Objectives
- Use Foundation Mini-Project: Tiny Task List in a runnable example rather than only describing it.
- Predict a result before execution and compare prediction with evidence.
- Introduce one safe failure and diagnose the cause systematically.
Foundation F11 · Lesson 03
Foundation Mini-Project: Tiny Task List
Objectives
By the end
- Build one semantic HTML page with a form and task list, styled responsively with plain CSS.
- Use JavaScript modules to add/remove/filter local in-memory tasks.
- Persist a tiny copy to localStorage only to practice serialization—not as architecture for the real course.
Foundation Mini-Project: Tiny Task List
Why this matters Build one semantic HTML page with a form and task list, styled responsively with plain CSS. This lesson is intentionally framework-light. You are building a mental model that will be reused when Next.js, NestJS, Prisma, TanStack Query, and deployment tooling add more vocabulary. The goal is not to memorize definitions. The goal is to predict what the computer will do and know where to look when reality differs from that prediction.
Mental model • Build one semantic HTML page with a form and task list, styled responsively with plain CSS. • Use JavaScript modules to add/remove/filter local in-memory tasks. • Persist a tiny copy to localStorage only to practice serialization—not as architecture for the real course. • Commit in small checkpoints and use DevTools to inspect DOM/state/events.
Step-by-step walkthrough 1. Write the concept in your own words before using a tool. If your explanation depends on framework jargon, simplify it one level. 2. Create the smallest runnable example that demonstrates only this concept. Keep it outside the main TaskFlow repository if experimentation could create noise. 3. Predict the result before running the command or clicking the UI. Prediction makes the output evidence instead of entertainment. 4. Run it and capture what actually happened: terminal output, browser state, request details, or file changes. 5. Change one assumption and repeat. Try an invalid input, wrong path, missing field, reordered data, or other safe failure relevant to the topic. 6. Explain the difference between the successful and failing runs. That explanation is the transferable skill.
TaskFlow connection Later in the course, framework readiness and taskflow preview stops being an isolated topic and becomes infrastructure for real features. When you encounter foundation mini-project: tiny task list again, ask which layer owns it, what its inputs are, what output proves success, and what failure evidence is available. That prevents you from copying framework snippets without understanding the underlying browser, runtime, operating-system, or language behavior.
Guided exercise Create a tiny example from scratch without copying the final code from a tutorial. Keep the example under about 30–50 lines where possible. After it works, deliberately break one assumption. Write the exact symptom and the smallest fix. Then delete the experiment or commit it in a dedicated practice folder so it does not pollute production project structure.
Check your understanding • Can you describe the concept without naming a framework? • Can you point to the exact input and output? • Can you name one common incorrect assumption? • Can you reproduce the idea in a tiny example? • Can you diagnose one intentional failure using evidence rather than guesses?
Instructor note Do not rush because the syntax looks easy. Most difficult full-stack bugs are not caused by forgetting syntax; they come from an incorrect model of ownership, execution environment, identity, time, or data flow. The foundation track exists so later lessons can move quickly without becoming mysterious.
Hands-on foundation studio
Predict → build → run → break → explain
Setup
- Create or reuse a disposable practice folder so experiments do not pollute the production TaskFlow tree.
- Open the terminal and editor side-by-side. Keep browser DevTools visible for browser work.
- Write the expected behavior in one sentence before adding code.
Do the work
- 01
Build TaskFlow Lite with create, toggle, delete, filter, and local persistence. Do not use a framework until the plain-language state model is written.
- 02
Run the smallest version first. Capture exact terminal/browser/database output before adding a second concept.
- 03
Change one input, ordering, state transition, or configuration assumption. Predict the new output, then run it.
- 04
Explain the result in terms of runtime behavior, data flow, identity, or ownership—not “the framework did it”.
- 05
Rebuild the example once without looking at the completed version.
textGuided practice: Trace TaskFlow end to end
Click “Create task”
-> React form state
-> HTTP POST /tasks
-> NestJS validation
-> service/business rule
-> Prisma
-> PostgreSQL
-> HTTP 201
-> query cache refresh
-> rendered task rowType it, predict it, run it, then change one assumption. The goal is not finishing the snippet; the goal is being able to explain the result.
Expected evidence
- The example runs from a documented command or browser action.
- Observed output matches a prediction you wrote before execution.
- The controlled failure produces a specific, explainable symptom.
- After the fix, the original reproduction passes again.
Intentional failure
Deliberately violate one assumption relevant to “Foundation Mini-Project: Tiny Task List”. Keep the failure small enough that you can identify a single causal change.
Explain it back
- What is the simplest accurate explanation of Foundation Mini-Project: Tiny Task List?
- Which input/state is the source of truth?
- What exact evidence distinguishes success from accidental success?
- What failure did you reproduce and how did you isolate it?
Practice before completion
Small experiment, intentional failure, explain-back
Build the smallest example that demonstrates this lesson. Then break one relevant assumption and diagnose it using terminal/DevTools evidence. Finally explain the concept without using a framework name.