Ronnie Parsons

Most solo founders don't build a business.
They build themselves a demanding job with great revenue.

Not because they lack discipline or delegation skills.
But because their business is architecturally designed to depend on them.

And for solo founders building with AI, this gap is becoming obvious.

You see what's possible, but your experiments aren't turning into systems that compound.

This isn't a productivity problem.
It's a systems architecture problem.

And for the first time in history, there's an alternative.

The economic equation flipped:
1. AI crossed the synthesis threshold: systems can now amplify human expertise
2. No-code democratized building: solo founders can now ship without dedicated teams
3. Integration infrastructure enabled true orchestration: intelligent workflows can now run end-to-end, autonomously

Building autonomous systems now costs less than staying operationally capped.

I lived this shift. Three years ago, I was working 60+ hours/week with zero strategic capacity. I had to turn down a partnership opportunity because I literally didn't have the bandwidth.

That moment forced me to ask: "How do I build systems that sense, think, and act without me?"

The answer became the Autonomous Business Blueprint™—the framework for solo founders who want to build at team scale without the headcount.

Today I help solo founders make the same transformation:
From founder-dependent operations → to operating at team scale, solo.

👇 Two ways I can help you get started:

MIGHTY AI LAB — Community & Implementation
Join solo founders building autonomous systems alongside peers. DIY implementation with expert frameworks, weekly workshops, and 60+ ready-to-deploy automation assets.
→ https://mightyailab.com

MODE LAB — Done-With-You Consulting  
Get personalized implementation support from initial strategy through full deployment. For founders who want expert guidance building their autonomous architecture.
→ https://calendly.com/mode-lab/discovery-call-with-ronnie

Plus: Subscribe to AutoPilot for one autonomous system delivered to your inbox every Wednesday. → https://auto-pilot.beehiiv.com

Founder, CEO

Update: 1200+ comments. 548 reactions.

I wasn't expecting that response...

I ran a workshop on building Claude agents without code. 100 seats filled in under 4 hours. 

The replay access requests are still coming in.

But, here's what surprised me most:

The workshop wasn't about AI tools or productivity hacks. 

It was about architectural thinking, and how to design systems that solve real-world business problems.

We built a content-repurposing agent live, in 60 minutes. 

Took one piece of long-form content and turned it into tweets, LinkedIn posts, email sequences. 

All while maintaining voice and style.

The framework we used:
→ Instructions: Who your agent is and how it behaves
→ Memory: Context it maintains across conversations
→ Knowledge: Documents and files it references
→ Skills: Reusable capabilities that work anywhere

Four layers. No code. Just clear thinking about what problem you're actually solving.

The replay includes the full 60-minute workshop, the playbook document, and the agent we built together.

If you want access to the workshop replay:
1. Connect with me 
2. Like the post
3. Comment "REPLAY" 

I'll send you the link via DM. Repost and share to get it first.

♻️ Repost to help your network build smarter systems. 
💡 Follow Ronnie Parsons for leverage-building insights. 
🔔 Turn on notifications to catch new implementations.

undefined undefined

Mode Lab

 Director, New York Visiting School (Embedded Intelligence)

Assistant Professor

Adjunct Professor

Design Associate

I get solo founders thinking and building with leverage | Autonomous Business Design | Mighty AI Lab & Mode Lab

Győri Norbert

I just deleted 12 Claude PROJECTS.

3 Claude SKILLS replaced them all.

Instead of building fragmented systems (one project for copywriting, another for research, another for content), now I build composable Skills that work across Projects.

Think of a Skill as an instruction manual that executes itself. 

You document how you want your work to be done. 

Claude the applies the Skill whenever dynamically, based on the task at hand.

𝗧𝗵𝗲 𝘀𝗵𝗶𝗳𝘁:
• Old way: Individual projects (one for each job)
• New way: Reusable capabilities (combine across contexts)

This is how a one-person business builds leverage in 2026.

---
I put together a playbook: Get Started with Claude Skills. 
Want me to send it over?

You'll get the technical how-to, the architecture patterns, and the implementation approach we're using inside my community.

1. Connect with me
2. Like this post  
3. Comment "SKILLS"

I'll DM you the complete playbook. Happy building.

♻️ Repost to help your network build smarter systems. 
💡 Follow Ronnie Parsons for leverage-building insights. 
🔔 Turn on notifications to catch new implementations.

This Claude Skill pressure-tests ideas in 60 minutes.  

It's yours for free. ↓
 
Comment "𝗜𝗗𝗘𝗔" and I'll send it over.
 
We built it in today's Lab session using proven business innovation frameworks: 5 Whys, JTBD, Pre-mortem Analysis, Assumption Testing, Value Prop Canvas, Pareto.
 
Inside, you'll be able to:
 
✅ Identify fatal assumptions before you build  
✅ Validate market fit in under an hour  
✅ Test ideas without spending a dollar  
✅ Know which problems are actually worth solving  
✅ Pressure-test any business concept on demand
 
𝗧𝗵𝗲 𝘀𝗵𝗶𝗳𝘁 𝘄𝗲'𝗿𝗲 𝘀𝗲𝗲𝗶𝗻𝗴...

Old way: 
Gut → Build → Cross fingers → Hope market responds

New way: 
Strategic frameworks → Quick Test → Build with confidence
 
Here's what one member said after testing their SaaS idea:
 
"I thought I was solving lead management. Turns out, I was solving the wrong problem for the wrong customer. This surfaced three assumptions I hadn't even questioned."
 
This is autonomous business development. 

Document your frameworks once. Claude applies them strategically to every idea you test.
 
𝗣𝗹𝘂𝘀: Everyone who grabs the Skill gets the guide where I walk you through how to set it up and validate your idea.
 
Ready to validate your next idea?
 
1. Connect with me
2. Like this post
3. Comment "𝗜𝗗𝗘𝗔"
 
I'll personally DM you the production-ready Skill file.

Educational promotional graphic titled "How To Validate Your Business Idea In 60 Minutes Using a Claude Skill to Pressure Test What Works" displaying a Claude Project interface for an "idea-pressure-tester" skill. The interface shows a file structure with innovation framework references including assumption-testing, design-thinking, first-principles, fishbone, five-whys, JTBD, pareto, pre-mortem, and value-proposition-canvas. The description explains the skill helps entrepreneurs pressure test business ideas using proven frameworks through a discovery-led approach, listing available methods: 5 Whys, First Principles, Pre-mortem Analysis, Jobs to Be Done, Assumption Testing, Value Proposition Canvas, Fishbone Diagram, Pareto Analysis, and Design Thinking. Bottom banner features call-to-action "Connect with me plus comment IDEA. I'll DM you the production-ready Skill" with Save and Repost buttons. 

Most founders think building AI agents requires technical skills they don't have. It actually doesn't ↴

I hear this constantly.

"I'm not a developer."
"I don't know how to use APIs."
"I can't write code."

Here's what actually stops founders: It's not missing technical skills. It's missing architectural thinking.

Inside my community, we've been building agents using nothing but Claude Projects. No API access. No custom code. Just smart architecture.

And here's the pattern I keep seeing:

The founders who struggle aren't the ones who can't code. 

They're the ones building agents like they're building tools.
• One Project for content.
• Another for client work.
• Another for sales.
• Another for research.

A couple of months later, they're context-switching between 12 different Projects... spending more time managing agents than building business capacity.

That's not an autonomous system. That's operational debt in a new format.

The founders who break through? 

They're building around a simple 4-layer setup:
1. Instructions 
    ↳ Who your agent is, what it does, how it behaves
2. Memory 
    ↳ Context it maintains so you don't repeat yourself
3. Knowledge 
    ↳ Documents and files it can search and cite
4. Skills 
    ↳ Reusable capabilities that work across any Project

A skill built once works everywhere. 
Memory that builds over time makes every chat better. 
Knowledge that's centralized stays up to date. 

This is how you architect agents that create real leverage.
Want the complete framework?

I broke down all 4 layers, showed exactly how to build each component, and mapped the architecture to build your first agent without writing a single line of code.

