Walmart CEO prediction on AI + is there an AI bubble?

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AI HUSTLE | SEPTEMBER 27 2025

Today, we're cutting through the noise and showing you how to automate your inbox, summarizing emails with action points and priority levels, and sending a consolidated digest straight to Slack. Imagine reclaiming hours from email triage every week! And that's just the start – the broader AI landscape is a whirlwind of innovation, investment, and intense debate.

From C-suite discussions at retail giants like Walmart about the inevitable reshuffling of the global workforce, to a speculative boom in AI infrastructure that has investors both giddy and nervous, and cutting-edge labs where AIs are learning to "think" like us through virtual worlds – every corner of the industry is buzzing.

Let’s dive into the implications for your business, your career, and the future of work itself.

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The Hustle: AI Email Assistant: Tame Your Inbox with Smart Summaries

The Goal: To automatically read and process all new emails from the past 12 hours, summarizing their content, identifying action points, sender, and priority, then delivering all this information as a concise Slack message with direct links to each email.

The Tools:

• Automation Platform: Make.com or n8n

• Email Service: Gmail, Outlook 365, or any IMAP/POP3 compatible email client.

• AI Language Model: OpenAI API (GPT-4o/GPT-3.5-turbo) or Anthropic API (Claude 3 Haiku/Sonnet).

• Communication Platform: Slack

Core Concept: This workflow will act as your personal email triage assistant. Every 12 hours, it will fetch new emails, use AI to extract key information and prioritize, and then consolidate it into a single, actionable digest sent directly to your chosen Slack channel.

Workflow Breakdown (Applicable to both Make.com and n8n)

Step 1: The Trigger - Fetching Recent Emails

• Schedule: Set your workflow to run every 12 hours.

• Email Node:

  • Make.com: Use the "Gmail > Watch emails" or "Microsoft 365 Mail > Watch for emails" module.

  • n8n: Use the "Gmail > New Email" or "Microsoft Outlook Mail > New Email" node.

• Configuration:

  • Connection: Connect your email account.

  • Folder: Specify the folder to watch (e.g., "Inbox").

  • Time Filter: Crucially, configure the node to only fetch emails received within the last 12 hours. Both platforms allow you to set a filter based on the "Received Date" or similar timestamp.

  • Unread Only (Optional but Recommended): You might want to filter for only unread emails to avoid processing already handled messages.

Step 2: AI Processing - Summarize & Prioritize Each Email

For each email fetched in Step 1, this step will run.

• Loop/Iterator (Implicit for Make, Explicit for n8n): If your email node fetches multiple emails, the subsequent nodes will automatically process each one in sequence (Make) or you'll use a "Split In Batches" or "Item Lists" node if you want to explicitly manage parallelism in n8n.

• AI Node:

  • Make.com: Use the "OpenAI > Create a Completion" or "Anthropic > Create a Completion" module.

  • n8n: Use the "OpenAI > Chat Completions" or "Anthropic > Chat Completions" node.

• The Master AI Prompt (Crucial!): This prompt instructs the AI on what information to extract and how to format it.

  'You are an AI assistant designed to summarize emails and extract key information. For the following email, provide: 1. A concise summary (2-3 sentences). 2. A list of clear, numbered action points, if any. If no action points, state "No explicit action points." 3. The sender's name and email address. 4. A priority level (Low, Medium, High, Urgent) based on the content and urgency implied. Format your response strictly as follows: --- **Summary:** [Summary of email content] **Action Points:** 1. [Action Point 1] 2. [Action Point 2] ... **Sender:** [Sender Name] (<[Sender Email]>) **Priority:** [Priority Level] --- Email Content: [Insert the email body/plain text from the previous email node here]’

   

• Extract Data: The AI will return a block of text formatted exactly as requested. You'll need to parse this output.

  • Make.com: Use a "Text Parser > Match pattern" or "Data store" module, or a custom script if needed. Often, the output can be directly mapped.

  • n8n: Use a "Code" node (JavaScript) or a "Split to Batch" and "Set" node with regex to extract each section (Summary, Action Points, Sender, Priority) into separate fields. This makes it easier to format the Slack message later.

• Generate Email Link: Most email nodes provide a direct link (URL) to the email in the web interface (e.g., Gmail's View URL or Outlook's Web Link). Make sure to capture this for each email.

Step 3: Collect & Format for Slack

Since you want to send one Slack message with all summaries, you need to collect the results from all processed emails.

