Issue #60: Agents That (Actually) Work, Agent Swarms, Ghosts in the Machine

Good morning.

There’s a funny moment right before a product becomes real.

Everyone still calls it a “concept,” but it’s already happening in the wild.

That’s where we are with AI in general right now when it comes to the mainstream.

You and I know better.

Agents aren’t hypothetical. Video generation isn’t cute anymore.

Advertising infrastructure isn’t catching up. It’s being rebuilt around data privacy and LLM orchestration.

What’s wild is how casual it all looks.

Using AI effectively is now a fundamental expectation of everyone at Shopify.

A Gen-4 video model quietly solves the single hardest problem in AI filmmaking.

WPP swallows a company just to improve on artificial-intelligence capabilities.

And then there’s OpenAI teasing a new “next” that sounds suspiciously like a product vertical, not just another model.

This week’s issue is about AI crossing multiple thresholds all at once. From tool to teammate. From toy to infrastructure. From viral demo to actual workflow.

The questions are shifting too—from “can it do this?” to “how do we integrate it without breaking trust, workflow, or UX?”

And maybe more importantly: Who owns the interface now?

—Sam

IN TODAY’S ISSUE 👨‍🚀 

• Shopify’s CEO Mandates AI Knowledge and Usage.

• Real AI Agents completing tasks

• The future of privacy-focused advertising

• OpenAI’s holdoff for the next big model

• Runway’s Gen-4 AI video character memory

• Good prompt for Market Research with Deep Research

Let’s get into it.

The Silent Takeover: How AI is Becoming Business as Usual

(This is a shorter version of the full issue, available to free subscribers and on the web. If you’re a Cortex subscriber, you get the full issue below—if you’re reading on the web, make sure you’re logged in. Cortex opens up once a month, at the end of the month.)

The Corporate AI Mandate: Shopify's Bold Move

Shopify CEO Tobi Lütke has fundamentally changed the company's relationship with AI, elevating it from optional tool to required competency. 

This represents perhaps the first major public example of a company fully integrating AI into its DNA rather than treating it as an add-on feature. 

The implications extend far beyond Shopify's walls, setting a precedent that other companies will likely follow to remain competitive.

This shift represents a fundamental redefinition of workplace productivity and competency.

• AI usage is now mandatory, factoring into performance reviews.

• Teams must prove a problem can't be solved with AI before requesting additional headcount.

• Product development must begin with AI-driven exploration.

• Requirements apply company-wide, including executive leadership.

• This approach treats AI as fundamental infrastructure, not optional technology.

From Conversation to Action: AI Agents Enter the Real World

The leap from theoretical AI capabilities to practical implementation is happening now. 

AI agents capable of executing complex multi-step tasks across different software platforms are operational and accessible. These systems don't just chat about tasks - they complete them with remarkable autonomy, fundamentally changing the relationship between humans and technology.

• Agents can control applications like Adobe Creative Suite to create finished content

• Systems translate from high-level intent to finished products across multiple platforms

• They function effectively as AI-powered employees capable of solving problems independently

• Available platforms include Manus, Convergence, Genspark, Fay, and Kairos

• "Agent swarms" allow simultaneous execution of hundreds of parallel tasks

• Successful implementation requires addressing latency, accuracy, and trust barriers

If you haven’t already, you should sign up to these general-purpose Agents and try them out:

• Manus: https://manus.im/

• Convergence: https://convergence.ai/

• Genspark: https://www.genspark.ai/

• Fay: https://beta.fay.work/

• Kairos: https://www.kairos.computer/

Another good option to try would be Lindy.ai, as they have “Agent Swarms” built into their flows.

Speaking of Agents: I’ve said many times that the real powerful Agents will be specialized for specific business domains.

For example, Will Bot, billed as “Your 24/7 Personal AI Marketing Agent”.

I’m not getting paid to talk about this Agent, I just want you to realize where we’re at:

“Will Bot understands your marketing data and helps you make better decisions faster, bridging the gap between creative and media teams.”

Quick rundown:

• Knows Everything: Connects across all data sources; understands and learns your workflow.

• Easy Control: Can take action in your various ad accounts on behalf of you.

• Always On: 24/7 instant access to all your data, wherever, whenever you need it.

• Instant Insights: Access any chart, metric, or analysis with a single sentence.

Will Bot can unite every ad channel, vision-level creative analytics, and first-party measurement tools to surface what drives ROI—without leaving Slack.

