🎮 The Next Input — Issue #161

In partnership with

⚡ The Briefing — 60 sec

• ChatGPT finally offers $100/month Pro plan Good middle ground for the AI serious founder. Not cheap enough to be casual, not absurd enough to feel like a vanity tier either.

• ‘It feels as if I’ve made a new best friend’: my experiment with AI journalling This is an exercise I may try for a month myself. A diary that talks back sounds slightly ridiculous until you realise it might actually help people reflect with more consistency than they do alone.

• Project Glasswing It speaks for itself. Anthropic is not just shipping models now; it is moving deeper into the security and infrastructure layer with a heavyweight coalition around Mythos Preview.

🛠️ The Playbook — The AI Reflection Engine

Mission
Build AI workflows that do more than answer questions by helping people think better, document better, and operate with more intention.

Difficulty
Intermediate

Build time
3–5 hours

ROI
Better decisions, cleaner thinking, and a much stronger bridge between daily AI usage and actual long-term leverage.

0) Why This Matters

There are at least three different versions of serious AI usage emerging.

One is practical operator tooling. OpenAI’s new $100 plan sits squarely in that zone: more serious than Plus, less excessive than the top-end tier, and explicitly built around heavier Codex usage for people doing real work with it. TechCrunch says the new plan offers 5x more Codex than Plus, while the $200 tier remains available with higher limits.

Another is reflective usage. The Guardian’s journalling experiment is light on spectacle but interesting for a different reason: AI is increasingly being used not just to execute work, but to mirror thought, emotion, and habit back to the user. That feels small until it isn’t.

And then there is the infrastructure play. Anthropic’s Project Glasswing brings together AWS, Apple, Cisco, CrowdStrike, Google, JPMorganChase, Microsoft, NVIDIA, Palo Alto Networks, and others to secure critical software, using Claude Mythos Preview to find and fix vulnerabilities at scale. Anthropic says it is committing up to $100M in usage credits and $4M in direct donations to open-source security organizations.

So the move is not just “use AI more.”

It is:

• use AI to sharpen daily work

• use AI to improve thinking, not just output

• build systems that turn personal utility into organisational edge

1) Architecture

2) Workflow

1. Capture raw thoughts, tasks, or observations through typing, dictation, or journalling.

2. Run that material through an AI reflection prompt to extract patterns, themes, and next actions.

3. Separate reflective insight from operational action so not every thought becomes a task.

4. Convert the useful outputs into documents, plans, reminders, or decisions.

5. Review weekly to see what the AI surfaced that was genuinely useful versus what was just pleasant noise.

6. Expand the workflow only when it starts improving clarity, execution, or decision quality.

3) Example Prompts

Daily Reflection Prompt

You are my reflection partner.

Review the journal entry below and return:
1. the main emotional or strategic themes
2. anything I may be avoiding
3. the one most useful action for tomorrow
4. one question I should sit with

Keep it honest, not flattering.

Journal entry:
[insert entry]

Founder Debrief Prompt

You are helping a founder think clearly.

Given the notes below:
- identify signal versus noise
- identify recurring concerns
- identify where emotion is distorting judgment
- suggest one practical next step

Notes:
[insert notes]

Weekly Pattern Prompt

You are reviewing a week's worth of entries.

Find:
- repeated themes
- recurring blockers
- energy patterns
- decisions I keep circling without making

Return the answer in bullet points only.

Action Extraction Prompt

You are converting reflective notes into execution.

From the notes below:
- extract real tasks
- ignore vague intentions
- prioritise only what materially matters
- flag anything that needs more thought before action

Notes:
[insert notes]

4) Guardrails

• Do not confuse reflection with execution.

• Keep the AI honest, not comforting.

• Review patterns over time, not just one entry at a time.

• Never let journalling become an excuse to avoid decisions.

• Treat personal AI workflows as systems, not rituals.

• Keep high-stakes decisions grounded in reality, not just elegant wording.

5) Pilot Rollout — 3 hours

1. Pick one capture habit you can sustain for two weeks: voice notes, journalling, or end-of-day debriefs.

2. Create one reflection prompt and one action-extraction prompt.

3. Run the workflow daily for 10–14 days.

4. Store outputs in one place so patterns can be reviewed together.

5. Compare what the AI surfaced against what actually mattered that week.

6. Keep only the parts of the workflow that sharpen thinking or improve follow-through.

6) Metrics

• Number of entries captured per week

• Percentage of extracted actions actually completed

• Repeated themes identified

• Decision clarity improvement

• Time from reflection to action

• Ratio of useful insights to vague output

• Weekly self-rated usefulness of the workflow

Pro Tip: The best AI reflection workflow should not make you feel smarter. It should make you clearer.

🎯 The Arsenal — Tools & Platforms

• ChatGPT Pro ($100) · strong middle ground for founders and operators who need more serious daily capacity without jumping straight to the top tier; TechCrunch reports it is aimed at heavier Codex usage and offers 5x more Codex than Plus.

• Claude · excellent for reflective prompting, structured critique, and deeper thought-partner workflows · Anthropic

• Project Glasswing · clear signal that Anthropic is building far beyond chat, with a major security coalition and access to Mythos Preview for defensive cybersecurity work.

• Notion / docs / notes apps · simple place to store entries, review patterns, and turn insight into action · Notion

• Voice capture tools · the easiest way to reduce friction and get better raw material into the system before the day disappears

Copy-paste prompt block:

You are helping me build an AI Reflection Engine.

For the workflow below:
1. identify the best capture method
2. identify how AI should reflect back themes and patterns
3. identify how actions should be extracted
4. identify what should stay reflective and not become a task
5. identify the top 5 risks of building a useless self-help loop
6. propose a 2-week pilot
7. define success metrics

Workflow:
[insert workflow here]

Return the answer in markdown with sections for:
- Workflow summary
- Capture method
- Reflection design
- Action extraction
- Risks
- Pilot rollout
- Metrics

💡 Free Office Hours

If you want to move from using AI as a chatbot to using it as an actual thinking and execution layer, I run free office hours to help design workflows that are useful, grounded, and worth keeping.

Book here: https://calendly.com

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🕹️ Game Over

The next level of AI might not just be better answers. It might be better self-awareness, better decisions, and fewer sloppy loops.

— Aaron Automating the boring. Amplifying the brilliant.

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