By skyforbes Type random prompt in → get random answer out → complain it’s “mid”.
I got bored of that. So I stopped treating it like a toy and turned it into a personal operating system instead.
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Step 1 – One core “brain”, not 1000 prompts
Instead of hoarding prompts, I built a single core spec for how ChatGPT should behave for me:
• ruthless, no-fluff answers
• constraints-aware (limited time, phone-only, real job, not living in Notion all day)
• default structure:
• Diagnosis → Strategy → Execution (with actual next actions)
This “core engine” handles:
• tone
• logic rules
• context behaviour
• safety / boundaries
Every chat starts from that same brain.
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Step 2 – WARCORE modules (different “brains” for different jobs)
On top of the core, I added WARCOREs – domain-specific operating modes:
• Business Warcore – ideas, validation, offers, pricing, GTM
• Design Warcore – brand, layout, landing pages, visual hierarchy
• Automation Warcore – workflows, Zapier/Make, SOPs, error paths
• Factory Warcore – I work in manufacturing, so this one thinks like a plant/process engineer
• Content / Creator Warcore – persona, hooks, scripts, carousels, content systems
Each Warcore defines:
• how to diagnose problems in that domain
• what answer format to use (tables, checklists, roadmaps, scripts)
• what to prioritise (clarity vs aesthetics, speed vs robustness, etc.)
So instead of copy-pasting random “guru prompts”, I load a Warcore and it behaves like a specialised brain plugged into the same core OS.
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Step 3 – Field modes: LEARN, BUILD, WAR, FIX
Then I added modes on top of that:
• LEARN mode –
Explain the concept with teeth. Minimal fluff, just enough theory + examples so I can think.
• BUILD mode –
Spit out assets:
prompts, landing page copy, content calendars, SOPs, scripts.
Less talk, more ready-to-use text.
• WAR mode –
Execution-only.
Short, brutal: “Here’s what you do today / this week. Step 1, 2, 3.”
• FIX mode –
Post-mortem + patch when something fails.
What broke, why, what to try next, how to simplify.
A typical interaction looks more like this:
[Paste core engine + Business Warcore snippet]
Mode: WAR
Context: small F&B business, low budget, phone-only, inconsistent content
Task: 30-day plan to get first paying customers and build a reusable content system.
The answer comes out structured, aligned with my constraints, not generic “10 tips for marketing in 2024”.
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What changed vs normal prompting
Since I started using this “OS + Warcore” approach:
• Way less “ChatGPT voice” and generic advice
• Answers actually respect reality (time, energy, device, job)
• I can jump between:
• business planning,
• content creation,
• factory/workflow issues,
and still feel like I’m talking to the same brain with different modes
• I reuse the system across chats instead of reinventing prompts every time
It stopped being “ask a question, hope for the best” and became closer to running my own stack on top of the model.
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Why I’m posting this here
I’m curious how other people are:
• turning ChatGPT into persistent systems, not just Q&A toys
• designing their own “OS layer” on top of LLMs
• using domain-specific configs (like my Warcores) to handle different parts of their life/work
If anyone’s interested, I can share:
• a stripped-down WARCORE template you can adapt,
• or how I combine Business + Content Warcore to plan and execute creator / side-business stuff.
How are you systematising your AI usage beyond single prompts?