Phase 5.5. Completes the lifecycle after submission: prepare, communicate, chase.
Interview preparation gets a durable, user-owned store. There were already two
per-application AI stores, InterviewPrepNote and AiWorkspaceNote, but both are
caches that regenerate when their context signature changes — anything a user
typed into them would eventually be overwritten. InterviewPrepItem is the side
nothing regenerates, covering company research, technical notes, behavioural
answers, STAR examples and the user's own questions in one table, because those
categories differ only by label and adding one must not need a migration. Each
item records whether the user wrote it or accepted a suggestion, and an
IsPrepared flag makes the section double as the preparation checklist.
Generation stays in the existing AiWorkspaceService "interview" module, appended
to AiInteraction as before. A suggestion is history until the user adds it as a
prep item; opening the section generates nothing.
Follow-up reuses what exists rather than adding a tracker. The date is
JobApplication.FollowUpAt, the same field RulesEngine and the reminder hosted
service already act on, so reminders keep working with no new wiring. The task
stays an ApplicationChecklistItem in the follow-up category — the section counts
open tasks without owning them. The record is a FollowUpSet JobEvent, the same
type the rest of the app emits.
Communication is untouched: Correspondence already owns recruiter contacts,
history and notes, and the workspace already mounted it.
The timeline interpreter learned five more types — InterviewScheduled,
InterviewCompleted and OfferReceived as milestones, FollowUpCreated and
FollowUpCompleted as routine, deliberately outside the milestone spine so it
stays a summary of what actually happened. JobEvent remains the history source.
InterviewPrepItems is reconciler-owned with a no-op migration, guarded on
JobApplications, and verified on a fresh MariaDB 11: int AUTO_INCREMENT primary
key, varchar owner and title, tinyint flag, datetime(6), composite index inside
the key limit.
371 backend tests, 128 frontend tests, Release build and the production build all
pass locally.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Phase 5.3. Three read-only reads that answer "how suitable is this job", "how
does my experience match", "what am I missing", "what happened previously".
Timeline (GET /{id}/timeline) is an interpretation layer over JobEvent, which
stays the source of historical truth. Each row gains a readable summary, a
category and a milestone flag; events group by day. Milestones are returned
unfiltered, because narrowing the detail must not hide what actually happened.
Job analysis (GET /{id}/analysis) extracts role, company, location, employment
type, seniority, salary, technologies, skills, responsibilities and keywords
from the advert, reusing the existing SkillTagger so the vocabulary matches the
job importer. It also reports what the advert does NOT say, which is usually the
more useful half.
Career matching (GET /{id}/match) feeds the master CareerProfile into the same
JobCvMatchService the CV builder uses, so one application scores identically
whichever surface asks. It returns the score, matched and missing skills, and
which experience and project entries are the evidence for each match.
All three are deterministic and own no data — no new table, no new column, and
nothing writes to the CareerProfile, a CvVariant, or the JobApplication. The AI
narrative stays where it already was, in AiWorkspaceService's job-analysis and
career-match modules, generated only when the user asks and versioned by the
append-only AiInteraction history. Opening a section costs nothing and changes
nothing.
Frontend adds Timeline, Analysis and Match sections to the workspace, sharing
one loader so loading, empty and error states are consistent. The deterministic
answer renders first, with the AI panel below it.
345 backend tests, 104 frontend tests, type check, production build all pass
locally.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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