^{AI MARKET PULSE}
AI Could Make the Entry-Level Job Market Much Harder for New Graduates

BlackRock CEO Larry Fink warns that the class of 2026 may face a brutal entry-level job market as AI begins to automate the white-collar tasks that once helped graduates get their foot in the door. The article argues that early-career office roles are becoming less secure, while competition for remaining jobs is intensifying. At the same time, AI-driven infrastructure growth is creating demand in skilled trades and other practical fields. The deeper thesis: AI is starting to disrupt the traditional college-to-office-job pipeline, making adaptability more important than ever.

So what does that mean for you?

The message is simple: young workers may need to think beyond the default white-collar path and build skills that match where demand is going. In practical terms, that means:

• Learn to use AI tools early
• Stay open to nontraditional career paths
• Prioritize adaptability over credentials alone

The signal is clear. AI is not just reshaping established careers—it is changing how new workers enter the economy in the first place.

👉️ Read the article here

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^{WORKFLOW BUILDER}
The 30-Day Newsletter Factory

Goal: Research, draft, and schedule a full month of high-value email newsletters in a single afternoon, freeing up 10+ hours of creative grunt work.

Steps:

1. Curate Winning Topics

   Identify high-engagement trends and questions within your niche to fuel four weeks of content.

   • Prompt ChatGPT: Search for the top 5 trending topics and "how-to" questions in the [Niche] space from the last 7 days and summarize why they are currently viral.

   • ➡️ Next: Select the 4 strongest topics—one for each weekly send.

2. Build the Content Skeleton

   Create a consistent structural framework for all four newsletters to ensure brand familiarity.

   • Prompt ChatGPT: Create a 4-part newsletter outline for [Topic] that includes a personal hook, 3 actionable bullet points, a "tool of the week," and a call to action.

   • ➡️ Next: Repeat for each of your four selected topics and save them in Notion

3. Generate the First Drafts

   Expand your outlines into conversational, personality-driven emails.

   • Prompt ChatGPT: Write a 400-word newsletter based on the outline for [Topic] using a "friend-to-friend" tone and plenty of white space for mobile readability.

   • ➡️ Next: Review the drafts for your "voice" and add any personal anecdotes.

4. Optimize Subject Lines & Preheaders

   Maximize your open rates with curiosity-driven headlines for every edition.

   • Prompt ChatGPT: Write 3 "curiosity-gap" subject lines and 3 matching preheaders for each of the 4 newsletters to encourage a high click-to-open rate.

   • ➡️ Next: Choose the strongest pair for each send and paste them into your ESP (Beehiiv/ConvertKit).

5. Automate the Formatting

   Convert your text into clean, professional email layouts without the manual design struggle.

   • Prompt ChatGPT: Convert the newsletter text for [Topic] into a Markdown-formatted draft that includes bold headers and clear bullet points ready for a direct copy-paste.

   • ➡️ Next: Paste your month of content into your newsletter platform and hit "Schedule."

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^{TODAY’S PROMPT}
Build an AI Inbox System That Sorts, Replies, and Routes for You

This mega-prompt acts like an AI email operations strategist and automation architect, turning your inbox workflow, lead criteria, response needs, and tech stack into a complete inbound email automation system you can actually implement. It builds a practical blueprint for sorting messages, qualifying leads, routing conversations, and auto-replying to common emails so you can save time, respond faster, reduce manual inbox work, and avoid missing important opportunities.

👉 Use the prompt + check out my example output here

AI INBOUND EMAIL AUTOMATION — SHORT VERSION

Act as an expert AI automation architect and email workflow strategist.

Your job is to design a practical AI system that manages inbound email for my business. The system should automatically sort incoming emails, identify and prioritize leads, send safe auto-replies to common messages, route important emails correctly, and reduce manual inbox work without creating unnecessary risk.

Use the inputs below to build the system. If anything is missing, make the most reasonable assumption and state it briefly before the plan.

