Phase 26 · Lesson 03

TaskFlow Broadcast Architecture

≈ 2 min core reading · 177 source/companion words
Learning contract

What you should be able to do after this

  • Explain TaskFlow Broadcast Architecture without relying on framework buzzwords.
  • Connect the lesson to the phase outcome: Add realtime synchronization without creating a second source of truth or leaking unauthorized events.
  • Reproduce the relevant behavior and verify it with evidence.
  • Diagnose at least one representative failure instead of guessing.
Figure 26.3 — TaskFlow boundary map
database/event source
Supabase Realtime channel
authorized/scoped subscription
event handler
query cache reconcile
UI
This lesson belongs to Phase 26. Keep the full request/data path visible even when today's code changes only one box.
Instructor workflow: predict first → implement the smallest slice → run it → inspect evidence → break one assumption → diagnose → explain it back. Do not copy the whole code block before understanding the first failing boundary.

TaskFlow Broadcast Architecture Volume 07 - Advanced Application Architecture

End-to-end path TaskFlow Realtime data path

User A NestJS Postgres DB trigger Realtime mutation rules + auth commit broadcast WebSocket

User B browser TanStack Query private channel invalidate/refetch

Realtime is a freshness signal. NestJS + PostgreSQL remain authoritative.

Why the event begins after commit The Task write still goes through NestJS, authorization, business rules, Repository/Prisma and PostgreSQL. A Postgres AFTER trigger emits an event only when the database change actually happens.

Topic granularity TaskFlow uses one private topic per Workspace Task stream: workspace:<workspaceId>:tasks. This avoids one channel per Task while still keeping tenant boundaries explicit.

Why the browser subscribes directly to Supabase Realtime NestJS remains the write/API authority, but the WebSocket freshness path can go directly from Supabase Realtime to the authenticated browser. We are not duplicating business logic in Realtime; we are delivering change notifications.

Failure philosophy If Realtime is unavailable, the app degrades to normal TanStack Query behavior: initial fetch, invalidation from local mutations, focus/reconnect refetch, manual refresh. That is a healthy architecture.

Executable lesson studio · architecture

Now turn the explanation into engineering skill.

TaskFlow Broadcast Architecture matters because it changes a real boundary in TaskFlow. The goal is to understand the inputs, owner, observable output, and failure modes before adding more abstraction.

By the end, you should be able to

  • Explain TaskFlow Broadcast Architecture in terms of concrete inputs, ownership, outputs, and evidence.
  • Implement or reproduce the smallest TaskFlow slice that demonstrates this architecture concept.
  • Diagnose one representative architecture failure using observable evidence instead of trial-and-error.
Figure 26.3B — Mental model
User intent
UI boundary
API contract
business rule
persistence
observable result
Read left-to-right while implementing. When debugging, walk right-to-left until the first observed fact differs from your prediction.
Code-along sequence

One coherent change at a time

  1. 01

    Restate the goal of “TaskFlow Broadcast Architecture” as one observable behavior. Write the success signal before touching code.

  2. 02

    Trace the boundary map: User intent → UI boundary → API contract → business rule → persistence → observable result. Mark the one boundary this lesson changes.

  3. 03

    Inspect the current repository state and record the exact files, route, table, or runtime involved. Avoid creating an abstraction before you can name the existing owner.

  4. 04

    Implement the smallest vertical slice. Add one coherent change, run the narrowest verification command, and read the output before continuing.

  5. 05

    Connect the slice to TaskFlow’s phase artifact: Realtime task updates that merge into TanStack Query state with scoped subscriptions and reconnect behavior.. Verify behavior from the outside as a user or API client would.

  6. 06

    Create one controlled failure that is safe to reproduce. Predict the symptom first, capture evidence, locate the earliest broken boundary, then fix only that cause.

  7. 07

    Close the reference and rebuild or explain the core change from memory. Record what you would monitor or test before trusting the same change in production.

txtBoundary trace
Input -> owner -> transformation -> observable output -> failure evidence

Do not copy this as a finished answer. Predict what each boundary does, type the smallest useful slice, run it, then compare the result with your prediction.

Verification

Prove the happy path

  1. Run the narrowest relevant command or request and require a clean exit/status.
  2. Inspect the boundary-specific evidence: terminal output, Network panel, database row/query plan, test report, container health, or deployment logs.
  3. Repeat the behavior once after the change so a one-off cached or stale result cannot masquerade as success.
Break it on purpose

Build debugging memory

  1. Events for other tenants visible to a client
  2. Change one assumption in the architecture example—identity, input, configuration, ordering, connectivity, or state—and predict the exact symptom before running it.
SymptomInvestigation path
Expected result does not appear

Return to the nearest observable boundary: input, network, process log, database, or rendered UI. Compare actual evidence with the predicted path.

A shortcut appears to fix it

Change one variable at a time and reproduce the original failure after the fix; otherwise you have correlation, not diagnosis.

Closed-reference challenge

Can you transfer the idea?

Without copying the final source, create a second small scenario that applies “TaskFlow Broadcast Architecture” to a different TaskFlow resource or input. Write the acceptance criteria first, implement it, and provide the evidence that each criterion is satisfied.

Explain-back

Answer these without reopening the solution

  1. What problem does TaskFlow Broadcast Architecture solve in TaskFlow, and what would be observably wrong without it?
  2. Which part of the architecture boundary owns the decision, and which neighboring layer must not own it?
  3. What evidence proves the happy path instead of merely suggesting it worked?
  4. Name one realistic failure or abuse case and the first place you would inspect.
  5. If requirements doubled tomorrow, which part of this design should stay stable and which part is allowed to change?
Lesson studio

Turn the reading into skill

01

Do it

Feed events into query cache updates or invalidation instead of a parallel global store.

Use the smallest change that demonstrates this lesson. Stop after it works and capture evidence.
02

Break it safely

Events for other tenants visible to a client

Predict the symptom before causing the failure. Then locate the earliest boundary where reality diverges from expectation.
03

Explain it back

Why does this responsibility live here, what input does it trust, what output proves success, and what would go wrong if another layer owned it?

If your explanation is vague, repeat the boundary trace before moving on.
Exit ticket

Before marking complete

Close the reference. Reproduce the core idea from memory or explain the exact request/data flow aloud. Then check your diff or notes for accidental shortcuts that bypass validation, authorization, error handling, or verification earned in earlier phases.