^{AI MARKET PULSE}
AI Startups Are Reaching $10M ARR at Record Speed

A new wave of AI-native startups is hitting $10 million in annual recurring revenue in as little as three months, a pace that would have seemed extreme just a few years ago. Stripe’s latest data shows that more companies than ever are launching, charging customers faster, and scaling revenue at unprecedented speed — with 2025 cohorts growing 50% faster than the prior year and double the number reaching $10M ARR within months. While investors caution that durable growth matters more than rapid spikes, the pattern is undeniable: AI dramatically compresses time from idea to revenue.

So what does that mean for you?
AI isn’t just accelerating product development — it’s accelerating revenue timelines. The edge now belongs to founders who move quickly and validate fast:

• Launch and charge customers early
• Focus on recurring revenue models
• Prioritize retention over vanity growth

The signal is clear. AI lowers the friction to build and deploy, enabling startups to reach meaningful revenue milestones at record speed. Those who pair rapid execution with sustainable retention can scale faster than previous generations; those who chase speed without durability risk short-lived spikes instead of lasting growth

👉️ Read the article here

AI Isn’t the Edge. Execution Is.

Most people are playing with AI.
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^{WORKFLOW BUILDER}
The Meal Prep Master

Goal: Transform a single photo of your fridge and a few dietary goals into a fully customized, zero-waste weekly meal plan.

Steps:

1. Catalog Your Inventory

   Use AI Vision to "see" what you already have and prevent overbuying.

   • Prompt ChatGPT: I am uploading a photo of my fridge. List every ingredient you see and categorize them into proteins, vegetables, and condiments.

   • ➡️ Next: Upload your fridge photo and verify the list for any hidden items.

2. Set Your Nutritional Guardrails

   Define your health goals to ensure the plan fits your lifestyle.

   • Prompt ChatGPT: Based on the ingredients identified, create a 7-day meal plan that is [e.g., high-protein / under 2,000 calories] and uses at least 80% of what is currently in my fridge.

   • ➡️ Next: Review the meal titles and swap any dishes you don't like.

3. Generate the Recipe Book

   Get step-by-step instructions for every meal in your new plan.

   • Prompt ChatGPT: Provide simple, 5-step recipes for the first 3 days of this meal plan, ensuring each meal takes less than 30 minutes to cook.

   • ➡️ Next: Save these recipes to a dedicated folder in your notes app.

4. Build the Gap-Fill Grocery List

   Identify the few missing pieces needed to complete your 7-day cycle.

   • Prompt ChatGPT: Identify which essential ingredients are missing from my current inventory to complete this 7-day plan and create a categorized shopping list for them.

   • ➡️ Next: Copy this list into your reminders or grocery app.

5. Master Your Prep Schedule

   Organize your cooking time to minimize daily effort.

   • Prompt ChatGPT: Create a "Sunday Prep" schedule that shows me exactly which ingredients to chop or pre-cook today to save the most time during the work week.

   • ➡️ Next: Set a 30-minute timer and knock out your prep work.

Pro Tip (Upgrade):
Use SaneBox to filter out distracting promotional emails and grocery newsletters, keeping your focused "Meal Prep Master" reminders at the top of your inbox.

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^{TODAY’S PROMPT}
Design a Day That Actually Works

This mega-prompt operates like a disciplined productivity architect, converting your priorities, energy patterns, and constraints into a structured daily execution blueprint. It transforms your schedule and workload into a clear performance system that aligns deep work with peak focus, integrates AI for leverage, and forces realistic trade-offs—cutting through reactive busyness, eliminating calendar chaos, and delivering a sustainable high-output plan without hustle culture, rigidity, or burnout-driven optimization.

👉 Use the prompt + check out my example output here

MEGA-PROMPT: AI Daily Productivity System

CLEAR ASK
You are to act as a high-performance productivity architect, behavioral systems designer, and AI workflow strategist.

Your task is to design a realistic, AI-assisted daily schedule that maximizes output while protecting energy, focus, and long-term sustainability.

The output must be:
- Structured and time-blocked
- Adaptive to energy fluctuations
- Aligned with stated priorities
- Free of unrealistic “perfect day” fantasy
- Focused on leverage, not busyness
- Immediately implementable without clarification

Design a system — not just a schedule.


CONTEXT & PURPOSE
The purpose of this prompt is to:
- Eliminate reactive workdays
- Align time with actual priorities
- Protect deep work capacity
- Integrate AI for automation and leverage
- Increase output without increasing stress

This is not a motivational productivity speech.
This is not a rigid 5AM routine template.
This is not hustle culture optimization.

Assume the user wants:
• High daily output
• Reduced mental clutter
• Realistic pacing
• Built-in recovery
• AI-assisted leverage

The goal is high output without burnout.


DETAILED INPUT REQUIREMENTS (USER MUST FILL THESE IN)
Use the inputs exactly as provided.
If something is missing, make reasonable assumptions and clearly state them.

