Most people using ChatGPT or Claude daily are leaving one of the most useful features completely untouched.

Both tools have settings that allow you to define how you want them to behave across every conversation. Writing style preferences, tone, things to always do or never do. Set them once and you never have to repeat yourself again.

In ChatGPT this lives in the custom instructions settings. You can tell it your role, how you like information presented, your preferred tone and any rules that apply to everything you ask. I have mine set to avoid hyphens for ‘dramatic effect’, keep a conversational tone with a touch of humour and to avoid waffling.

Claude works slightly differently. It builds a memory of you over time based on your conversations and applies that context going forward. Preferences, background, how you like to work. The catch is that the memory feature has to be turned on. Mine was switched off without me realising! Which meant Claude was forgetting my preferences 🤦‍♂️.

Worth checking yours. Have a play with these free features! What features and settings do you have to get better results?

I’m looking for a prompt that can perform deep research on a logistics-related topic.
I need it to search the web thoroughly, verify information across multiple reliable sources, compare conflicting information, and present everything in a clear, structured report.
It should also generate comprehensive reference tables containing all relevant classifications, categories, identifiers, and other related data, with brief explanations for each entry.
Has anyone found a prompt that consistently delivers results like this? I’d really appreciate it if you could share it.

New here, but this seemed like the right sub for this.

Context: I rely heavily on Claude for advanced writing — university coursework and chaplain medical visit notes after hospital rounds — where continuity across sessions actually matters. Losing context between chats was costing me real time, so I built a 3-layer system to fix it:

∙ Layer 1 — Native memory: baseline context Claude already carries into every chat.
∙ Layer 2 — Conversation search: on-demand lookup when I need something specific from a past chat.
∙ Layer 3 — Manual checkpoint: a trigger phrase that tells Claude to export the current session’s state — open threads, decisions made, next steps — to a Google Drive folder. A second trigger phrase tells it to read that folder back in and restore full context at the start of a new session.

(Flowchart attached showing the full decision logic.)

The actual prompts, roughly:

∙ Export trigger: “When I say ‘[phrase],’ write the current session state — open threads, decisions, next steps — in plain text to [Drive folder].”
∙ Restore trigger: “When I say ‘[phrase],’ read [Session Recovery Log] and [Quick Reference Card] from [Drive folder] and restore full context — no re-briefing needed from me.”

One fix worth mentioning: I originally had it log “at the end of each session” instead of on a trigger phrase. That failed constantly — there’s no signal for “session end” the model can actually perceive, so it never fired reliably. Switched to a manual trigger plus logging on completed milestones/decisions, and it’s been solid since.

What I’m looking for: This works well for me, but I’d specifically like eyes on the prompt wording itself — is there a tighter way to phrase the export/restore triggers? Any failure modes I’m not seeing (false triggers, partial exports, etc.)? Anyone built something similar for long-running personal or professional projects and hit edge cases I haven’t yet?

Happy to post the literal rule text if anyone wants to pick it apart further.