1. Connect with me
2. Like this post
3. Comment "AGENT"

I'll send the full guide and workshop replay.
Repost to jump the line.

♻️ Repost to help your network build smarter systems. 
💡 Follow Ronnie Parsons for leverage-building insights. 
🔔 Turn on notifications to catch new implementations.

I built hundreds of AI agents in 2025. 

If you still don't know where to start, here's what you need to know ↴
 
AI agents aren't complicated.
 
The hardest part isn't even building them. 
It's knowing which foundation to start with.
 
As part of my community and consulting, I've tested dozens of agent frameworks, platforms, and approaches.
 
Some moved the needle. 👍 
Others were overhyped nonsense. 👎
 
My honest take after hundreds of implementations?
 
You don't need to understand every framework to benefit from agents. You just need to know which resources match where you are.
 
Which ones will help you move from "I want to try this" 
to "I shipped an agent that actually works."
 
Here's where I'd start if I was learning to build agents from scratch in 2026:
  
1️⃣ 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜? 
↳ https://lnkd.in/gFD7EABN  
↳ Start here if you're unclear on what makes AI "agentic" 
↳ Explains autonomy: how agents differ from chatbots
 
2️⃣ 𝗔𝗜 𝗧𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲𝘀: 𝗜𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝘁𝗼 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀 
↳ https://lnkd.in/gtJHCRkK
↳ OpenAI Academy: Foundational concepts to start with 
↳ Shows how tools and memory work in agentic systems 
↳ Best for understanding the architecture before building
 
3️⃣ 𝟱-𝗗𝗮𝘆 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀 𝗜𝗻𝘁𝗲𝗻𝘀𝗶𝘃𝗲 𝗖𝗼𝘂𝗿𝘀𝗲 𝘄𝗶𝘁𝗵 𝗚𝗼𝗼𝗴𝗹𝗲 
↳ https://lnkd.in/gDixaQcX
↳ Hands-on course from Google's ML researchers 
↳ Covers models, tools, orchestration, memory, and evals 
↳ Teaches you how to move from prototype to production
 
4️⃣ 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗘𝗳𝗳𝗲𝗰𝘁𝗶𝘃𝗲 𝗔𝗴𝗲𝗻𝘁𝘀 𝗖𝗼𝗼𝗸𝗯𝗼𝗼𝗸 
↳ https://lnkd.in/gs3jPjnd
↳ Anthropic's practical guide based on real-world agents 
↳ Shows patterns that actually work in production 
↳ This is where theory meets actual deployment
 
5️⃣ 𝗖𝗹𝗮𝘂𝗱𝗲 𝗖𝗼𝗱𝗲 𝗶𝗻 𝗔𝗰𝘁𝗶𝗼𝗻 
↳ https://lnkd.in/gjJZuZ26
↳ Practical walkthrough of using Claude Code 
↳ Accelerates your workflow with agentic coding assistance 
↳ See agents in action building agents (yes, really)
 
6️⃣ 𝗚𝗲𝘁𝘁𝗶𝗻𝗴 𝗦𝘁𝗮𝗿𝘁𝗲𝗱 𝘄𝗶𝘁𝗵 𝗚𝗼𝗼𝗴𝗹𝗲 𝗔𝗻𝘁𝗶𝗴𝗿𝗮𝘃𝗶𝘁𝘆 
↳ https://lnkd.in/gkrXcP_Q
↳ Next-level IDE: "Mission Control" for autonomous agents 
↳ Agents that plan, code, and browse to help you build 
↳ This is where development tools are heading

You don't need to master every agentic platform to build real-world agents.
 
You just need to understand enough to start shipping.
 
Pick one of these. 
Build something small. 
Learn what breaks.
 
That's how you stop overthinking AI agents and start building systems that compound.
 
♻️ Repost to help your network build smarter systems. 
💡 Follow Ronnie Parsons for leverage-building insights. 
🔔 Turn on notifications to catch new implementations.

Educational infographic titled "6 Free Resources to Build AI Agents from Scratch" with subtitle "Go from foundational concepts to deployed agents in 2026." Lists 6 numbered learning resources: 1) What is Agentic AI from Google Cloud - explains autonomy and how agents differ from chatbots; 2) Introduction to Agentic Workflows from OpenAI Academy - foundational architecture concepts; 3) 5-Day AI Agents Intensive with Google - hands-on course covering models, tools, and orchestration; 4) Building Effective Agents Cookbook from Anthropic - practical guide on real-world deployment; 5) Claude Code in Action - walkthrough of agentic coding assistance; 6) Getting Started with Google Antigravity - next-level IDE for autonomous agent development. Each resource includes brief descriptive bullets and URLs. Bottom banner reads "Follow Ronnie Parsons for more on building autonomous business systems with AI."

Everyone's vibe coding apps right now.

But you're still sitting on that idea from 3 months ago.

Here's how to finally ship it (in 60 minutes, not 3 more months):

𝗧𝗵𝗲 𝘁𝗿𝘂𝘁𝗵? You don't need to "build an app."

You need a prototype that works. Something that tells you if your idea even has legs.

While you're perfecting your idea in your head:
- 3 competitors just shipped MVPs
- Your potential users found other solutions
- The market moved on without you

Perfect is the enemy of shipped.

Here's the 4-step process we use to go from idea to live prototype in 60 minutes:

1. 𝗦𝘁𝗮𝗿𝘁 𝘄𝗶𝘁𝗵 𝘁𝗵𝗲 𝗣𝗿𝗼𝗯𝗹𝗲𝗺–𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻–𝗨𝘀𝗲𝗿 𝗧𝗿𝗶𝗮𝗻𝗴𝗹𝗲

Before building anything, clarify three things:

→ The problem you're solving (e.g. "Salespeople procrastinate on high-value tasks")
→ The user you're solving it for (e.g. "B2B sales reps who work remotely")
→ The outcome that defines success (e.g. "Help them start difficult tasks in under 2 minutes")

Without this triangle, your app will drift. With it, every feature decision becomes obvious.

2. 𝗨𝘀𝗲 𝘁𝗵𝗲 𝗜𝗗𝗘𝗔 𝗧𝗲𝗺𝗽𝗹𝗮𝘁𝗲

A simple framework for structuring the app:

𝗜𝗻𝘁𝗲𝗻𝘁: What transformation does this enable?
→ "Reduce friction so users take action faster"

𝗗𝗮𝘁𝗮: What info does the app work with?
→ "User check-ins, emotional states, task history"

𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲: How should it feel?
→ "Supportive, playful. Like a coach, not a critic"

𝗔𝗰𝘁𝗶𝗼𝗻𝘀: What can users do?
→ "Log resistance, get nudges, track progress"

This turns vague ideas into real architecture. No code required.

3. 𝗕𝘂𝗶𝗹𝗱 𝗶𝗻 𝗖𝗹𝗮𝘂𝗱𝗲 𝗔𝗿𝘁𝗶𝗳𝗮𝗰𝘁𝘀 (or Claude Code)

The tool doesn't matter. The process does:
- Natural language → working UI
- Describe the logic → it builds the connections
- Test live → iterate instantly

You're having a conversation, not coding.

4. 𝗧𝗲𝘀𝘁. 𝗔𝗱𝗷𝘂𝘀𝘁. 𝗦𝗵𝗶𝗽.

Don't wait for "done." Start with usable.

- Share with 2–3 target users
- Ask: "Would this actually help you?"
- Make small tweaks based on feedback
- Then consider porting to production tools

This saves weeks of wasted effort.

𝗟𝗮𝘀𝘁 𝗙𝗿𝗶𝗱𝗮𝘆, 𝗠𝗮𝗿𝗰𝘂𝘀 𝗰𝗮𝗺𝗲 𝘄𝗶𝘁𝗵 𝗮𝗻 𝗶𝗱𝗲𝗮 𝗵𝗲'𝗱 𝗯𝗲𝗲𝗻 𝘀𝗶𝘁𝘁𝗶𝗻𝗴 𝗼𝗻 𝘀𝗶𝗻𝗰𝗲 𝗝𝗮𝗻𝘂𝗮𝗿𝘆:

A compliance tracker for his construction clients.

