "Notebook (.ipynb)"


💻   Uploading Your Files

After following the steps shown in the previous section ("File" => "Open"), then click on "Upload" button to upload your files.


📗   See Your Progress

Once you enroll in this course—or any other short course on the DeepLearning.AI platform—and open it, you can click on 'My Learning' at the top right corner of the desktop view. There, you will be able to see all the short courses you have enrolled in and your progress in each one.

Additionally, your progress in each short course is displayed at the bottom-left corner of the learning page for each course (desktop view).


📱   Features to Use

🎞   Adjust Video Speed: Click on the gear icon (⚙) on the video and then from the Speed option, choose your desired video speed.

🗣   Captions (English and Spanish): Click on the gear icon (⚙) on the video and then from the Captions option, choose to see the captions either in English or Spanish.

🔅   Video Quality: If you do not have access to high-speed internet, click on the gear icon (⚙) on the video and then from Quality, choose the quality that works the best for your Internet speed.

🖥   Picture in Picture (PiP): This feature allows you to continue watching the video when you switch to another browser tab or window. Click on the small rectangle shape on the video to go to PiP mode.

√   Hide and Unhide Lesson Navigation Menu: If you do not have a large screen, you may click on the small hamburger icon beside the title of the course to hide the left-side navigation menu. You can then unhide it by clicking on the same icon again.


🧑   Efficient Learning Tips

The following tips can help you have an efficient learning experience with this short course and other courses.

🧑   Create a Dedicated Study Space: Establish a quiet, organized workspace free from distractions. A dedicated learning environment can significantly improve concentration and overall learning efficiency.

📅   Develop a Consistent Learning Schedule: Consistency is key to learning. Set out specific times in your day for study and make it a routine. Consistent study times help build a habit and improve information retention.

Tip: Set a recurring event and reminder in your calendar, with clear action items, to get regular notifications about your study plans and goals.

☕   Take Regular Breaks: Include short breaks in your study sessions. The Pomodoro Technique, which involves studying for 25 minutes followed by a 5-minute break, can be particularly effective.

💬   Engage with the Community: Participate in forums, discussions, and group activities. Engaging with peers can provide additional insights, create a sense of community, and make learning more enjoyable.

✍   Practice Active Learning: Don't just read or run notebooks or watch the material. Engage actively by taking notes, summarizing what you learn, teaching the concept to someone else, or applying the knowledge in your practical projects.


📚   Enroll in Other Short Courses

Keep learning by enrolling in other short courses. We add new short courses regularly. Visit DeepLearning.AI Short Courses page to see our latest courses and begin learning new topics. 👇

👉👉 🔗 DeepLearning.AI – All Short Courses [+]


🙂   Let Us Know What You Think

Your feedback helps us know what you liked and didn't like about the course. We read all your feedback and use them to improve this course and future courses. Please submit your feedback by clicking on "Course Feedback" option at the bottom of the lessons list menu (desktop view).

Also, you are more than welcome to join our community 👉👉 🔗 DeepLearning.AI Forum


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Welcome to this course on Spec-Driven Development built in partnership with JetBrains. Spec-Driven Development is currently the best type of workflow for building serious applications with agentic coding assistance. Give your coding agent a markdown file or a long prompt, explaining exactly what to build and it implements that spec. Rather than writing code by hand, you focus on writing down the context that the agent doesn't already have. I'm delighted that our instructor for this course is Paul Everett, who's developer advocate at JetBrains. Thank you Andrew and wait, I didn't know you wore spectacles, You're right. I don't actually need these. Okay, that's what I thought. Anyway, Spec-Driven Development has three main benefits that you'll start to see right away. First, you can control large code changes with small changes to the spec. One sentence like, use SQLite with Prisma ORM, might affect hundreds of lines of code. Change that to MongoDB for the same downstream amplification. This makes writing specs really efficient, far more so than writing code. Second, specs help eliminate context decay between sessions, preserving the non-negotiable. Agents are stateless, so loading them with the highest quality context right when they boot up is important. And finally, specs improve your intent fidelity. You define the problem, success criteria, constraints, and so on, and the agent can elaborate to create a fuller plan. One way I often write a spec is by having a conversation with an agent like Claude Code or Gemini or ChatGPT Codex, to make the key architectural choices using my knowledge of how I want to make different trade-offs. Then have the agent summarize the key decisions in a markdown file. Writing a spec requires thinking, and this is hard work. You have to decide what product you want to build, what is its features, its technical architecture. And without a spec, you'll be leaving these important decisions up to the whims of the coding agent, which might be okay if you want to move really fast and just roll the dice, but certainly leads to less maintainable code and sometimes pretty weird products. For example, I've seen teams working on a complex software product where there was no clear spec, and this led to many downstream headaches from these different coding agents under the direction of different developers, building quickly, building in contradictory ways. Spec-Driven Development involves developing a constitution at the project level to define the immutable standards. Then iterating through feature development loops. These loops isolate each feature on its own branch with plan, implement, and verify steps that leave a clean slate between features and reduce headaches and context switching. This same workflow supports both greenfield and brownfield projects. In greenfield projects, you start from scratch. You'll develop the constitution in a conversation with the agent. In Brownfield, existing code bases, you'll generate the project constitution based on the existing code base. In both cases, you'll then iterate through these feature development loops, managing versioning in small steps. In this course, you'll also see how to write your own agent skills to automate your spec-driven workflow. You know, if you can accomplish what you need in just one short prompt, that's great. I'm definitely an advocate of lazy prompting when it works. But the great developers I know out there almost always will write detailed specs for projects with any significant complexity, because they have unique context and an opinion on what or how to build that'll be superior to letting the LLM, which is missing that context, pick randomly. If a coding agent is going to go off and write code for 20 or 30 minutes, which may correspond to several hours of traditional developer work, you're often better off sitting down for three or four minutes and writing really clear instructions. Many people have contributed to this course, including Konstantin Chaika and Zina Smirnova from JetBrains and Isabel Zaro from DeepLearning.AI. Let's go on to the next video and let's write some specs.
course detail
Next Lesson
Spec-Driven Development with Coding Agents
  • Introduction
    Video
    ・
    4 mins
  • Why spec−driven development?
    Video
    ・
    4 mins
  • Workflow overview
    Video
    ・
    3 mins
  • Set up your environment
    Reading
    ・
    5 mins
  • Setup
    Video
    ・
    1 min
  • Creating the constitution
    Video
    ・
    10 mins
  • Feature specification
    Video
    ・
    3 mins
  • Feature implementation
    Video
    ・
    1 min
  • Feature validation
    Video
    ・
    4 mins
  • Project replanning
    Video
    ・
    6 mins
  • The second feature phase
    Video
    ・
    6 mins
  • The MVP
    Video
    ・
    3 mins
  • Legacy support
    Video
    ・
    4 mins
  • Build your own workflow
    Video
    ・
    6 mins
  • Agent replaceability
    Video
    ・
    3 mins
  • Conclusion
    Video
    ・
    1 min
  • Quiz

    Graded・Quiz

    ・
    10 mins
  • Accomplishment
    Course Info