AI Operating System — Talk Resources

1 — The Master Context Prompt

Paste this into ChatGPT or Gemini. Fill in the five brackets. Save the output somewhere you can return to every Sunday.

Act as my elite Chief of Staff and AI Time Management Architect.
My goal is to build a ruthless, highly efficient weekly workflow that
maximizes my deep work and delegates or automates the rest.

Here is my context:

- Role: [Employee / Boss / Agency Owner / Freelancer / Startup Founder]
- Primary Output: [e.g., Writing code, closing sales, managing 5 direct reports, designing product architecture]
- My 'Deep Work' Hours: [e.g., 8:00 AM – 11:00 AM] — I have the most energy here.
- My 'Admin/Reactive' Hours: [e.g., 3:00 PM – 5:00 PM] — I have the least energy here.
- Key Bottlenecks: [e.g., Too many unnecessary meetings, getting stuck in my inbox, context-switching between projects]

Your task:

1. The Perfect Week — Design an optimized, block-scheduled weekly calendar
   tailored to my role and energy levels.
2. The Automation Hitlist — Identify 3 specific daily tasks I currently do
   manually that I can automate using AI tools (Zapier, Make, ChatGPT
   Actions, or Gemini Workspaces).
3. The Triage Protocol — Give me a strict framework for how to process
   incoming requests, emails, and meetings without breaking my deep work
   state.

Output the strategy clearly, prioritising high-leverage activities.

Re-run weekly. Add one line at the top each Sunday — "shipped X, two new direct reports, deep-work hours pushed to 9–12" — and the model recalibrates the system for you.

Want the full integration guide (calendar wiring + the three background automations)? It is the full Time Management in the AI Age playbook on this site.

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2 — The AI Operating System tool stack

The rule: one tool per layer, used for two weeks, before you add the next.

Research & sense-making

Tool	What it is	Start here
Perplexity	Cited, real-time AI search	✅
Exa	Semantic search built for AI workflows
Elicit	Academic research assistant
Consensus	Peer-reviewed evidence search

Prompting & reasoning

Tool	What it is	Start here
ChatGPT	Default workhorse	✅
Claude	Best for long-form writing & code review
Gemini	Best if you live in Google Workspace
Mistral Le Chat	Fast, strong open model

Automation & glue

Tool	What it is	Start here
Zapier	Easiest no-code automations	✅
Make	More power, more complexity
n8n	Self-host, full control
Pipedream	Code + no-code hybrid

Coding & shipping

Tool	What it is	Start here
Claude Code	Terminal-first AI engineer	✅
Cursor	AI-native VS Code
Bolt	Prompt to full-stack app
v0	Prompt to React UI

Copywriting & content

Tool	What it is	Start here
Claude	Best long-form writing	✅
Hemingway Editor	Tighten any draft
Notion AI	In-doc co-writer
Lex	Distraction-free AI writing

Image generation

Tool	What it is	Start here
Midjourney	Highest aesthetic ceiling	✅
ChatGPT Images	Easiest prompt-to-image flow
Ideogram	Best for posters with text
Flux	Open-weights, self-hostable

Video generation

Tool	What it is	Start here
Runway	Pro-grade video model	✅
Sora	Long, coherent shots
Kling	Strong motion fidelity
HeyGen	Avatar-driven video

Audio & voice

Tool	What it is	Start here
ElevenLabs	Best AI voice cloning	✅
Suno	Prompt-to-song
Otter.ai	Meeting transcription
Descript	Edit audio like a doc

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3 — Recommended reading list

The essays, posts, and books that shaped the worldview behind the talk.

Essays & posts (read first, free)

• "Situational Awareness" — Leopold Aschenbrenner. The clearest argument for what the next 5 years of AI look like.
• "Machines of Loving Grace" — Dario Amodei. Anthropic's CEO on what a positive AI future actually looks like.
• "The Bitter Lesson" — Rich Sutton. Why scale + general methods keep winning. The foundational AI worldview.
• "What's our problem?" — Tim Urban. The mental-model layer underneath strategic thinking.
• "Aggregation Theory" — Ben Thompson. Why the internet keeps producing winner-take-most companies (and why AI will too).
• "How to Do Great Work" — Paul Graham. The operator's reading of how impactful work happens.

Books (read deeper)

• The Coming Wave — Mustafa Suleyman. The political economy of AI and synthetic biology.
• Co-Intelligence — Ethan Mollick. Practical use of AI in real work, real teams.
• The Singularity Is Nearer — Ray Kurzweil. Long-arc thinking on where compute takes us.
• Atomic Habits — James Clear. The compounding systems layer behind any AI workflow.
• The Hard Thing About Hard Things — Ben Horowitz. Operator playbook for building anything serious.
• Range — David Epstein. Why generalists win in fast-moving fields. The AI era favors range.

Newsletters worth subscribing to

• Stratechery — Ben Thompson on tech strategy
• Import AI — Jack Clark's weekly AI brief
• One Useful Thing — Ethan Mollick on practical AI
• The Pragmatic Engineer — Engineering & AI tooling
• Latent Space — Deep AI engineering interviews
• Torch99 — Yours truly. AI strategy, GEO, the AI-first economy.

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4 — The slide deck

The deck link drops here right after the live talk on May 23, 2026.

🔥 Slide deck — coming soon (within 24 hours of the talk). If you are reading this before May 24, 2026, the deck is still on Liwaa's laptop. Refresh this page after the talk — or watch your inbox: we email it directly to every email that unlocked this page.

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Where to go next

You now have:

• The Master Context Prompt to turn AI into your weekly operator
• The full AI Operating System tool stack with one clear starting point per layer
• The reading list behind the worldview
• The slide deck (or the queue for it)

If you want a 1:1 with Liwaa, book through the Tomohi mentor app — first session is free for Marhaba Talk attendees.

If you want to make sure AI search itself sees you correctly, run a free audit on 99Visibility — the live GEO platform for the AI search era.

If you want raw thinking on AI strategy, GEO, and product building, you are already on the Torch99 list. Reply to the welcome email any time — it goes straight to Liwaa.

— Liwaa, Torch99