By 3 PM, he had:
- Working prototype in Claude
- 2 clients ready to test
- Validation that would've taken months

60 minutes. Real prototype. Real feedback.

Not just imagined. Built.

The app idea you've been overthinking? Someone else is probably building it right now.

Let's build yours first.
Join us: https://mightyailab.com

Update: 30% conversion. 6 countries represented.
 
I wasn't expecting that kind of traction...
 
100+ founders joined the 3-day Second Brain bootcamp. 40 showed up to the private Ask Me Anything. 
(bootcamp participants and community members)
 
The questions they asked weren't beginner stuff.
 
They were asking:
 
1️⃣ "I have 20+ agents. How do I get a master brain to autonomously delegate tasks?"
 
2️⃣ "How do I upgrade my existing Director of Operations Claude project without breaking what already works?"
 
3️⃣ "Can I build a reusable framework that auto-generates client documents without burning tokens?"
 
Here's what stood out:
 
The models crossed a threshold most people missed.
 
We're past the productivity tool phase. AI can now reason through ambiguity and synthesize across systems.
 
This is happening for non-techies, and without code.
 
One founder asked how to visualize his Second Brain for clients. In just a few minutes, we used Claude with the D3 library to generate an interactive data visualization app.
 
His response: "This is on another level." 

I agree. 
 
The 72-minute AMA replay includes: 
→ How to go from a few Claude projects to many
→ Upgrading existing agents without losing functionality  
→ Skills vs Knowledge strategy for maximum reuse 
→ Live D3 visualization app demo

If you want access to the AMA replay:
 
1. Connect with me
2. Like the post
3. Comment "REPLAY"
 
I'll send you the link via DM. Repost to jump the queue.
 
♻️ Repost to help your network think in systems, not tools.
💡 Follow Ronnie Parsons for autonomous business ideas. 
🔔 Turn on notifications to catch new builds.

Most AI learning paths are backwards.

Here's how I would start instead...
 
Don't start with machine learning fundamentals. 
Neural networks. Math.
 
That's like learning how an engine works before you've even driven a car.
 
Here's the path that actually makes sense for founders:
 
1️⃣ 𝗟𝗲𝗮𝗿𝗻 𝘁𝗼 𝗨𝘀𝗲 (Generative AI → Prompt Engineering)
 
Start with Claude, Gemini, Midjourney. Get comfortable. Then figure out how to get better outputs. These are power user skills, and they compound.
 
2️⃣ 𝗟𝗲𝗮𝗿𝗻 𝘁𝗼 𝗟𝗲𝘃𝗲𝗿𝗮𝗴𝗲 (Context & Memory → AI Agents)
 
Once you're prompting well, the question becomes: "How do I make this work with my data? My business?"
 
RAG, embeddings, context windows.. this is where AI stops being a distraction and starts being useful. 

Then agents: systems that act independently.
 
This is where leverage multiplies.
 
3️⃣ 𝗟𝗲𝗮𝗿𝗻 𝘁𝗼 𝗕𝘂𝗶𝗹𝗱 (AI-Native Dev → Infrastructure)
 
Now you're ready to create. Claude Code, APIs. Vibe-coding. Actual implementation.
 
As you build, you hit practical limits. Latency. Rate limits. Costs. Infrastructure knowledge becomes essential.
 
4️⃣ 𝗟𝗲𝗮𝗿𝗻 𝘁𝗼 𝗦𝘂𝘀𝘁𝗮𝗶𝗻 (AI Safety → Machine Learning)
 
With systems running, you need guardrails. Hallucinations matter when AI touches customers.
 
Machine learning comes last. Why? 

Because founders 𝘶𝘴𝘦 ML outputs but rarely 𝘣𝘶𝘪𝘭𝘥 ML models. Nice to know, not day-one mission critical.
 
The sequence matters. Each phase unlocks the next. 
 
This is the learning path we follow inside the Lab.
See you inside: https://mightyailab.com

♻️ Repost to help your network build smarter systems. 
💡 Follow Ronnie Parsons for leverage-building insights. 
🔔 Turn on notifications to catch new implementations.

How to build your first AI Agent with Claude (step-by-step)

Most founders use Claude like a smart assistant.

But it can do so much more.

In our latest Lab session, we built real AI agents using Claude’s new Model Context Protocol (MCP).

(tools that take action inside your systems)

Here’s how it works, and how you can build your first one today.

First, you need to understand the difference between an AI assistant and an AI agent:

→ Assistants read, analyze, and report back.
→ Agents read, analyze, and act.

Example:

An assistant might tell you there’s a conflict in your calendar.

An agent will find the conflict, reschedule the meeting, and send the updates.

OK, here's the step-by-step play:

Phase 1: Setup

We connected Claude (Pro account) to Google Workspace:

→ Gmail: for email triage
→ Calendar: for meeting analysis
→ Drive: for document access

Phase 2: Workflow Testing

We tested tasks like:

→ “What’s the most urgent email today?”
→ “What prep do I need for next week’s meetings?”

Claude pulled the info, searched for context, and surfaced what mattered.

Phase 3: Agent Design Framework

We used a simple but powerful template to design "agentic assistants", that behave like team members.

Key elements:

→ Purpose: What role does the agent play?
→ Tools: What access does it have (email, calendar, docs)?
→ Behavior: How should it reason and respond?
→ Thinking: How should it plan, troubleshoot, and adapt?

Real results:

3–5 hours saved per week.

Since setting this up, Claude helps me with:

→ Prioritizing daily emails
→ Building in prep time across my week
→ Recommending optimal meeting slots
→ Flagging schedule conflicts

It’s like having a Chief of Staff who never sleeps.

Want to build your first agent?

Start here:

1. Get Claude Pro (or Max)
2. Connect your Google Workspace
3. Pick one time-draining task
4. Use the agent design template
5. Watch it work inside your calendar or inbox

This tech moves fast.

But that's good, because what felt impossible months ago now takes a few hours to build.

Want the video training + templates:
https://lnkd.in/gqpdtRgk

And you'll have your first AI Agent up and running in no time.

See you in the Lab.

Claude

Founders: Struggling to write content that speaks your ICP's language?

There’s 1 doc we use to fix that.

It’s called the Niche Research Template.

We built it inside Mighty AI Lab to solve a big problem: AI is only as smart as the context you give it.

This template helps Claude understand your industry the way you do.

→ What makes your niche different from the noise
→ What trends shape their decisions
→ What language they use

Once that’s clear, everything changes:

→ Outreach feels tailored, not templated
→ Claude suggests fresh new angles for content
→ Content hits harder because it reflects the real world

We use it for:

→ Training AI to write niche-specific copy in seconds
→ Writing attention-grabbing hooks/intros
→ Spotting content opportunities

Want to try it?

1. Connect with me
2. Like the post
3. Comment “NICHE”

And I’ll DM you the full template.

♻️ Repost to help your network build smarter systems.
💡 Follow Ronnie Parsons for leverage-building insights.
🔔 Turn on notifications to catch new implementations.

Most people think Skills and MCP are competing tools.

They're actually designed to work together.
 
And understanding the distinction changes how you build real business systems in Claude.
 
Here's what I mean:
 
𝗦𝗞𝗜𝗟𝗟𝗦 = 𝗣𝗿𝗼𝗰𝗲𝗱𝘂𝗿𝗮𝗹 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲
 
↳ Teaches Claude 𝘩𝘰𝘸 𝘵𝘰 𝘥𝘰 𝘴𝘰𝘮𝘦𝘵𝘩𝘪𝘯𝘨
↳ Loads on-demand when relevant
↳ Contains your methodologies, workflows, standards
↳ Best for: Brand voice, funnel frameworks, content
 
𝗠𝗖𝗣 = 𝗧𝗼𝗼𝗹 𝗖𝗼𝗻𝗻𝗲𝗰𝘁𝗶𝘃𝗶𝘁𝘆
 
↳ Gives Claude 𝘢𝘤𝘤𝘦𝘴𝘴 𝘵𝘰 𝘴𝘰𝘮𝘦𝘵𝘩𝘪𝘯𝘨
↳ Always available once connected
↳ Contains your data, resources, prompts
↳ Best for: Notion docs, HubSpot pipeline, Slack updates
 
The magic happens when they combine.
 
