Remove Hot Jobs

Manage the hot jobs list in

daily_hot_jobs.json

. Hot jobs are sticky LinkedIn listings shown at the top of the daily email, 5 per category (or 8 for Tech Lead / AI categories).

Key concepts

• current_jobs: dict of category → list of job objects. Clear a slot by removing from this list — it backfills on next run.
• blocklist: list of

  [company, title]

  pairs. Blocklisted jobs never reappear in that category.
• If a job was applied to (company is in the tracker), do NOT blocklist it — the system auto-removes tracker companies naturally.
• If a job is being dismissed without applying, blocklist it so it doesn't come back.

Categories (exact keys in JSON)

• Senior Java

• Backend Java

• Product Owner

• Assistant Project Manager

• Tech Lead / Lead Developer

• AI / GenAI Engineer

What to do based on what the user says

Remove a single job (applied or dismissed) — remove it from

current_jobs[category]

. If dismissed (not applied), also add

[company.lower(), title.lower()]

to

blocklist

.

Clear all jobs in a category — set

current_jobs[category] = []

. For each job, blocklist it unless the user says they applied to it (or it's already in the tracker).

Remove from blocklist — find and delete the matching

[company, title]

pair from the

blocklist

array.

List current hot jobs for a category — read and print

current_jobs[category]

.

Steps

1. Read

   daily_hot_jobs.json

   .
2. If the user didn't specify which jobs they applied to vs dismissed, ask — applied jobs should NOT be blocklisted.
3. Make the changes (clear slots + update blocklist as needed).
4. Write the file back.
5. Confirm: how many slots cleared, how many blocklisted, which category.

Important notes

• Blocklist entries must be

  [company.lower().strip(), title.lower().strip()]

  — lowercase, no leading/trailing spaces.
• Clearing slots triggers backfill on the next daily run (11:00 AM).
• Do NOT run the daily script after editing — changes take effect on the next scheduled run.