BUSINESS INFO
• Business type: [insert]
• What I sell: [insert]
• Main purpose of inbound email: [lead gen / support / sales / partnerships / scheduling / mixed]
• Email volume: [insert]
• Team size: [solo / small team / other]
• Biggest inbox problems: [insert]

EMAIL WORKFLOW
• Email platform: [Gmail / Outlook / other]
• Types of emails received: [insert]
• Emails that can be auto-replied to: [insert]
• Emails that must be reviewed by a human: [insert]
• Emails that should never get an auto-reply: [insert]
• Routing rules: [insert]

LEAD LOGIC
• What counts as a qualified lead: [insert]
• Lead priority levels: [hot / warm / cold / unqualified]
• Data to extract from emails: [name, company, budget, timeline, etc.]
• CRM: [HubSpot / Salesforce / Airtable / none]
• Need CRM entry: [yes / no]
• Need lead scoring: [yes / no]

AUTO-REPLY RULES
• Common message types needing replies: [insert]
• Reply tone: [professional / warm / direct / premium]
• Brand voice notes: [insert]
• Links to include: [Calendly / FAQ / intake form / other]
• Need personalized replies: [yes / no]

TOOLS
• Automation platform: [Zapier / Make / n8n / Lindy / no preference]
• AI model: [ChatGPT / Claude / Gemini / no preference]
• Other tools: [Slack / Notion / HubSpot / Calendly / etc.]
• Technical skill level: [beginner / intermediate / advanced]
• Build style: [no-code / low-code / simplest possible]

SAFETY
• Compliance needs: [none / legal / healthcare / finance / other]
• Need human approval for some replies: [yes / no]
• Need confidence threshold: [yes / no]
• Need logging or audit trail: [yes / no]
• Need fallback rules when AI is uncertain: [yes / no]

OUTPUT
Create the final answer in these sections:

1. Automation Summary  
Explain what the system does, what is automated, what stays human-reviewed, and why it fits the business.

2. Email Categories  
Define the main inbound email categories and what should happen to each one.

3. Workflow  
Map the step-by-step flow from incoming email to classification, lead scoring, reply, routing, CRM logging, and fallback handling.

4. Tool Stack  
Recommend the best tools and explain what each one does.

5. Lead Scoring  
If relevant, define hot, warm, cold, and unqualified lead logic.

6. Auto-Replies  
Explain which emails should get automatic replies, when to avoid automation, and include sample templates if useful.

7. Safety Rules  
Define confidence thresholds, human review triggers, and categories that should never be fully automated.

8. Rollout Plan  
Give the simplest version to build first, then how to improve it over time.

Make the final system practical, safe, and easy to implement. Avoid over-engineering. Prioritize speed, lead capture, clear routing, and useful automation.

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^{AI SPOTLIGHT}
Jensen Huang Just Painted an Extreme Vision of the AI Agent Future

Nvidia CEO Jensen Huang is envisioning a future where AI agents become deeply embedded in everyday work at a scale that dwarfs human headcount. Speaking at Nvidia’s GTC conference, Huang said that within a decade the company could have roughly 75,000 employees working alongside 7.5 million AI agents—a ratio of 100 agents for every human worker. In his view, these systems will not simply act like chatbots, but as autonomous software workers capable of reasoning, planning, and taking action around the clock. Nvidia is also moving to support that future by launching tools that help enterprises build and manage their own agents. Because Nvidia sits at the center of the AI economy, Huang’s comments carry weight beyond one company. The deeper thesis: AI agents are increasingly being positioned not as side tools, but as a core layer of future knowledge work.

Key Takeaways:

• Jensen Huang believes AI agents could eventually outnumber human workers at massive scale
• Nvidia is building tools to help enterprises create and deploy their own agent systems
• The broader vision of work is shifting toward humans managing fleets of always-on AI agents

👉️ Read the full article here

^{AI QUICK HITS}

🎥 A new independent film will use an AI-generated version of Val Kilmer—with his estate’s permission and compensation—marking one of Hollywood’s most high-profile tests yet of how generative AI can ethically bring a deceased actor back to the screen.

📱 Nothing CEO Carl Pei argues that smartphone apps will eventually be replaced by AI agents that understand a user’s intent, take action on their behalf, and turn phones from app-launching tools into far more proactive, personalized systems.

🧑‍💻 Google just upgraded AI Studio into a much more complete app-building environment, adding a stronger coding agent, Firebase backend support, modern web framework integrations, and persistent project memory so users can go from simple prompts to production-ready web apps in one place.

🤔 ^{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—58% were right!

Did you vote in the poll from March 18th? The bottom 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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