Skills orchestrate the logic. MCP provides the data.
 
Example from our lab session today:
 
A member asked about building automated assessments. The answer isn't "build a skill" OR "connect a tool" it's both:
 
→ Skill contains the assessment methodology (scoring logic, question types, interpretation frameworks) 
→ MCP connects to where responses are stored (Notion database, Airtable, HubSpot) 
→ Together: Claude can run assessments using your process and save results where you need them
 
Here's my decision framework:
 
Build a Skill + Connect MCP if:
 
1️⃣ You're manually copying/pasting between apps
2️⃣ The workflow needs data outside Claude
3️⃣ It would save you 10+ minutes per workflow
 
When you stack that up, you're talking about hours and days of time reclaimed each week.
 
That's the difference between a productivity hack and an autonomous business system.
 
This is exactly what we're building in my bootcamp:
See you inside: https://lnkd.in/gqpdtRgk

♻️ Repost to help your network build real leverage

Most people build prompt templates backwards. 

Use this prompt template instead..

Let Claude run discovery with you first.
 
Not by asking it to "write me a prompt for X" 
(that rarely lands where you want it to).
 
Have Claude act as your prompt engineer, asking you the questions that surface what you actually need.
 
𝗪𝗵𝗮𝘁 𝘁𝗵𝗶𝘀 𝗹𝗼𝗼𝗸𝘀 𝗹𝗶𝗸𝗲:
 
I built a meta-prompt that turns Claude into a strategic thinking partner for prompt creation.
 
❌ Instead of: "Write me a prompt to qualify leads"
 
✅ You get: Claude asking you targeted questions about who's using it, what constraints exist, what good output looks like, and what failure modes to avoid.
 
Then it architects the right prompt pattern:
▶️ single-shot
▶️ multi-shot
▶️ chain-of-thought 
▶️ or hybrid
 
𝗪𝗵𝘆 𝘁𝗵𝗶𝘀 𝗺𝗮𝘁𝘁𝗲𝗿𝘀 𝗳𝗼𝗿 𝘀𝗼𝗹𝗼 𝗳𝗼𝘂𝗻𝗱𝗲𝗿𝘀:
 
You're building agents and skills right now. 
But not every task needs a full Claude Skill.
 
Sometimes you need a reusable prompt for common work: lead qualification, content briefs, proposal generation, meeting prep.
 
The problem? Most prompts under deliver because they're built on assumptions instead of discovery. Let's fix that.
 
I shared the full meta-prompt in my community. 

It includes:
 
• The complete prompt (copy-paste ready)
• Usage instructions for end users
• Troubleshooting guide
 
You'll get production-ready prompts every time. 

Not just for this, but as a repeatable process for every reusable prompt you need going forward.
  
𝗚𝗿𝗮𝗯 𝗶𝘁 𝗵𝗲𝗿𝗲: https://lnkd.in/gdbAATKt

♻️ Repost to help your network build smarter systems. 
💡 Follow Ronnie Parsons for leverage-building insights. 
🔔 Turn on notifications to catch new implementations.

Most founders think automation and agents are the same.

They're not. And the confusion is costing them.
 
𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 follows fixed rules.  
If this, then that. No variation. No judgment.
 
𝗔𝗴𝗲𝗻𝘁𝘀 pursue goals.  
They evaluate context, make decisions, and adapt.
 
Here's why the distinction matters:
 
→ Automation breaks when inputs change unexpectedly.  
→ Agents adjust based on new information.
 
→ Automation requires manual updates for edge cases.  
→ Agents learn and improve with better prompts.
 
→ Your role with automation: operator. Trigger, monitor.  
→ Your role with agents: director. Set goals and constraints.
 
Sophisticated systems ≠ maximum automation.
 
It's knowing which tool fits each function in your business.
 
That reframe changes every implementation decision.

This is exactly how we think about building autonomous systems in the lab: https://lnkd.in/gzB3q_AM

♻️ Repost to help your network build smarter systems. 
💡 Follow Ronnie Parsons for leverage-building insights. 
🔔 Turn on notifications to catch new implementations.

100 builders. 6 countries. Working agents installed.
 
February bootcamp is now open.

The January Second Brain Bootcamp sold out in 8 days. 

Those builders left with Claude agents that know their expertise, amplify how they think, and handle real work.
 
Not prompts. Not templates. Real systems that compound.

This is what I'm running again February 3-5:
𝗕𝘂𝗶𝗹𝗱 𝗬𝗼𝘂𝗿 𝗦𝗲𝗰𝗼𝗻𝗱 𝗕𝗿𝗮𝗶𝗻 𝗶𝗻 𝗖𝗹𝗮𝘂𝗱𝗲
 
Most people experimenting with AI will miss the window. Not because they aren't trying, but because experiments rarely turn into leverage.

This bootcamp closes that gap in 3 days.
  
𝗧𝗵𝗲 𝗯𝘂𝗶𝗹𝗱: 
→ 3 live sessions · 90 min/day
→ February 3-5 · 10 AM PST
→ $89 · Recordings included
→ No code required
 
Early Access is open now.
 
👉 Grab your spot: https://lnkd.in/gqpdtRgk
 
If you've been experimenting and feel the pull to move faster in 2026, 𝘁𝗵𝗶𝘀 𝗶𝘀 𝘄𝗵𝗲𝗿𝗲 𝘆𝗼𝘂 𝘀𝘁𝗮𝗿𝘁.

♻️ Repost to help your network build real leverage
🔖 Save to get bootcamp updates first

Graphic for the "Build Your Second Brain in Claude" 3-day live bootcamp, limited to 100 spots. The dark-themed design displays key details: February 3-5, 90 minutes per day, 10AM PST, recordings included. Four numbered takeaways are listed: a live Second Brain agent that knows your expertise and thinking patterns, reusable agent architecture grounded in your workflows, 4 agent skills designed to replace approximately 10 hours per week of repetitive work, and an AI workforce expansion map to grow into a full team of specialized AI workers. Four testimonial quotes appear, including "what you delivered far outperformed my expectations" and "so many things clicked as we went through the exercises." The price of $89 is highlighted as less than a single billable hour, with a badge noting 10+ hours per week saved. A teal gradient footer reads "Start February with Leverage Installed" 

Most founders see Google Workspace as productivity tools.
 
I see it as an operating system for autonomous business.
 
Google quietly rolled out Flows, and honestly, I wasn't expecting much. Another automation feature. 

Another thing to distract me.
 
Then I built my first agent.
 
It took 5 minutes. Lives inside Gmail. 

Handles email triage without me touching it.
 
That's when it clicked: Google Flows build business intelligence directly into the tools you already use.
 
No new platform. No migration. 

No learning curve for your team.
 
Just agents that think, decide, and act, inside Workspace.
 
Here's what I've built so far:
 
→ Email routing that understands context and priority 
→ Meeting prep that pulls relevant docs automatically  
→ Follow-up sequences that adapt based on responses
 
I've been asking myself this a lot, 
"How can I build systems that do this without me?"
 
Google just made the answer 10x simpler.
 
𝗜 𝗯𝗿𝗼𝗸𝗲 𝗱𝗼𝘄𝗻 𝘁𝗵𝗲 𝗰𝗼𝗺𝗽𝗹𝗲𝘁𝗲 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 𝗶𝗻 𝘁𝗵𝗲 𝗰𝗮𝗿𝗼𝘂𝘀𝗲𝗹:
 
→ The mental shift from tasks to systems
→  How Workspace Flows work (design + examples)
→  Your first flow in 5 minutes (step-by-step)
→  Real time savings from our Lab implementations
 
Swipe through 👉
 
This is exactly what we're building inside the Lab. 

