^{AI SPOTLIGHT}
Most Companies Aren't Seeing the AI Savings They Expected

A new survey from Bain & Company found that many businesses investing heavily in AI are struggling to generate the cost savings they projected. Among companies actively measuring AI-driven savings, 40% reported reductions of 10% or less, despite many organizations increasing spending based on assumptions that earlier AI investments would pay for future rounds of deployment. Bain surveyed 951 companies across nine industries and found that nearly half of large organizations are funding new AI initiatives based on savings that have yet to materialize. The firm argues that the technology itself is often working, but companies are running into challenges around data accessibility, implementation, and measuring real business outcomes. The deeper thesis: the next phase of AI adoption may be less about deploying more tools and more about proving measurable business value from the ones already in place.

Key Takeaways:

• Bain's survey found that 40% of companies measuring AI savings achieved cost reductions of 10% or less

• Nearly half of large organizations are reinvesting in new AI projects based on expected savings rather than realized results

• Data access, integration challenges, and unclear ROI are emerging as major barriers to scaling AI successfully

👉️ Read the article here

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^{AI SPOTLIGHT}
Uber Burned Through Its AI Budget in Just Four Months

Uber has introduced a new policy that caps employee spending on AI coding tools at $1,500 per month per tool, including products like Claude Code and Cursor. The move comes after the company reportedly exhausted its entire annual AI budget in just four months, following an aggressive push that encouraged employees to use AI as much as possible and even tracked usage on internal leaderboards. At the same time, Uber executives have acknowledged that measuring AI's real productivity impact remains difficult, with leadership noting it's often hard to connect AI usage directly to customer-facing improvements. The decision highlights a growing challenge facing enterprises as AI costs rise: proving that increased spending is translating into measurable business value. The deeper thesis: the AI race is entering a new phase where companies may be forced to focus less on adoption and more on accountability.

Key Takeaways:

• Uber now caps employee spending on AI coding tools at $1,500 per month per tool

• The company reportedly exhausted its annual AI budget within the first four months of the year

• Growing AI costs are increasing pressure on companies to demonstrate clear returns on their investments

👉️ Read the full article here

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^{TODAY’S PROMPT}
Build a Complete Cold Outreach Campaign in Minutes

This mega-prompt acts like an elite outbound sales strategist, turning a simple description of your offer into a complete cold outreach system. It builds personalized email sequences, subject lines, follow-up messages, and a sending cadence so you can spend less time writing and more time booking conversations.

👉️ See the example inputs and outputs here

Act as a world-class B2B outbound sales strategist,
direct-response copywriter, and lead generation
expert.

Your job is to create a complete cold outreach
campaign that turns my offer into a predictable
lead-generation system.

Business Name: [Business Name]
Offer: [Product or Service]
Target Customer: [Target Customer]
Problem Solved: [Problem]
Desired Outcome: [Outcome]
Proof: [Case Studies, Results, Testimonials]
Call To Action: [Book a Call, Demo, Audit, Reply]
Outreach Channel: [Email, LinkedIn, or Both]
Tone: [Professional, Friendly, Direct]
Number of Follow-Ups: [Number]

Create the following:

1. Ideal Prospect Profile
• Best-fit job titles
• Company characteristics
• Buying signals
• Common pain points
• Likely objections

2. Outreach Positioning
• Unique angle
• Core value proposition
• Key differentiator
• Primary messaging pillars

3. Subject Lines
Generate 15 subject lines using curiosity,
personalization, direct-response,
problem-focused, benefit-focused, and
pattern-interruption approaches.

4. Initial Outreach Email
Create a short version, a standard version,
and a highly personalized version. Each
should have a strong hook, clear value
proposition, natural CTA, and conversational
tone.

5. Follow-Up Sequence
Write [Number of Follow-Ups] follow-up emails.
Each follow-up should introduce a new angle,
add new value, avoid repetition, and end with
a simple CTA.

6. LinkedIn Outreach
Create a connection request, first message,
follow-up #1, and follow-up #2.

7. Objection Handling
Write responses for:
• Not interested
• No budget
• Already using another solution
• Bad timing
• Send more information

8. Campaign Cadence
Provide the ideal send schedule, spacing
between follow-ups, campaign length, and
recommended sequence.

9. Optimization Plan
Provide:
• 5 personalization ideas
• 5 A/B tests
• Key metrics to track
• Biggest mistakes to avoid

Write everything in a natural, human voice.
Avoid corporate jargon, generic sales
language, and obvious AI phrasing. The final
campaign should be ready to deploy with
minimal editing.

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^{AI QUICK HITS}

💸 GitHub Copilot users are revolting after Microsoft's shift to token-based billing triggered reports of monthly costs jumping from tens of dollars to hundreds—or even thousands—for heavy AI users.

🧑‍💻 Microsoft just launched Scout, a new OpenClaw-inspired AI assistant for Microsoft 365 that learns how you work over time, remembers preferences, and can automate tasks across your inbox, calendar, desktop, and browser.

🏢 OpenAI is pushing deeper into enterprise software with six new Codex plug-ins for jobs like sales, investing, product design, and data analytics, as knowledge-worker adoption grows more than three times faster than developer usage.

📈 Anthropic has confidentially filed paperwork with the SEC for a potential IPO, giving the AI company the option to go public after regulators complete their review.

⚡ Tennessee just passed a law requiring large data centers to pay for their own power infrastructure, signaling that states are starting to push back against the massive energy demands created by AI's data center boom.

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🤔 ^{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—70% were wrong!

Did you vote in the poll from June 1st? 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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