## Summary
Starts from a security finding on the background-job status endpoints
and folds in the most important issues surfaced by a follow-up review of
the same feature area (categorization backfill, bulk rule re-evaluation,
automation-rule apply).
Each change is its own commit.
## Changes
### 1. `fix(security)` — scope job-status cache keys to the owning user
The categorization, bulk re-evaluation, and apply status endpoints
looked jobs up by a bare job UUID with no user scoping. Any
authenticated user who obtained another user's job id could poll its
progress payload. Cache keys now include the owning user's id, so a
status request keyed by the polling user's id resolves only that user's
own jobs — a mismatched owner falls through to the existing 404. No
ownership store or extra lookup. Cross-user isolation tests added for
all three endpoints.
### 2. `fix(automation-rules)` — re-check `only_uncategorized` at apply
time
The apply flow cached a match snapshot for up to 15 min (keyed only by
`rule.updated_at`) and applied the rule's category to every id in it
without re-checking eligibility. A transaction categorized *after* the
snapshot (by the user, a sibling rule, or a concurrent AI backfill) was
silently re-categorized and stamped `category_source=Rule`. Now
re-filtered through `shouldSkipForOnlyUncategorized()` at apply time;
skipped rows are no longer counted as changed.
### 3. `perf(automation-rules)` — memoize rule set per user in
`applyRules()`
Bulk re-evaluation calls `applyRules()` once per transaction, and each
call re-queried the user's whole rule set + labels — an N+1 scaling with
transaction count (the sibling apply job already loaded rules once).
Memoized per user for the service instance's lifetime (resolved fresh
per job, so rules created mid-run are intentionally not seen).
Query-count test asserts one `automation_rules` query regardless of
transaction count.
### 4. `fix(transactions)` — stop polling when the job never starts
The re-evaluate and apply pollers rescheduled on any non-terminal
status, including `pending`. If the queue worker is down the job never
runs, `failed()` never fires, and the client polled for the full
hour-long TTL with a stuck spinner. Now gives up after 30 consecutive
`pending` ticks (~30s), mirroring the guard the AI-categorization poller
already has. Long `processing` runs are unaffected.
### 5. `test(automation-rules)` — cover apply job execution and failure
branches
`ApplySingleAutomationRuleJob` was only asserted to be *pushed*; its
`handle()` body and `failed()` branch had no coverage, and
`ReEvaluateTransactionRulesJob::failed()` was untested too. Added direct
`handle()`/`failed()` tests pinning the progress-cache payloads.
## Deferred follow-ups (surfaced by review, not in this PR)
- **Consolidate the three frontend pollers onto `usePollJobStatus`** —
they hand-roll `setTimeout` loops and don't tear down on unmount (can
`setState`/`onClose` after the dialog closes). The hook already exists
and is unmount-safe; routing all three through it would also make the
`pending` cap unit-testable. The cap in change #4 currently mirrors the
already-shipped AI poller and is not separately unit-tested.
- **`noteAlreadyPresent()` uses a substring match**
(`AutomationRuleService`) — a rule note that is a substring of an
existing note is silently not appended. Should compare note lines
exactly.
- **No dedup/lock on concurrent apply/re-evaluate jobs** — note appends
are a non-atomic read-then-write, so two concurrent jobs can duplicate a
note. Category/label writes are already idempotent.
- **Transient 404 → false "failed"** — a mid-run cache
eviction/TTL-expiry (or the deploy window of change #1, where an
in-flight job's pre-deploy key is orphaned) makes the poller surface a
false failure. Retry a few times on transient errors before giving up.
- **`matches()` pagination** advances `next_offset` by fetched rows, not
page-window size — deleted ids can stall infinite scroll before reaching
`total`.
- **"Apply to N" count / encrypted-skip counts** can be stale or
under-report vs what's actually processed.
- **Job-trait convention drift** between the three jobs (modern
`Queueable` vs legacy trait stack).
## Testing
- `vendor/bin/pint --test` — pass
- `bun run format` / `bun run lint` — pass (one pre-existing unrelated
warning in `chart.tsx`)
- Affected Pest suites (apply, re-evaluate, evaluation, rule,
categorization, apply-rule-suggestions) — 94 tests pass
## Summary
Lets existing (non-onboarding) users discover and manage AI
categorization, gated behind a new Pennant feature flag. When a flagged
paid user grants consent, every uncategorized transaction is categorized
in the background with live, on-screen feedback.
Enable per user: `php artisan feature:enable AiConsentSettings
user@example.com`
## What's included
**Feature flag**
- New `AiConsentSettings` Pennant flag (off by default), exposed to the
frontend via the shared `features` prop.
**Billing settings (`/settings/billing`)**
- When the flag is active, a section to grant or revoke AI consent
(checkbox → `POST`/`DELETE /ai/consent`).
**Transactions page**
- A consent prompt rendered as the first row of the transactions table
(new `DataTable` `topRow` slot), styled with the shared gradient
`AiSparkleIcon`. Only shown to paid users with the flag who haven't
consented yet.
- An inline "Enable AI" button records consent without leaving the page.
**Backfill on consent**
- Granting consent dispatches a queued
`CategorizeUncategorizedTransactionsJob` that categorizes all of the
user's uncategorized transactions, **most recent first**, recording
progress in the cache.
- The transactions page polls a new status endpoint (`GET
/ai/categorization/{jobId}/status`): visible uncategorized rows show a
spinner + pulse while the backfill runs, categories stream in via
partial reloads, and a toast tracks `processed / total` until
completion.
## Notes / decisions
- **Polling, not websockets** — the project has no broadcasting
configured; this mirrors the existing `ReEvaluateTransactionRules` job +
status-endpoint pattern.
- The backfill job is kept separate from
`CategorizeOnboardingTransactionsJob` so the onboarding pass stays
progress-free (small, commented duplication).
- Reuses the existing `AiCategorizationGate` (config kill-switch + pro
plan + active consent) — free users and disabled-AI never dispatch the
job.
- Not included (YAGNI): cancelling an in-flight backfill on revoke;
persisting the spinner across full page reloads.
## Testing
- New Pest coverage: feature-flag exposure, billing/transactions consent
props, consent-triggered dispatch + gating, the status endpoint
(200/404), job progress recording, and recent-first ordering.
- `php artisan test --exclude-testsuite=Browser` passes (one unrelated,
pre-existing `DashboardTest` failure on `main`).
- Pint, Prettier and ESLint clean.
Víctor Falcón