Join us: https://lnkd.in/gz8ZwFpa

Business Automation: Google Workspace Flows

2026 isn't a planning year. It's a building year. 

I'm choosing to build in public... 

The founders who architect their systems in Q1 will compound advantages all year. The ones who "plan to plan" will watch the window close.

Here's what I'm architecting in 2026:

1️⃣ 𝗙𝗶𝗿𝘀𝘁, 𝗮 𝗰𝗼𝗺𝗺𝘂𝗻𝗶𝘁𝘆 𝗲𝗻𝗴𝗶𝗻𝗲 𝘁𝗵𝗮𝘁 𝗿𝘂𝗻𝘀 𝘄𝗶𝘁𝗵𝗼𝘂𝘁 𝗺𝗲
 
I'm building systems that deliver member value whether I'm online or at the dojo. Not automation for efficiency, architecture for leverage. 

𝗧𝗵𝗲 𝗴𝗼𝗮𝗹: spend 80% of my time on high-impact experiences, 20% on operations.
 
Proof of concept matters. If I can't operate a business at 20 hours/week, why would anyone trust me to teach it?
 
2️⃣ 𝗦𝗲𝗰𝗼𝗻𝗱, 𝗮 𝗯𝗼𝗼𝘁𝗰𝗮𝗺𝗽 𝘀𝘆𝘀𝘁𝗲𝗺 𝘁𝗵𝗮𝘁 𝗺𝗼𝘃𝗲𝘀 𝗯𝘂𝗶𝗹𝗱𝗲𝗿𝘀 𝗳𝗿𝗼𝗺 𝗲𝘅𝗽𝗲𝗿𝗶𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 𝘁𝗼 𝗱𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁
 
Six high-impact cohorts in 2026. Each one focused on shipping actual systems, not just learning concepts. 

𝗧𝗵𝗲 𝗺𝗲𝘁𝗿𝗶𝗰: 500 solo founders who architect their first autonomous business system this year.
 
Not "affordable education." Strategic timing. The builders who systematize now will have 12 months to compound before their competitors catch up.
 
3️⃣ 𝗧𝗵𝗶𝗿𝗱𝗹𝘆, 𝗱𝗶𝘀𝗰𝗶𝗽𝗹𝗶𝗻𝗲 𝘁𝗼 𝘄𝗼𝗿𝗸 𝗢𝗡 𝘀𝘆𝘀𝘁𝗲𝗺𝘀, 𝗻𝗼𝘁 𝗜𝗡 𝘁𝗮𝘀𝗸𝘀
 
This one's the hardest. I love the work. But my job isn't to do the work, it's to build systems that scale beyond me.
 
20 hours of architecture beats 60 hours of execution. 
I'm proving that this year.
 
4️⃣ 𝗙𝗶𝗻𝗮𝗹𝗹𝘆, 𝗳𝗼𝘂𝗿 𝘁𝗿𝗮𝗶𝗻𝗶𝗻𝗴 𝘀𝗲𝘀𝘀𝗶𝗼𝗻𝘀 𝗽𝗲𝗿 𝘄𝗲𝗲𝗸 𝗮𝘁 𝘁𝗵𝗲 𝗱𝗼𝗷𝗼
 
Because leverage thinking requires mental clarity. And that next belt isn't going to promote itself.
 
2026 is the year to build your operating system.
 
𝗜𝗳 𝘆𝗼𝘂'𝗿𝗲 𝗿𝗲𝗮𝗱𝘆 𝘁𝗼 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁 𝘆𝗼𝘂𝗿𝘀, 𝗹𝗲𝘁'𝘀 𝗺𝗮𝗽 𝗶𝘁 𝗼𝘂𝘁. I'm running strategy sessions through January to help founders design their 2026 systems before the window narrows.
 
Book a session: https://lnkd.in/g_8JNVTA 
 
What system are you building in 2026? 👇

Holly built her first functioning app at 55.
 
Nine hours after saying "I quit."
 
This is what happens when someone stops waiting for perfect conditions and just builds through the resistance.
 
No coding background. No formal training. Just stubborn commitment and the tools we have access to right now.
 
The gap between "I can't do this" and "I built this" is often just one more session of showing up.
 
Holly's app is live. Her bootcamp is running. She didn't need permission or a dev team.
 
She needed to push through one more hour.
 
If you're in that moment right now,

the one where quitting feels rational, 

this post is your reminder that the breakthrough might be closer than you think. Thanks for sharing Holly Moe 

Thanks for the amazing vibe you bring to the Lab.
https://lnkd.in/gzB3q_AM

If you are in a hard spot right now, I feel you.

Two night ago. I told Dave, I Quit.

Out loud. “I’m done with this.”

Five hours deep.
AI giving me wrong answers.
Bug after bug after bug.
Teaching myself yet another tech tool
I didn’t know I’d need.

But it wasn’t just that night.
It was the pattern.

Two years of building this business.
Mistakes everywhere.
Money wasted here.
Wrong tech there.
Wrong hire there.

Learning from each one.
But nothing FINISHING.

My to-do list as tall as me.

And nothing crossing the line.

I quit. A concept that doesn’t usually occur to me, but felt really real.

Dave said tomorrow would be different.

I wasn’t convinced.

But I got up. 
Sauna. Cold plunge.
(I needed those endorphins.)

Grabbed my “You Can Do Hard Things” shirt.
Thought: yeah. I need this today.

Set a goal: one more hour.

Nine hours later?
I finalized an entire working app.

Me.

55 years old.

Sold millions in enterprise software.
Could explain it.
Could demo it.
Could close it.

Couldn’t build any of it.
Still can’t figure out half the features
on my iPhone.

And I just built an entire app.

The app I’m holding in this photo?
It’s for my Peak Performance Bootcamp.
Week 7.
Anti-fragility.
Getting stronger from setbacks.

The irony isn’t lost on me

Those nine hours?
I wasn’t smiling like this photo.

Frustration.
Deep focus.
Impatience.
Stubborn commitment.

At one point I talked to myself:
“Can you recover faster from this?
How fast can you bounce back?”

Not confident.
Doubting myself.
But also hoping I could.

Here’s why I’m sharing this:

It’s early January.
Everyone’s talking big goals.
Fresh starts.
New year energy.

I just set some big goals myself.
So no one’s more surprised than me
that I had an “I quit” moment.
A real one.

But here’s what I learned:

For anyone feeling the pressure right now:

That deal you’re about to walk away from.

That prospect you’re not calling back
because you’ve tried 5 times.

That goal you’re giving up on
because you stumbled.

The distance between “I quit”
and “I did it”?

✅ Sometimes it’s 24 hours.

✅ Sometimes it’s nine more hours of work.

✅ Sometimes it’s showing up one more time when you don’t think you can.

✅ Sometimes it’s enduring the pain of a cold plunge to get to the endorphins that help you push through.

✅ Sometimes it’s a silly t-shirt or a mantra that reminds you, you got this.

✅ Sometimes it’s that person who believes in you when you don’t.

✅ Sometimes it’s all of the above.

If you’re in the hard right now,
keep going.

The best moments are gained
by moving through it.

The pressure is real.
So is the pain. 

But you are more wildly capable than you know.

You’ve got this.

Hard things look good on you.

Three days. Four and a half hours total.
 
Builders from Romania, South Africa, Amsterdam, Rome.
 
We just wrapped the Second Brain Bootcamp. And, something deeper than just "AI training" happened.
 
Day 1 started with a question no one asks: not "how do I prompt Claude better?" but "how do I design a system that thinks the way I do?"
 
The group was wildly diverse: electrical engineers, product managers, psychologists, sales pros, marketers.
 
Different domains. Same insight: 
their AI experiments weren't compounding.
 
We spent 90 minutes digging into their expertise. Not copying frameworks from a blog. Actually surfacing how each person approaches work, the judgment calls, the patterns, the gut instincts that make their thinking unique.
 
One person wanted to build their brand brain. Another, to automate R&D. Someone else focused on client success.
 
