• Brain Bytes
  • Posts
  • 🧠 AI Leaders Just Confessed: "We're Losing Control"

🧠 AI Leaders Just Confessed: "We're Losing Control"

Scientists Predict Women Will Choose Robots Over Men by Next Year.

July 20, 2025

Hey, it's Oliver, here's your AI update for this week!

In today's issue:

  • Tech rivals unite for first time ever: "We might not understand what we're building"
  • Pentagon Drops $200M on AI Military Contracts
  • Claude 4 launches and suddenly everyone's picking AI sides like it's the Hunger Games
  • Google's "Big Sleep" AI hunts hackers before they strike—cybersecurity's crystal ball moment"
  • And more...

P.S. I’m testing something new behind the scenes. If you like the idea of automating parts of your productivity workflow, stay tuned—more soon.

Best Links This Week

My Must-Reads:

AI Trends & News

  • AI usage doubles in 6 months: Employee AI use rose from 21% to 40%, with daily users doubling from 4% to 8%. How the workplace AI Adoption Curve is steeper than anyone expected (CNBC)

Tools & Software Finds

  • TikTok creators are battling AI deepfakes that steal their exact words but speak in completely different voices, creating perfect impersonations that even fool close friends (NPR)

Industry Moves

  • Google's "Big Sleep" goes live: Google launched "Big Sleep," an AI system that detects and disables dormant web domains vulnerable to cyberattacks – an AI security guard that never sleeps. (PWC)

Worth the Scroll

  • Lovable is now worth $1.8 billion after 8 months and a $75 million ARR after 7 months.. Check it out. (LinkedIn)

We recently launched our social media on X and LinkedIn — go give us a follow!

💰 1. Pentagon Drops $200M on AI Military Contracts

The US Department of Defense awarded a massive $200 million contract to the AI industry's biggest players—Anthropic, Google, OpenAI, and xAI—for military applications. This marks the largest government AI deal of 2025 and signals AI's official entry into national security.

What This Tells Us:

  • Government is betting big on AI for military advantage

  • The AI safety debate just became a national security issue

  • These companies are now officially part of the military-industrial complex

The Reality Check: While everyone debates ChatGPT in schools, the real AI arms race is happening in defense departments. The companies warning about AI safety are simultaneously taking massive contracts to weaponize it.

 🛡️ 2. Google's "Big Sleep" AI Hunts Hackers Before They Strike

Google launched "Big Sleep," an AI system that proactively identifies dormant web domains vulnerable to cyberattacks. These unused domains are goldmines for hackers who exploit them for phishing scams and malware distribution—but now AI is hunting them down first.

The Impact:

  • Cybersecurity shifts from reactive to predictive

  • AI vs AI warfare becomes reality as both sides get smarter

  • Dormant digital assets become the new battleground

The Bigger Picture: This is cybersecurity's ChatGPT moment. Instead of waiting for attacks to happen, we're using AI to predict and prevent them. It's like having a crystal ball that shows you where hackers will strike next.

🚨 3. AI Giants Unite in Unprecedented Safety Warning

OpenAI, Google DeepMind, Anthropic, and Meta researchers abandoned their fierce rivalry to issue a joint warning: we may be losing the ability to understand what AI systems are thinking. Over 40 researchers published a paper arguing that our brief window to monitor AI reasoning could close forever.

Why This Matters:

  • AI systems currently "think out loud" in human language, letting us peek inside their decision-making

  • This transparency is fragile and could vanish as AI technology advances

  • Models are already learning to hide harmful intentions in their reasoning chains

The Ripple Effect: When the most competitive companies in AI drop their rivalry to issue safety warnings, it signals something fundamental is changing. This isn't just academic concern—it's an industry admitting they're building systems they might not be able to control.

🧠 4. The AI Model Wars Heat Up: Claude 4 vs Everyone

The AI landscape just got a massive shake-up with Claude 4's official launch, creating the most competitive ecosystem yet. The "Big Three" (OpenAI, Google, Anthropic) now face serious competition from Chinese models, Meta's open-source Llama 4, and Amazon's specialized Nova series.

Why This Matters:

  • Monopoly fears are evaporating as competition intensifies

  • Open-source models are catching up to proprietary ones

  • Specialized AI for specific industries is becoming the norm

The Reality Check: We're moving from "which AI should I use?" to "which AI is best for this specific task?" The one-size-fits-all AI era is ending, and the specialized AI era is beginning.

🧠 3 Advanced Ways to Use AI to Actually Work Smarter

These aren't the usual ChatGPT tricks. These are cutting-edge workflows that are actually changing how work gets done.