There will be 100+ Agents like Will Bot within months.

For every business area.

(I’ve talked about this coming for the past year or so, in previous issues).

Everyone’s working on specialized Agents.

The New Privacy Paradigm: WPP's Strategic Data Play

WPP's acquisition of InfoSum signals a fundamental shift in how advertising will function in an increasingly privacy-conscious world. 

This move highlights the growing importance of clean room technology that enables personalization without compromising user privacy. 

It demonstrates a recognition that the advertising landscape is permanently changing in response to both regulatory pressures and consumer expectations.

For marketers, this acquisition underscores the urgency of developing first-party data strategies that don't rely on third-party cookies. The future belongs to brands that can balance personalization with privacy.

The Next AI Leap: OpenAI's Mysterious Announcement

Sam Altman's cryptic teaser suggests OpenAI is preparing to unveil something significant. 

While specific details remain unknown, the company's track record indicates whatever is coming will likely push AI capabilities forward substantially. 

This pattern of continuous advancement creates both opportunities and threats for businesses built around AI technologies.

The cyclical nature of these releases creates a challenging dynamic for AI-dependent businesses.

 Features that seem advanced today can quickly become baseline expectations tomorrow. 

Companies that have built their value proposition around capabilities that could be incorporated into foundation models may need to rapidly evolve their offerings.

The Character Breakthrough: Runway's Gen-4 Video Revolution

Runway's Gen-4 has solved one of the most persistent problems in AI-generated video: maintaining consistent characters across scenes. 

This breakthrough fundamentally changes what's possible with AI in visual content creation. 

By enabling recognizable, persistent characters, Gen-4 allows for the development of ongoing narratives and brand identities that were previously impossible with AI tools.

This advancement transforms AI video from a novelty to a practical business tool. 

The ability to maintain visual consistency across content enables the creation of branded series, recurring characters, and cohesive campaigns at scale. 

In brief:

• Characters now appear consistently across frames and scenes with stable identities.

• Enables the creation of recurring stories and coherent brand narratives.

• Represents a workflow revolution for content creators and marketers.

• Companies should design character systems like mascots or stylized representatives.

• Organizations can build modular video libraries instead of disconnected one-offs.

• Technology enables content scaling without proportional hiring.

• AI video has evolved beyond experimental use to become brand-safe and business-ready.

Deep Research Prompt for Market Intelligence

Give this prompt a spin with either Perplexity or Deep Research (ChatGPT, Grok 3).

It’s a pretty decent prompt for uncovering market intelligence.

If you use Perplexity, you can select to search for social results (social media, etc.)

You have to add a couple of details at the beginning of it, namely information about your Target Audience and Offer (information about what you’re selling).

Here’s the prompt:

# Customer Psyche Analysis
This framework conducts extensive psychological and behavioral research to uncover authentic customer mindsets, challenges, and journeys for crafting emotionally resonant, conversion-focused messaging that aligns with your specific offering.

----------------------------------------

## PARAMETERS:
- Target Market = "DEFINE_TARGET_MARKET"
- Your Offering = "DEFINE_YOUR_PRODUCT_OR_SERVICE"

## I. Market Intelligence Gathering
Perform a detailed and thorough investigation into the {Target Market} in relation to the problem space your {Offering} addresses. Your aim is to extract genuine, emotion-driven insights directly from potential customers, using their authentic language.

Data collection sources:
- Discussion platforms (Reddit, Quora, specialized communities)
- Social channels (Twitter/X, Instagram, YouTube comments, Facebook groups)
- Customer testimonials and competitor product reviews
- Industry publications, podcasts, and topical discussions
- Q&A sites and help forums related to your offering category

## II. Essential Discovery Areas
### 1. Comprehensive Audience Profile
- Demographic composition (age ranges, income brackets, education levels)
- Value systems and belief structures
- Aspirational goals and personal definitions of success
- Notable achievements and significant setbacks
- External factors they perceive as obstacles to their fulfillment
- Conscious and unconscious biases
- Core worldview regarding relationships, purpose, and fulfillment

### 2. Key Challenge Identification
- What primary pain points emerge consistently in audience discussions?
- What language patterns indicate their most significant struggles?
- How do they rank or prioritize their related problems?
- What emotional intensity surrounds different challenges?
- Which challenges align most directly with your offering's solutions?
- What hidden or unstated problems can be inferred from their discussions?
- What timeframe do they believe their problems have existed or worsened?