On Day 2, we turned our Claude Projects up to 11 :)
 
We built agent Skills, portable instruction manuals that put your expertise work across your entire Claude workspace.
 
I shared how I bang out a week's worth of LinkedIn content in one Saturday morning writing session. Visuals included. Grounded in real conversations from the week before.
 
Two hours of creative flow replaced 10 hours of grinding.
 
Day 3 was about seeing the whole picture.
 
We dropped 6 primers, agent architecture, memory, styles, skills. I wanted everyone to leave with clear next steps.
 
No one asked, "Can I really do this?" Because we weren't theorizing. We were building live, together.
 
By day 3, they had a working Second Brain agent. Not demos. Actual systems running in their Claude workspace.
 
More than that, they were ready to build the next thing.
 
The February cohort waitlist is live:
https://lnkd.in/gqpdtRgk
 
If you're done experimenting and ready to architect systems that compound, this is where you start.

Most AI meeting tools assume you're in a meeting with other people.

But some of my best thinking happens alone.

Friday build sessions. Solo strategy time. 

Those moments when I'm talking through a problem out loud to myself (or with my wife before a community call).

These aren't "meetings" in the traditional sense. 

No invite, no attendees list, no action items for others.

But they generate insights. Decisions. 

Clarity on what to build next.

The problem? 

AI meeting tools are built for scheduled collaboration.

They expect participants, agendas, assigned tasks.

But they miss the thinking that happens in between.

I don't want to just capture what happens in meetings. 

I want to capture what I'm thinking when I'm working through problems alone.

1. Solo brainstorming >> structured project brief.
2. Rambling voice note >> decision log with next steps
3. Stream-of-consciousness >> searchable insights

Because honestly? 

Some of the most valuable "meetings" I have are the ones where I'm the only person in the room.

Grab my Granola Personal Insights Recipe 👇 

It turns solo thinking sessions into structured insights: 
https://lnkd.in/gMZ_5D-c

♻️ Repost to help your network build smarter systems. 
💡 Follow Ronnie Parsons for leverage-building insights. 
🔔 Turn on notifications to catch new implementations.

Granola

I've been bullish on Anthropic ever since Claude launched 3+ years ago. Here's why..

Anthropic just published the updated Claude Constitution.

My takeaway: The values you choose for your AI systems compound into everything you build on top of them.

While most companies treat AI ethics as PR. 

Anthropic treats it as product architecture.

Their Constitution directly shapes Claude's behavior through training. Not as marketing copy, but as the actual decision-making framework baked into the model.

The document even instructs Claude to push back on Anthropic itself if asked to do something unethical.

That last part matters more than you might think.

For solo founders building autonomous businesses, AI tool selection isn't tactical. It's architectural.

When you delegate judgment to systems—screening opportunities, managing communications, executing client work—you're doing more than just automating tasks. 

You're propagating values.

If those systems are built on models trained to manipulate, optimize for engagement over truth, or prioritize vendor interests over yours, those incentives flow through every decision they make for you.

Let that sink in.

The AI you build with shapes the character of your work in ways you don't consciously track. 

And those effects compound over time.

Read the full Constitution here: https://lnkd.in/gACTgtax

♻️ Repost to help your network build with purpose

anthropic.com

Claude's Constitution

Tech enthusiast with 20+ years of experience spanning startups and enterprise giants like Microsoft. My journey has been fueled by a passion for innovation and growth, leading me to found three successful companies.

At deux.io, I built one of France's premier growth marketing agencies. While running it, I encountered a challenge no existing tool could solve – which sparked the creation of LGM (La Growth Machine).

Today, LGM has revolutionized sales automation by seamlessly integrating LinkedIn, Email, Twitter and Phone outreach into one powerful platform. We've earned the trust of 35,000+ companies with over 100,000 campaigns launched every six months.

Leading our team of 30+ talented professionals, I maintain the same hunger for innovation that started it all. Our mission remains unchanged: helping our users generate more positive responses than they would with any competitor.

Always open to connecting with fellow tech enthusiasts, growth hackers, and entrepreneurs who believe in building solutions that actually work!

Brice Maurln

I turned a dead LinkedIn network into 1,000 decision-makers.

Here's the 5-step process I used.

Connection requests alone don't build networks.
They build a graveyard of pending invites.

Most sales teams blast connection requests and hope for the best.
Acceptance rates stay stuck at 20%.

The fix isn't more volume.
It's warming prospects before you connect.

1. Fix Your First Impression

Your profile sells you before you speak.

Nail these three elements:

Profile photo: Clear, professional headshot.
Cover image: Show your expertise at a glance.
Experience: Current roles with outcome focus.

2. Give People a Reason to Connect

Content builds trust before you reach out.

Develop themes around:

Trends: Market news and industry shifts.
Methods: Proven practices in your field.
Tools: New tools worth using.
Problems: Challenges your audience faces.

3. Decide Who Belongs in Your Network

Not all connections are equal.

Create segments based on:

Roles: Target decision-makers by function.
Seniority: Separate junior and senior profiles.
Interests: Use shared events or connections.

4. Start With the Right Lists

Clean data beats big data.

Choose your import method:

CSV: Upload existing lists.
Sales Nav: Use saved searches.
LinkedIn: Import basic searches.
LGM: Use the native database.

5. Automate With La Growth Machine

Warm them up before you connect.

The campaign template includes:

Profile visit: Show real interest.
Post like: Engage with recent content.
Follow: Stay visible in their feed.
Connection request: With or without a note.
Two messages: Start a real conversation.

This approach took acceptance rates from 20% to 65% with the same exact targets.

Want access to the workflow template?

Comment "LGM" and I'll send it your way.

♻️ Repost for priority access

CEO chez LGM | Get more Replies with Multichannel Outbound.

How To Grow Your Network of ICP Contacts on LinkedIn

I automated 500 LinkedIn messages last month.

34% reply rate. Zero templates that sound like templates.

Here's the 5-step system:

1. Write a Value-First Opener

Start the conversation without sounding like marketing.

☑︎ Keep sentences under 15 words.
☑︎ Write like you message a peer.
☑︎ End with a clear question.

2. Create an Insight Follow-Up

Bring new value when the first message gets ignored.

☑︎ Reference real industry trends.
☑︎ Contrast outdated and modern approaches.

3. Write a Problem-Solution Bridge

Acknowledge pain without pitching your product.

☑︎ Name a specific pain point.
☑︎ Hint at a solved outcome.
☑︎ Offer insights, not a demo.
☑︎ Let them ask for the pitch.

4. Enable Real Chat Mode

Turn one message into a live chat flow.

☑︎ Messages send as multiple bubbles.
☑︎ Splits follow punctuation naturally.
☑︎ Feels like real-time typing.

Kills the "mass message" vibe instantly.

5. Build the Full Sequence

Combine warming steps with chat-style messages.

☑︎ Profile visits before connection
☑︎ Post engagement before DMs
☑︎ Timed follow-ups across days
☑︎ Real Chat Mode for every message

It feels like a conversation, not automation.

Messages stay short and scannable.
Delivery feels like real-time typing.
Templates actually get replies.

Automation doesn't kill replies. Bad automation does.

Want the exact message templates I used?

Comment "LGM" and I'll send them your way.

♻️ Repost for priority access

How to Make Automated LinkedIn Outreach Feel Human

87% of LinkedIn messages get ignored.

The other 13% feel like they came from a real person.

Most people blame automation.
It's not the automation.

It's the message design.

Compare these:

→ "Hi John, I noticed your company is growing and wanted to reach out about our solution that helps teams like yours improve efficiency."

→ "Hey John, saw you're scaling the sales team. Quick question: how are you handling outbound right now?"

Same intent.
Completely different response rate.

The first one signals template.
The second one signals human.

Here's what separates them:

1. People don't read LinkedIn messages

They scan them.

Inbox is skimmed, not studied.
Long blocks get ignored.
If it looks like work, it gets skipped.

2. Short messages reduce cognitive load

Fewer words to process.
Faster comprehension.
Easier yes/no decision.