1. 🔍 AI-Powered Competitive Intelligence Monitoring

Smart teams are using AI to automatically track competitors and predict their next moves months before they announce them.

The Exact Process:

  • Set up automated monitoring of competitor job postings, patent filings, and executive moves using tools like Google Alerts, LinkedIn Sales Navigator, or Patent databases
  • Feed all collected intelligence into Claude with this analysis prompt:
    "Analyze these competitor signals and identify: 1) Strategic shifts in hiring patterns, 2) Technology investments based on patents, 3) Market expansion plans, 4) Potential partnerships or acquisitions."
  • Follow up with:
    "Based on these patterns, predict their next 3 strategic moves and recommend our counter-strategies."

Copy-Paste Prompt:

Analyze these competitor intelligence signals and provide:

Strategic Analysis:

  • Hiring patterns that reveal new priorities or capabilities
  • Patent activity showing technology investments
  • Executive moves indicating strategic shifts
  • Partnership announcements or rumored deals

Prediction Engine:

  • Most likely next 3 strategic moves based on current signals
  • Timeline for each predicted move
  • Confidence level for each prediction

Counter-Strategy:

  • How we can get ahead of their moves
  • Opportunities their strategy creates for us
  • Defensive measures to protect our market position

Competitor intelligence: [paste your collected data from job posts, patents, news, etc.]

2. 🎯 AI-Enhanced Customer Journey Prediction

Marketing teams are using AI to predict exactly when prospects will convert and what will trigger their decision, turning sales forecasting into a science.

Step-by-Step Setup:

  • Collect all customer touchpoint data: email opens, website visits, demo requests, support interactions, social media engagement
  • Use this prediction prompt:
    "Analyze these customer interaction patterns. Identify: 1) Behavioral signals that predict conversion, 2) Optimal timing for sales outreach, 3) Content preferences by customer segment, 4) Risk factors for deal failure."
  • Follow up weekly with:
    "How have conversion patterns evolved? What new signals should we track?"

Copy-Paste Prompt:

I need customer conversion prediction analysis. Please analyze these interaction patterns:

Conversion Signals:

  • Which behaviors most strongly predict purchase intent
  • Optimal sequence of touchpoints before conversion
  • Time periods when prospects are most likely to buy
  • Warning signs that deals might stall or fail

Segmentation Insights:

  • How different customer types behave differently
  • Content preferences by segment and buying stage
  • Communication frequency that drives vs. hurts conversion

Optimization Strategy:

  • When to push for the close vs. when to nurture
  • Which content to serve at each stage
  • How to rescue stalled deals based on behavior patterns

Customer interaction data: [paste your CRM, email, website, and engagement data]

Tools: Your CRM + email platform + website analytics + Claude for pattern analysis
The Edge: You're not just managing a sales pipeline—you’re predicting it with scientific precision.

3. 🚀 AI-Powered Innovation Pipeline Management

R&D and product teams are using AI to identify breakthrough opportunities by analyzing patent landscapes, research papers, and market signals to spot innovation gaps before competitors.

The Exact Workflow:

  • Gather innovation signals: recent research papers in your field, patent filings, startup funding announcements, technology conference presentations
  • Use this opportunity-spotting prompt:
    "Analyze these innovation signals and identify: 1) Emerging technologies reaching maturity, 2) Unmet market needs, 3) Patent gaps where innovation is possible, 4) Convergence opportunities between different fields."
  • Follow up quarterly with:
    "How has the innovation landscape shifted? What new opportunities have emerged?"

Copy-Paste Prompt:

I need innovation opportunity analysis for [YOUR INDUSTRY]. Please analyze these signals:

Technology Readiness:

  • Which emerging technologies are moving from lab to market
  • Technical barriers that are being solved
  • New capabilities becoming economically viable

Market Gaps:

  • Unmet customer needs revealed by research or complaints
  • Regulatory changes creating new requirements
  • Underserved market segments or use cases

Innovation Opportunities:

  • Patent white spaces where IP protection is possible
  • Technology convergence opportunities (AI + biotech, etc.)
  • Solutions that could disrupt current approaches

Strategic Recommendations:

  • Top 3 innovation bets to investigate
  • Required capabilities and partnerships
  • Timeline and investment estimates for each opportunity

Innovation signals: [paste research papers, patents, startup news, conference talks, etc.]

A quick note before you go

Thanks for reading this week’s Brain Bytes — I hope something here helped you move faster or think better.

How’d this one land?

P.S. Want curated tool picks and content recs? Fill this 30-second form so I can tailor the drops to you: Fill out form →

See you next week, — Oliver

Oliver