Create Your Effort Estimation Log

You will create a log of your effort estimation process. This log will help you track your progress, reflect on your estimation process, and improve it over time.

Instructions

There are several different ways you can store your log. You can use a simple text file, a spreadsheet, or a more complex tool like GitHub issues with extensions. The important thing is to keep it consistent and accessible.

• Choose a format for your log. Here are some options:
  • Text File: A simple text file where you write down your task/project, estimation for the task/project, the actual time it took you, and reflections on the estimate/task.
  • Spreadsheet: A spreadsheet where you can track your task/project, estimation for the task/project, the actual time spent, and reflections on the process.
  • GitHub Issues: Create a GitHub issue for each task with labels for estimation, actual time spent, and reflections.

Your log is a personal record, so choose the format that works best for you. You don’t need to share it with anyone, but you can if you want to. As you work through the course, you will add entries to your log for each task or project you complete.

Create your log and make your first entry. The first entry should be about this task itself, including the time you spent creating the log and your reflections on the process of creating it.

Example Log Entry

Here is an example of what a log entry might look like:

```Task E46: “Island Snow” mockup in Next.js Estimation: 1.5 hours Actual Time Spent: 3 hours Reflections: I underestimated the complexity of setting up the Next.js environment and integrating the components. I need to improve my estimation skills for similar tasks in the future.

You can add more details to your log entries as needed, such as the date you started and completed the task, the estimated size of the task, any challenges you faced, and how you overcame them.

## AI-assisted logging (if you used AI tools)

If you used any AI assistance (LLMs, Copilot, code-generation tools), add an "AI" section to the relevant log entry. This helps separate time spent prompting and verifying from ordinary implementation time.

Suggested AI fields to include in a log entry:

- AI Tool / Provider (e.g., ChatGPT-4o, GitHub Copilot, Llama 3 13B)
- Model / Version (if available)
- Prompt count (number of prompt iterations)
- Prompt time (total minutes spent writing/iterating prompts)
- Generation time (minutes spent waiting for/processing model output)
- Verification time (minutes spent reviewing, testing, and correcting output)
- Integration / refactor time (minutes spent adapting generated code into your project)
- Provenance / notes link (link to a file with prompts, diffs, or verification evidence)

Example AI-augmented log entry:

```text
Task E46: "Island Snow" mockup in Next.js
Estimation: 1.5 hours
Actual Time Spent: 3 hours
AI: Tool=ChatGPT-4o; Model=4o; Prompts=4; Prompt time=30 mins; Generation time=5 mins; Verification time=70 mins; Integration=15 mins; Provenance=./ai-prompts/island-snow-prompts.md
Reflections: AI helped produce a working scaffold quickly, but verification and integration took the majority of time. The estimate should have included verification overhead.

If you did not use AI for a particular entry, you may omit the AI section.