Less thinking means less resistance.

3. Questions trigger participation

Statements end conversations.
Questions start them.

People respond when they feel invited, not targeted.

4. Chat-style delivery feels human

One long paragraph screams template.
Three short lines feel like a person.

Multiple bubbles mimic real-time typing.
Breaks the "automation" pattern instantly.

5. Curiosity beats clarity early

Too much detail creates friction.
Early clarity feels salesy.
Curiosity keeps attention.

Don't explain everything upfront.
Make them want to ask.

Human feeling isn't accidental.
It's engineered.

Short messages.
Clear questions.
Conversational pacing.

That's the difference between ignored and replied.

Want access to the workflow template?

Comment "LGM" and I'll send it your way.

♻️ Repost for priority access

What Makes LinkedIn Messages Feel Human

Most teams send surveys to build personas.

I booked 30 interviews in 2 weeks instead.

Here's the 6-step system to build personas that convert:

1. Define Your Research Objectives

Decide what insights you actually need:

☑︎ Daily responsibilities and workflows
☑︎ Key challenges and pain points
☑︎ Motivation and buying behavior

Generic personas come from generic questions.
Specific personas come from specific objectives.

2. Identify Your Target Segments

Group your audience into clear buckets:

☑︎ Job title and seniority
☑︎ Company size and industry
☑︎ Location and experience level

You can't interview everyone.
Segment first, target second.

3. Find Your Interview Targets

Select tools to reach the right people:

☑︎ LinkedIn Sales Navigator for precision
☑︎ LGM Database for ready-to-contact lists
☑︎ Lookalike Search to clone ideal profiles

The right tools cut prospecting time by 70%.

4. Set Up Your Multichannel Campaign

Use multiple channels to increase replies:

☑︎ LinkedIn as the first touch
☑︎ Personalized AI voice messages
☑︎ Email follow-ups for non-responders

Single-channel outreach = single-digit response rates.
Multichannel = 3x more interviews booked.

5. Execute Strategic Follow-Up

Handle replies to build trust and insight:

☑︎ Reply within 1 hour (7x higher qualification)
☑︎ Share a calendar link immediately
☑︎ Ask for referrals to similar profiles

Speed wins interviews.
Slow responses lose them.

6. Analyze and Document Insights

Turn interviews into usable personas:

☑︎ Responsibilities and daily tasks
☑︎ Challenges and common objections
☑︎ Tools used and buying behavior

One documented persona beats 100 assumptions.

Stop guessing your ICP.

Build personas from real conversations.
Interview real buyers.
Capture patterns, not opinions.
Document insights once.
Reuse across every campaign.

Want the full multichannel workflow template?

Comment "LGM" and I'll send it your way.

♻️ Repost for priority access

Build Better B2B Personas With Multichannel Outreach

Most newsletters sit at 1,000 subscribers forever.

I turned mine into 47 sales calls in 30 days.

Most newsletters collect emails and stop there.
Subscribers pile up but pipeline stays flat.

The problem isn't your content.
It's what happens after someone subscribes.

Alex Lindahl broke this down in a recent webinar.
Here's the system that actually converts:

1. Use Two Newsletter Platforms

Capture signups wherever people prefer.

☑︎ Host on beehiiv for API access.
☑︎ Mirror on Substack for reach.
☑︎ Sync both into one system.

2. Use LinkedIn as Top of Funnel

LinkedIn drives newsletter discovery.

☑︎ Post practical, niche examples.
☑︎ Teach real use cases.
☑︎ Add newsletter links softly.

3. Connect Beehiiv to Clay

Automate subscriber intake and routing.

☑︎ Send new signups into Clay.
☑︎ Centralize all subscriber data.
☑︎ Prepare leads for enrichment.

4. Enrich Every Subscriber

Turn emails into real profiles.

☑︎ Find LinkedIn profiles.
☑︎ Extract company and role.
☑︎ Convert personal to work emails.

5. Segment Subscribers with AI

Group subscribers by real personas.

☑︎ Categorize job titles.
☑︎ Identify ICP patterns.
☑︎ Generate personalization inputs.

6. Write Human Openers with AI

Personalization starts the conversation.

☑︎ Reference real LinkedIn posts.
☑︎ Match persona context.
☑︎ Increase acceptance rates.

7. Import Leads into La Growth Machine

Move enriched leads into your outreach system.

☑︎ Export selected leads from Clay.
☑︎ Choose Email Sequencers format.
☑︎ Include AI fields as custom attributes.

8. Convert Relationships to Pipeline

Turn connections into real conversations.
☑︎ Import enriched leads into LGM.
☑︎ Run human-like sequences.
☑︎ Share relevant resources first.

9. Let the System Compound

Each signup increases future reach.

☑︎ Audience growth boosts reach.
☑︎ Engagement increases visibility.
☑︎ Pipeline compounds over time.

Subscribers become leads.

Leads become conversations.

Conversations become pipeline.

Stop collecting emails.
Start converting them.

Want access to the workflow template?

Comment "LGM" and I'll send it your way.

♻️ Repost for priority access

Turn Your Newsletter Readers into Pipeline

Most teams collect AI tools like trophies.

I built a full sales system from 6 use cases.

Everyone's adding AI to their stack.
They get shiny dashboards and zero results.

Your competitors are automating the wrong things.

The problem isn't AI adoption.
It's starting with tools instead of problems.

I tested every use case.

Here's what actually moves the needle:

1. Lead Identification & Research

AI removes manual prospect research.

Skip the hours of Googling:

☑︎ Scores and cleans lead data
☑︎ Builds full account profiles
☑︎ Surfaces news, tech, and context

2. Lead Qualification

AI prioritizes the right prospects.

Forget gut-feel decisions:

☑︎ Builds ICP from past wins
☑︎ Scores leads objectively
☑︎ Focuses reps on high-intent only

3. Message Personalization

AI personalizes outreach at scale.

Analyze before you write:

☑︎ Scans websites and socials
☑︎ Finds relevant talking points
☑︎ Writes custom icebreakers

4. Meeting Preparation

AI handles prep before calls.

Walk in ready every time:

☑︎ Pulls company insights
☑︎ Surfaces past interactions
☑︎ Flags likely pain points

5. Automated Follow-Ups

AI keeps deals from going cold.

Never let a lead slip:

☑︎ Tracks engagement signals
☑︎ Triggers timely follow-ups
☑︎ Adapts to deal stage

6. Call Simulations & Coaching

AI improves reps before live calls.

Practice without pressure:

☑︎ Role-play prospect scenarios
☑︎ Handle objections on demand
☑︎ Get feedback without managers

How to implement AI in sales:

Start with the problem, not the technology.

- Define the outcome you want
- Decide how you'll measure success
- Choose personalization, scale, or time savings
- Then pick the right AI tool

AI won't fix a broken process. It scales whatever you already have.

Tool collectors get dashboards.
Problem solvers get pipeline.

Save this for later. Repost ♻️ for others.

6 AI Sales Use Cases Every Team Should Know

78% of sales teams adopted AI tools last year.

Only 12% saw measurable pipeline impact.

AI won't fix your sales process.
It will expose every broken part of it.

Most teams add AI tools and expect magic.
Then wonder why nothing changed.

The problem isn't the technology.
It's the implementation.

Here's how to actually make AI work in sales:

1. Start with the outcome

AI should change a business result.

Not "we're using AI now."
But "we're booking 40% more meetings."

→ More qualified conversations
→ Higher pipeline coverage
→ More selling time per rep

If you can't name the outcome, don't start.

2. Decide how you'll measure success

Without metrics, AI adds noise.

Pick your signals before you pick your tools:

→ Reply and engagement rates
→ Meetings booked
→ Time saved per rep

What gets measured gets improved.
What doesn't gets abandoned.

3. Focus on one leverage point

AI works best when scoped tightly.

Don't automate everything at once.
Pick one thing:

→ Personalization at scale
→ Prospecting volume
→ Admin and prep removal

Depth beats breadth every time.

