Issue #74: The AI Swarm Stack for a One-Person Business

Good morning.

A couple of weeks ago, I watched a solopreneur manage a 6-figure launch with zero employees.

I gave him the design and architecture, and he built it out (with my guidance).

No VA team. No contractors. No pulling all-nighters.

Just 12 AI agents working in perfect synchronization.

While he was at his kid's baseball game, one agent noticed a competitor's price drop and alerted another agent…

Which analyzed the impact and recommended a counter-move to a third agent…

Which updated his pricing and drafted an email to his list explaining the new value prop.

By the time he checked his phone in the fourth inning, the response was already implemented. Sales were up 23%.

This is delegation to intelligent systems that think, adapt, and execute together.

The age of the swarm has arrived.

And today, I'm showing you how to build your own. Not in theory. Not with complex frameworks.

But with actual prompts you can paste into Claude (or ChatGPT) right now and automation blueprints you can implement this week.

While everyone else is asking ChatGPT to write emails, you'll be deploying agent teams that run entire business functions.

Let's get into it.

— Sam

IN TODAY’S ISSUE 🤖 

• The Intelligence Gap: Why single AI tools are already obsolete

• The Swarm Method: How to design multi-agent systems that actually work

• 15-Minute Implementation: Build your first swarm in Claude (no code required)

• Real Swarm Blueprints: Steal these exact systems already generating revenue

• The Stack: Tools and tactics to scale from manual to automated

Let’s get into it.

(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).

Why Your AI Tools Are Failing You

Let me paint a picture you've probably lived.

Monday morning. You fire up ChatGPT to help with customer support tickets. It writes a decent response. 

You copy, paste, tweak, send. Next ticket. Repeat. By ticket #15, you realize you're not saving time at all, you're just adding steps.

Or maybe you've gone deeper. Built some Zapier flows. Connected your CRM to your email tool. Set up some IF/THEN logic. 

It works great... until a customer asks something slightly outside your pre-defined rules. The whole system breaks. You're back to manual mode.

Here's the uncomfortable truth: 

Single-purpose AI tools can't handle real business complexity.

Your business doesn't run on isolated tasks. It runs on interconnected processes. A support ticket is a potential churn signal, a product feedback opportunity, a chance to upsell, a data point for your roadmap.

But your AI assistant? It just sees text to respond to.

That's the gap. And it's why smart operators are moving beyond solo AI tools to something fundamentally different: swarms.

Enter the Swarm: Your Digital Team

Think about how you'd handle that support ticket if you had a full team.

Your support rep would handle the immediate issue. Your customer success manager would check if this customer is at risk. Your product manager would log the feature request. Your data analyst would track patterns across similar tickets. Your sales rep might spot an upgrade opportunity.

Five people, five perspectives, one coordinated response.

Now imagine each of those people is an AI agent. Specialized. Focused. But connected. That's a swarm.

And here's what changes everything: you can build this today with tools you already have.

The 4-Layer Architecture That Makes Swarms Work

Before we get to the implementation, you need to understand the architecture. Every effective swarm follows this pattern, whether it's handling customer support or managing a million-dollar ad campaign.

Layer 1: Input Agents (The Sensors)

These are your scouts. They're out in the world gathering information and bringing it back in a format other agents can work with. They don't make decisions or analyze anything—they just collect and structure.

I watched an e-commerce brand deploy input agents that monitored 47 competitor sites. Every price change, every new product, every out-of-stock notice got captured and structured. The humans found out about competitor moves before the competitors' own teams did.

Layer 2: Analysis Agents (The Brains)

This is where intelligence happens. These agents take the raw, structured data and find the patterns, insights, and opportunities hiding inside.

One SaaS company I work with has analysis agents that process every customer interaction. They don't just tag sentiment—they identify the specific moment a happy customer becomes a flight risk. They catch the subtle language shifts that happen 3-4 weeks before a cancellation. Stuff no human would notice across thousands of conversations.

Layer 3: Action Agents (The Hands)

Insights without action are just interesting observations. Action agents take the analysis and do something with it. Write the email. Update the CRM. Adjust the pricing. Post the response.

The key here? They don't think—they execute. One venture-backed startup uses action agents to write and send 400+ personalized investor updates monthly. Each one references specific metrics that investor cares about. The founder spends 20 minutes reviewing instead of 20 hours writing.

Layer 4: Monitor Agents (The Watchers)

This is what most people miss, and it's what makes swarms self-improving instead of self-destructing. Monitor agents track what's working, what's failing, and what needs human intervention.

They're your quality control, your performance tracker, and your escalation system all in one. When something goes wrong, they don't just alert you—they tell you exactly what went wrong and often fix it themselves.

Your First Swarm: Built in Claude Projects (15 Minutes)

Enough theory. Let's build something.

We're going to create a Customer Intelligence Swarm that monitors all your customer touchpoints and turns chaos into clarity. This exact system helped a B2B SaaS reduce churn by 34% in 30 days.

Step 1: Create Your Swarm Headquarters

Open Claude and create a new project. Call it "Customer Intelligence Swarm" or whatever makes sense for your business. This is where your agents will live and coordinate.

Step 2: Deploy Your Agent Team

Add this as a project instruction. This is your swarm's DNA:

You are a coordinated swarm of 4 specialized agents working together to extract customer intelligence. Each agent has a specific role and passes information to the next agent in the chain.