• Aggregator Node:

  • Make.com: Use an "Aggregator" module.

  • n8n: Use a "Merge" node with the "Merge By Amount" or "Merge By Property" option, or a "Code" node to build a single message payload.

• Message Construction: Within the aggregator or a subsequent node, build a single text block for your Slack message.

  '*--- Your Email Digest (Last 12 Hours) ---* *Email 1:* *Subject:* [Email 1 Subject] *Link:* [Email 1 Link] [AI Summary from Step 2 for Email 1] *Email 2:* *Subject:* [Email 2 Subject] *Link:* [Email 2 Link] [AI Summary from Step 2 for Email 2] ... and so on for all emails ... --- *End of Digest*’

   

  Hint: You can use Slack's Markdown for formatting (bold, italics, lists).

Step 4: Send to Slack

• Slack Node:

  • Make.com: Use the "Slack > Create a Message" module.

  • n8n: Use the "Slack > Post Message" node.

• Configuration:

  • Connection: Connect your Slack workspace.

  • Channel: Specify the channel where you want to receive the digest (e.g., #inbox-digest or a private channel to yourself).

  • Message Text: Map the aggregated message constructed in Step 3 to the message body.

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🚀 The AI Pulse: 3 Signals to Watch This Week

• Walmart CEO Predicts AI Will Reshape "Nearly Every Job." Doug McMillon, CEO of retail behemoth Walmart, isn't shying away from AI's transformative power, stating it will change nearly every job within the company. While Walmart aims to maintain its 2.1 million global workforce over the next three years, the composition of these jobs will shift dramatically. The company is actively developing AI tools like chatbots and creating new "agent builder" roles, even as it automates more warehouse and back-of-store tasks.

  • The Hustle Take: This isn't just about robots replacing low-skill jobs; it's about AI elevating and altering roles across the board, from customer service to strategic planning. For your hustle, this signals a critical need for "AI literacy" and "AI integration skills." Instead of fearing job displacement, focus on how you can leverage AI tools to enhance your current role or create entirely new value. Look for opportunities to become an "AI agent builder" within your niche, designing workflows and prompts that make existing processes more efficient or unlock new capabilities. The future favors those who can work with AI, not against it.

• AI Spending Reaches Epic Levels – Is a Bubble Forming? The artificial intelligence boom has ignited one of the costliest building sprees in history, with tech giants pouring hundreds of billions into new data centers, chips, and energy infrastructure. Companies like OpenAI are committing trillions in future data center investments, even as their current revenue remains comparatively tiny. This level of speculative investment, reminiscent of the dot-com bubble's fiber-optic overbuilding, raises questions about whether these expenditures will ever pay off, and if we're heading for a significant correction.

  • The Hustle Take: The "picks and shovels" companies (like Nvidia) are minting money, but the ultimate profitability of AI applications is still a question mark. For your hustle, this indicates a "winner-take-all" dynamic at the foundational infrastructure level. If you're building an AI product, focus intensely on demonstrable ROI for your users. The market will demand clear value, not just hype. Be wary of taking on significant debt for unproven AI ventures, and prioritize solutions that offer immediate, tangible benefits. The underlying tech might be speculative, but your application needs to solve a real, pressing problem.

• The Virtual Worlds Where AI is Making Its Next Big Leap. To move beyond being "book smart" (learning from text and images), AI needs to get "street smart" through "world models." This involves training AIs in realistic virtual environments where they can learn, make mistakes, and predict outcomes, much like humans and animals. Companies like Google DeepMind with Genie 3 are creating photo-realistic, open-world virtual landscapes for AI training, and startups like Waabi are building entire simulated worlds to train self-driving trucks. This approach is crucial for embodied AIs (robots, autonomous vehicles) and is seen as key to achieving Artificial General Intelligence (AGI).

  • The Hustle Take: This is where AI moves from software to tangible, physical impact. For your hustle, this trend unlocks a massive opportunity in "simulation and digital twin development." If AIs need virtual worlds to learn, then the businesses that build, manage, or provide data for these simulations will become invaluable. Consider how you can apply simulation technologies in your industry, whether it's for training AI-powered processes, optimizing complex systems, or even creating digital twins of physical assets. The ability to model and predict in a virtual space will be critical for the next generation of AI-driven innovation.Share your thoughts, comments, or ideas! We read every email.

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