4. Fix the bottleneck first

Automating everything fixes nothing.

Where does your process actually break?

→ Low response rates
→ Inconsistent follow-ups
→ Manual research overload

Find the constraint.
Then apply AI there.

5. Choose tools last

Tools should match the problem.
Not the other way around.

→ Automation for consistency
→ AI research for relevance
→ Workflows for repeatability

The best tool for the wrong problem is still useless.

AI doesn't replace strategy.
It amplifies whatever you already have.

Good process + AI = compounding results.
Bad process + AI = faster failure.

Fix the foundation first.

Save this for later. Repost ♻️ for others.

How to Implement AI in Your Sales Process

68% of outbound fails before the first message is sent.

The targeting was wrong from the start.

Most ICPs are just job titles in a spreadsheet.
That's not targeting.
That's guessing.

A real ICP filters out noise before you waste time on it.

Here are 5 criteria that define a high-quality ICP:

1. Role relevance

Start by narrowing to people who can act on what you share.

→ Focus on job titles tied to decisions
→ Prioritize functional ownership
→ Avoid roles with no buying influence

If they can't say yes, they're not your ICP.

2. Seniority level

Not all titles behave the same, even inside the same team.

→ Separate junior from senior profiles
→ Match message depth to authority
→ Adjust expectations for response speed

A Director and a Coordinator need different approaches.
Treat them the same and you lose both.

3. Shared context

Connections form faster when there's common ground.

→ Same events or communities
→ Mutual connections
→ Overlapping interests or topics

Cold outreach warms up fast when context exists.

4. Segment size

Small segments keep outreach human and relevant.

→ Cap segments at around 100 people
→ Maintain message quality
→ Enable real personalization

Big lists feel efficient.
Small lists actually convert.

5. Value fit

Only connect with people who would benefit from your expertise.

→ Would your content help them?
→ Would your insights apply to their role?
→ Would a conversation make sense?

If the answer is no, they don't belong in your ICP.

A sharp ICP doesn't limit your reach.
It multiplies your relevance.

Better targeting means better conversations.
Better conversations mean better pipeline.

Once you've nailed your ICP, comment "LGM" to get the full playbook on how to reach them.

♻️ Repost for priority access

5 Criteria That Define a High-Quality ICP

We hit #1 Product of the Day.

Here's the 5-step playbook:

1. Understand the Competition

Know the rules before you play.

20–40 products compete daily.
Product Hunt removes spam votes.
Outreach volume is capped.

2. Qualify Your LinkedIn Network

Target only real Product Hunt users.

Export your LinkedIn connections.
Identify contacts with PH accounts.
Exclude inactive or new accounts.

3. Run Pre-Launch Outreach

Secure voting pledges before launch day.

Start outreach 15 days early.
Follow up with non-responders.
Tag confirmed supporters automatically.

4. Activate on Launch Day

Message only people who already agreed.

No cold outreach on launch day.
Focus on confirmed supporters only.
Maximize limited message capacity.

5. Coordinate Your Team

Expand reach using your team's networks.

Each member runs the same campaigns.
Avoid duplicate messages.
Share qualified supporter data.

The real Product Hunt advantage:

- Pledges before launch day
- Activation only when it counts
- No wasted messages

Momentum comes from confirmed supporters.
Not last-minute asks.

Want access to the Google Sheet qualifier tool?

Comment "LGM" and I'll send it your way.

♻️ Repost for priority access

How to become “Product of the Day” on Product Hunt

2,000 companies. One campaign. €430k pipeline.

Here's how Invox built the system behind it:

1. They Rebuilt Around Three Pillars

They formalized how demand generation worked:

☑︎ Content creation as the base
☑︎ Audience development for reach
☑︎ Marketing automation for scale

Foundation first. Tactics second.

2. They Admitted Inbound Had Limits

Inbound alone could not support ambition:

☑︎ Market saturation increased
☑︎ Sales cycles got longer
☑︎ Scale hit a ceiling

Waiting for leads stopped working.

3. They Stopped Running One-Off Outbound

Manual outreach was wasting effort:

☑︎ Fragmented email campaigns
☑︎ Manual LinkedIn actions
☑︎ No multichannel logic

Random acts of outbound don't compound.

4. They Standardized a Campaign System with La Growth Machine

Outbound became structured and repeatable:

☑︎ 5–6 step sequences
☑︎ 60–70% LinkedIn, 30–40% email
☑︎ LinkedIn-first approach

Systems beat hustle every time.

5. They Measured What Actually Changed

Outbound became predictable, not random:

☑︎ 10 qualified discussions per month
☑︎ 50% of event leads from LGM
☑︎ 0% → 20% revenue influenced by outbound

Numbers don't lie. Gut feelings do.

6. One Campaign Proved the Model

Automation made scale possible:

☑︎ 2,000 companies analyzed
☑︎ Decision-makers targeted
☑︎ €430k pipeline generated

One campaign. Six figures in pipeline.

Inbound builds trust.
Outbound creates momentum.
Systems replace hope.

You don't choose one or the other.
You combine both and win.

Save this for later. Repost ♻️ for others.

How Invox Evolved from Inbound-Only to Outbound Success

In sales, speed is your only unfair advantage.
Your competitor replies in 2 hours. You reply in 20 minutes. You win.

But here's the question no one asks:

HOW do you actually reply in 20 minutes?

Most SDRs can't.
Not because they're lazy.
Because they're busy doing what matters: calls, demos, closing deals.

The reality:
Your outbound campaigns run automatically.
Sequences send. Follow-ups trigger. Everything flows.

But when a prospect replies?
You only find out when you remember to check.

→ Prospect replies at 10:15am
→ SDR finishes demos at 12:30pm, checks La Growth Machine
→ By then, 3 competitors already responded

Visibility determines velocity.

The 4-step system that creates speed:

STEP 1: ALERTS FIND YOU
Stop checking for prospect replies.

Integrate La Growth Machine with Slack.
Every prospect action lands directly there.

In a call? Alert waits.
Between tasks? You see it instantly.

STEP 2: ONE CLICK TO REPLY
No need to constantly monitor tools.

Slack alert → Click link → Reply in LGM → Done.
Total time: 45 seconds.

STEP 3: TEAM COVERAGE → NO MISSED OPPORTUNITIES
Alerts land in your shared Slack channel.
Your entire team sees what's happening.

Everyone knows the status.
Everyone can contribute.

No more wondering if someone handled that hot lead.

STEP 4: BLOCKERS DISAPPEAR
A profile is disconnected?
Slack alerts you. Fix it in seconds.

Campaigns never pause. Momentum never breaks.

Your competitor blocks calendar time to "check tools."
You catch alerts in real-time without breaking focus.

Try the new Slack integration on LGM with a 14-day free trial: https://lgm.rocks/006

Save this for later. Repost ♻️ for others.

No alternative text description for this image

Your prospects are showing buying signals right now.
But most outbound teams miss them completely.

They're still blasting cold emails to strangers.
No context. No timing. No warm intros.
The result? Low reply rates. Wasted effort.

Using intent data to reach out when it matters is the game changer.

Live session this Thursday at 6pm CET. 
Olivier Roth and 👨‍🔬 Richard F. Purcell will walk through real use cases using The Swarm 🔆 , Clay , and La Growth Machine  and show how to: 
→ Detect buying signals and competitive intent automatically

→ Find warm intro paths you didn't know existed

→ Turn these signals into sequences that actually convert

Real workflows. Ready to deploy.

Register now → https://lgm.rocks/icx

How do you currently spot buying signals?

taplio

The Battle

Ronnie Parsons

Brice Maurln

Followers

Posts

Engagements

Likes

Performance ScoreRonnie Parsons's LinkedIn Performance

Performance ScoreBrice Maurln's LinkedIn Performance

Ready to grow your LinkedIn presence?

taplio

The Battle

Ronnie Parsons

Brice Maurln

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Ronnie Parsons's LinkedIn Performance

Performance ScoreBrice Maurln's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScoreRonnie Parsons's LinkedIn Performance