### 3. Awareness Spectrum Analysis (Schwartz Framework)
- **Completely Unaware**: Do they recognize they have the identified challenge? What symptoms do they describe without naming the problem?
- **Problem-Aware**: How do they articulate their challenge? What terminology do they use?
- **Solution-Aware**: What general approaches do they believe might help? What categories of solutions are they exploring?
- **Product-Aware**: Which specific products/services are they comparing? What features matter most to them?
- **Most Aware**: What brands/solutions do they already trust? What would make them take immediate action?

### 4. Offer Alignment Analysis
- How does your offering directly address their identified key challenges?
- What aspects of your solution might they be skeptical about based on past experiences?
- What unique elements of your offering solve problems they don't realize they have?
- What language from their discussions could be mirrored in describing your solution?
- Where on the awareness spectrum are your ideal customers, and how should your messaging adapt?

### 6. Belief Systems & Influence Factors
- Who do they trust for advice in this domain?
- What proof elements would they find most convincing?
- What social or external validation matters most to them?
- What objections consistently appear in their discussions?
- What competing priorities might prevent action?
- What timeline do they expect for results or implementation?

## III. Deliverable Components
### 1. Key Challenge Summary:
- Primary identified challenges ranked by prevalence and emotional intensity
- Verbatim quotes illustrating how the audience describes each challenge
- Analysis of challenge evolution (how problems develop or compound over time)
- Direct connections between identified challenges and your offering's solutions

### 2. Voice-of-customer evidence organized by:
- Emotional intensity (frustration, hope, skepticism, desperation)
- Awareness level (from unaware to most aware)
- Problem specificity (general discomfort vs. precise challenge)

### 3. Comprehensive customer journey map showing:
- Initial problem recognition triggers
- Information-gathering methods
- Decision-making criteria
- Implementation concerns
- Success measurements

### 4. Messaging framework recommendations:
- Key benefits that resonate across awareness levels
- Objection-handling approaches backed by customer language
- Trust-building elements specific to your offering category
- Emotional triggers that connect with core audience values
- Specific language patterns to adopt or avoid

### 5. Competitive positioning insights:
- Perceived gaps in existing solutions your offering addresses
- Specific frustrations with competitors you can highlight
- Unique advantages customers are actively seeking
- Price sensitivity thresholds and value perceptions

Try it out, let me know what you think.

(If you’re a Cortex subscriber, you get the full issue with tips, details, prompts, and more below).

Let’s get personal for a second.

The reason I write Bionic Business is because I know what it feels like to be building something while the ground is shifting—hard and fast. 

You're focused on growth, customers, team issues, product velocity, and then the entire environment changes. 

Quietly. In the background. At first.

Then, suddenly, it's right at your door.

I built an Executive Assistant Agent (we called her “Jill”) a couple of years ago, before Agents were a thing. Lots of work, lots of development. Lots of time.

Now? 

You can just pay $20-40 per month for one and don’t have to build a thing (unless you want to).

I’m fortunate to be about 2-3 years ahead in AI, and have been for a few years now. 

It’s thrilling and terrifying at the same time. 

By the time I’ve uncovered an opportunity with AI, something changes and it’s not even worth building. 

I’m in the process of creating a fully autonomous business (a couple of them, actually) because now, finally, the tech is here (if you’re on the bleeding edge).

That’s not a brag or even a humble brag. 

I’m just telling you this because: 

Sometimes the best strategy is to wait out some of the AI technology, instead of chasing after shiny AI objects. 

Double-down on using AI to help you with distribution and market share, primarily. 

This week wasn’t about big, flashy model drops. It was about things getting real.

• AI agents didn’t just demo, they completed tasks.

• A video model didn’t just improve quality, it created characters you can actually use.

• Shopify didn’t announce an “AI initiative”, they rewrote how their entire company works.

These aren't signals that the future is coming. These are signs that it's already here, and being distributed unevenly across ready companies.

If you're a founder, a marketer, or a builder, here's the funny truth:

You don’t have to be ahead of everyone. But you do have to stop acting like this stuff is optional.

So here's one smart thing to walk away with:

Pick one AI capability this week and figure out how to turn it from an experiment into a default.

Not a test. Not a pilot. Just make it part of how your business runs. 

Because eventually, the companies that win won't be the ones with the best AI tools.

They’ll be the ones where nobody even calls it AI anymore.

It’ll just be how they work.

And by then, it'll be too late to catch up.

Talk soon,
Sam Woods
The Editor