CORE PRIORITIES
• Top 3 Professional Priorities:
• Top 2 Personal Priorities:
• Long-Term Goal (if relevant):

CURRENT WORK STRUCTURE
• Job Type (Remote / Hybrid / In-person / Entrepreneur):
• Required Work Hours:
• Meeting Load (Low / Moderate / High):
• Commute Time (if any):

ENERGY PROFILE
• Peak Energy Time:
• Low Energy Time:
• Sleep Duration:
• Workout Schedule (if any):

TASK PROFILE
• Deep Work Tasks:
• Shallow/Administrative Tasks:
• Recurring Obligations:

AI TOOLS AVAILABLE
• AI Tools I Currently Use:
• Automation Tools (if any):
• Open to Learning New Tools? (Yes / No):

CONSTRAINTS
• Family Obligations:
• Time Restrictions:
• Health Constraints:
• Other Non-Negotiables:

TIME HORIZON
[Immediate / 30 days / Long-term system build]


OUTPUT REQUIREMENTS (MANDATORY FORMAT)

1. PRODUCTIVITY SNAPSHOT
- Core time constraints
- Energy strengths
- Bottlenecks limiting output
- Immediate leverage opportunities

2. OPTIMIZED DAILY SCHEDULE (TIME-BLOCKED)
- Morning Structure
- Deep Work Blocks
- Admin/Reactive Windows
- Recovery Periods
- Shutdown Routine

Include specific time ranges and purpose for each block.

3. AI LEVERAGE INTEGRATION
- Tasks to automate
- Tasks to accelerate with AI
- Prompts or workflows to use
- Estimated time saved per day

4. ENERGY ALIGNMENT STRATEGY
- What to schedule during peak energy
- What to schedule during low energy
- Recovery triggers
- Burnout prevention guardrails

5. DISTRACTION DEFENSE SYSTEM
- Rules for meetings
- Notification boundaries
- Context switching limits
- Decision fatigue reduction

6. 7-DAY IMPLEMENTATION PLAN
- Day 1 adjustments
- Week 1 system testing
- What to track
- What to refine

7. ONE HIGH-LEVERAGE HABIT
The single habit that creates disproportionate daily gains.

8. ONE HARD TRUTH
A direct observation about current productivity behavior.

9. ONE-SENTENCE CORE INSIGHT
A concise, memorable rule for sustainable high output.


ADDITIONAL INSTRUCTIONS (CRITICAL)
You must:
- Avoid unrealistic scheduling density
- Avoid extreme discipline prescriptions
- Prioritize sustainability
- Distinguish essential vs optional tasks
- Structure for mobile readability
- Design for long-term consistency
- Flag overcommitment risks
- Keep recommendations realistic

If trade-offs are required between intensity and sustainability, choose sustainability.
If assumptions are made, state them explicitly.


FINAL QUALITY CHECK
Before delivering the answer, verify that:
- The schedule is realistic
- Energy alignment is logical
- AI leverage is clearly integrated
- Burnout risk is minimized
- No major revision would be required
- The system is immediately usable

The user should finish feeling:
“My day finally works for me — and I can execute at a high level without burning out.”

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^{AI SPOTLIGHT}
Claude Cowork Is Moving From Chatbot to Enterprise Infrastructure

Anthropic is expanding Claude Cowork from a research release into a full enterprise-grade productivity platform, adding connectors to tools like Google Drive, Gmail, and DocuSign along with customizable plugins that encode institutional workflows. Rather than positioning it as just another chatbot, Anthropic is framing Cowork as a context-aware assistant embedded directly into daily office systems. While fears of job displacement linger, company leaders say widespread labor disruption hasn’t materialized yet — though impacts may be uneven. The shift isn’t about novelty; it’s about integration. The same AI interface that answers prompts can now operate inside company infrastructure, shaping how knowledge work actually gets done.

Key Takeaways:

• Claude Cowork now integrates directly with enterprise tools
• Custom plugins encode institutional workflows and knowledge
• AI productivity tools are evolving into embedded infrastructure

My Take:

This isn’t about smarter chat — it’s about system-level integration. When AI plugs directly into internal tools and workflows, it becomes operational infrastructure rather than an optional add-on. The edge won’t belong to companies casually experimenting with chatbots; it will belong to those embedding AI into their daily systems, where context and execution compound over time.

👉️ Read the full article here

^{AI QUICK HITS}

📘 Meta just signed a massive multiyear deal with AMD to deploy up to 6 gigawatts of AI chips across its data centers—alongside millions of Nvidia processors—as it ramps up $135 billion in AI spending and diversifies suppliers to fuel its growing computing demands.

🪖 The Pentagon is pressuring Anthropic to loosen its AI safety guardrails for military use—threatening to label the company a supply chain risk or invoke the Defense Production Act—setting up a high-stakes showdown over government leverage, vendor dependence, and who ultimately controls the rules governing advanced AI systems.

🍎 Apple is investing over $500 billion across the U.S., including building a new Houston factory to assemble AI servers for its data centers, a move aimed at strengthening its Apple Intelligence infrastructure, expanding domestic manufacturing, and potentially reducing reliance on overseas production amid rising tariffs.

🤔 ^{Which image is real?}

One of these images is real, and one was created with AI. Vote for which one you think is real, and tell us why you voted that way.

The last edition’s results—54% were right!

Did you vote in the poll from February 23rd? The top image was real! Go back and see the photos here. So what do you think? Are you getting better at spotting AI vs. not?

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