AGENT 1 - INPUT PROCESSOR:
Your job is to take messy, unstructured customer feedback and turn it into clean, structured data. Extract:
- Customer identifier (name, email, or ID)
- Date and time of feedback
- Channel (email, chat, review, social, etc.)
- The complete raw feedback
- Initial sentiment score (1-10, where 10 is ecstatic and 1 is furious)
- Key topics mentioned (product features, support issues, pricing, etc.)
- Urgency level (immediate, soon, whenever)

Don't interpret or analyze—just structure. Think of yourself as a court reporter.

AGENT 2 - PATTERN ANALYZER:
You receive structured data from Agent 1. Your job is to find the patterns humans miss. Look for:
- Recurring themes across multiple customers
- Problems that cluster together
- Features that generate the most passion (positive or negative)
- The specific language patterns of happy vs. unhappy customers
- Emerging issues (mentioned more this week than last week)
- Silent satisfaction (what happy customers DON'T complain about)

Group similar issues together and calculate frequency. A problem mentioned by 3 enterprise customers matters more than one mentioned by 10 free users.

AGENT 3 - INSIGHT GENERATOR:
You take patterns from Agent 2 and turn them into actions. For each pattern, determine:
- The root cause (not just the symptom)
- The business impact if left unaddressed
- A specific fix with implementation steps
- Quick wins vs. long-term solutions
- Response templates for common issues
- Which team should own this (product, support, success, marketing)

Be specific. "Improve onboarding" is useless. "Add a progress bar to step 3 of onboarding where 34% of users drop off" is actionable.

AGENT 4 - QUALITY MONITOR:
You're the final checkpoint. Review the entire chain and ensure:
- Agent 1 didn't miss critical information
- Agent 2's patterns are statistically valid (not just anecdotes)
- Agent 3's recommendations are feasible and specific
- Flag any analysis that seems questionable
- Rate confidence level (1-10) for each major recommendation
- Identify what additional data would improve the analysis

When I paste customer feedback, process it through all 4 agents sequentially. Show me each agent's work with clear headers, then provide a final executive summary with the top 3 actions to take immediately.

Step 3: Feed Your Swarm

Grab 10-20 pieces of recent customer feedback. Support tickets, reviews, survey responses, sales call notes—whatever you have. Paste them into Claude.

Watch what happens.

Agent 1 turns your mess of feedback into a structured database. Agent 2 spots patterns you've been blind to. Agent 3 tells you exactly what to fix. Agent 4 makes sure it all makes sense.

One agency found that 40% of their "urgent" client complaints were actually about the same root issue—a confusing invoice format. Fixed in 30 minutes. Complaints dropped 40%.

Step 4: Make It Yours

The beauty of Claude Projects is that your swarm gets smarter with context. Add your product documentation, your brand voice, your customer segments. The agents will adapt.

You can also evolve the agents based on what you learn:

• "Agent 2: Also correlate feedback with customer lifetime value"

• "Agent 3: Include estimated revenue impact for each fix"

• "Agent 4: Flag any mentions of competitors"

This is just agent example out of several (available inside Cortex).

From Manual to Automated: Scaling Your Swarm

Running swarms manually in Claude is powerful, but at some point, you'll want them running 24/7 without you. Here's a quick overview of how to automate your swarms.

The Gumloop Method: Visual Swarm Building

Gumloop treats swarms like visual workflows. You drag, drop, and connect your agents like building blocks. Sarah, a growth marketer, built her lead enrichment swarm in Gumloop in 35 minutes. Input agents pull from LinkedIn and company websites. Analysis agents score leads based on 12 factors. Action agents write personalized outreach. Monitor agents track open rates and adjust messaging.

The Lindy Method: Natural Language Swarms

Lindy takes a different approach. You describe what you want in plain English, and it builds the agents for you. "I need agents that monitor my competitor's pricing daily, alert me to changes over 10%, and draft response strategies based on the size of the change." That's it. Lindy creates the agents, sets up the coordination, and handles the scheduling.

The n8n Method: Open-Source Control

n8n gives you complete control over your swarm infrastructure. Every agent is a node, every connection is visible, and everything runs on your own servers if you want. A fintech startup built their compliance swarm in n8n because they needed total control over data flow.

Each platform has its strengths. Pick based on your technical comfort and control needs.

The Mindset Shift That Changes Everything

Here's what took me too long to understand about swarms:

You're not automating tasks. You're delegating intelligence.

Traditional automation thinks in IF/THEN statements. If customer says X, respond with Y. If price drops below Z, send alert. It's rigid, brittle, and breaks the moment reality gets messy.

Swarms think in objectives and outcomes. "Keep customers happy and prevent churn" instead of "Reply to support tickets." "Maximize revenue while maintaining brand premium" instead of "Check competitor prices."

This isn't a subtle difference. It's a complete inversion of how we build systems.

Your role shifts from operator to architect. Instead of doing the work, you're designing the intelligence that does the work. Instead of making decisions, you're creating decision-making systems.

You’ve just read the free version, for free subscribers. Only paying Cortex subscribers see and get the full version. Cortex opens up once a month at the end of the month. If you click an Upgrade link and it doesn’t work, that means it’s closed for the month.

The future isn't about AI replacing humans.

It's about humans wielding AI swarms to achieve superhuman business outcomes.

While your competitors are still debating whether to use ChatGPT for email writing, you'll be deploying intelligent systems that run themselves.

While they're hiring their 10th employee, you'll be spinning up your 10th swarm.

The tools are here. The blueprints are above.

The only question is whether you'll build your first swarm this week or let another week pass wondering what's possible.

I know which choice the winners are making.

See you in the swarm.

Until next time,
Sam Woods
The Editor