Kevin Payne

GTM Engineer at LawVu | Building Revenue Systems For Impact Startups | A16z, YC & Techstars Portfolio

From the intersection of AI, Startups, and Web3. The future of tech belongs to impact driven creators and operators.

In 2020, I was a full-time contributor for publications with 200+ bylines in HubSpot, Crunchbase, Blavity and major tech publications. In 2025, I joined a Series A/B SaaS company as a GTM Engineer building AI-powered revenue systems.

Most operators choose one path: stay employed OR go solo. I'm proving you can do both without burnout. Build a portfolio career and diversify your sources of income one small bet at a time.

How I can help...

FOR CREATORS: If you're building a personal brand or content business, my frameworks show you how to learn in public (Learn > Create > Share) and monetize your expertise through the 5C model. Join 23K+ creators who follow my systems for scalable content and portfolio income.

FOR OPERATORS: If you're at a Series A/B company wanting to build portfolio income alongside your full-time employment, I show you how to prototype revenue systems in your operator role, document what works, then package that knowledge into content and coaching offers.

My Approach: I don't consult from the sidelines. I prototype AI systems in my operator role, document what works, then teach operators and implement for founders. Learn as an operator, share as a creator.

Current Focus: Building portfolio career through the 5C model:

- Clone
- Content
- Courses
- Community
- Conferences

Learning in Public: Learn in operator role > Create content documenting what works > Share with operators and founders. Get paid to learn, get paid to share.

Three Core Interests:

1. The Operator Stack: Leverage AI systems for sustainable growth
2. Portfolio Income: Small bets optimized for social impact
3. The Five-Pillars: Integrated life philosophy

Meta-Advantage: Teaching AI workforce implementation while using AI workforce to scale personal brand… authentic proof-of-concept.

Join 1K+ creators and founders getting their minds renewed. No fluff, just Growth Guides that merge biblical wisdom with proven AI systems.

Subscribe at https://substack.com/@kevintpayne or follow @kevintpayne.

Founder

Building a portfolio of digital real estate. Everyone’s familiar with real estate investments. It’s as simple as buying a house or land to rent or sell for profit. 

Digital real estate works the same way. Every domain name, every website and every blog you see online is internet property. They represent digital real estate you can buy and sell just like houses, apartments and lots.

I specialize in writing and speaking about solopreneurship, artificial intelligence, and minimalism. My mission is to document my journey and impart wisdom pertaining to wealth and health.

Building AI agents backward? 

Starting with tools, copying prompts, and then wondering why it all sounds like garbage?

The real issue isn't downstream... it's upstream.

Discover the game-changing framework here:

Your AI agents are mirrors.

They reflect your clarity of thought, your decision-making frameworks, and your values... whether you've articulated them or not.

Feed them confusion, and you get confident noise at scale.

I call this the Confident Idiot Problem.

AI tools are incredible at sounding certain. They deliver mediocre ideas with Fortune 500 conviction.

If you don't have your own convictions locked in, you mistake that confidence for quality.

The fix isn't better prompts.
The fix is clearer thinking.

Before I write a single prompt, I articulate:
→ What I've learned through direct experience
→ What I believe that peers would disagree with
→ What I refuse to do, even for money

Opinions vs. Convictions:

- **Opinion:** "AI will transform business."
- **Conviction:** "I only build AI that augments human judgment. Autonomous AI without oversight creates fragile systems."

One is a position you hold.
The other is a position that holds you.

The Conviction Stack has three layers:

1. **Identity** - Who am I?
2. **Framework** - How do I think?
3. **Output** - What does quality look like?

Most operators only provide AI with Layer 3, similar to asking someone to paint your house without specifying the color.

Here's the Conviction Audit:

- What have you learned the hard way? (Earned beliefs)
- What do you believe that peers would disagree with?
- What would you refuse to do, even for money?
- What frameworks do you use repeatedly?

Document everything.

Compile this into an Operating Philosophy.

~2,000 words that capture:

Who you are
How you think
What quality looks like
What you won't do

This becomes the master prompt for every AI system you build.


**Old approach:**
- Copy templates → Generic results

**New approach:**
- Load Operating Philosophy → AI uses your mindset for solutions

Same tools, but conviction transforms outcomes.

AI is your ultimate leverage tool, magnifying whatever you pour into it.

Fuel it with clarity → Watch your returns skyrocket.
Feed it confusion → Scale up a symphony of confident noise.

Dive into the full Conviction Audit framework here:

https://lnkd.in/g2GfRFqC

Urban night market with neon signs; a man stares at a holographic, digitized reflection displaying neural network visuals and code.

AI operators think in workflows, not words.

Stop tweaking prompts. Start designing systems.

Months of optimization led me to the breakthrough strategy of focusing on workflow design.

Here's how it reshaped the game:

Marginal gains. Infinite loops. Shaky outcomes.

Then it hit me: the flaw wasn’t in my prompts... it was in the architecture.

The Prompt Engineering Dilemma:

Solitary prompts are delicate. They shine in trials but crumble quietly in real-world use.

Context changes. Edge cases appear. The model confidently produces garbage.

You can't solve architectural problems through prompt engineering.

The Prompt Architecture Shift

Stop asking: "How do I improve this prompt?"

Start by asking: "How do I design a system for graceful prompt failures?"

This involves:

Decomposition

Break a complex task into simpler ones. Each prompt handles one function, and together they accomplish what a single prompt can't.

Validation Layers

The output of every prompt gets checked before the next step:

- Does this look right?
- Does it match the expected format?
- Does it contain the required elements?

Failures get caught. Reruns happen automatically. Bad outputs never propagate downstream.

Context Management

What information does this prompt actually need?

- Not everything.
- Not the whole document.
- Just the relevant context for this specific task.

Smaller context windows. More focused instructions. Better outputs.

Fallback Paths:

What's the plan for model errors?

Human help. New prompts. Quick recovery.

Our design handles setbacks. Failures are expected.

Prompt engineering refines; prompt architecture shapes the vision.

The other makes entire workflows reliably excellent.

The operators who win at AI aren't better at writing prompts; they're better at designing systems where prompts are just one component.

What's one workflow you've built that chains multiple AI calls together?

No alternative text description for this image

Silence is my secret weapon for productivity as I navigate the chaos of a portfolio career.

No calls, no content... just stillness.

Discover why this daily practice sets the stage for success.

I used to wake up and immediately check Slack.
Then email.
Then LinkedIn notifications.

By 7 am, my brain was already reactive... responding to everyone else's priorities.

None of my own.

The challenge of crafting a varied career: there's an endless list to tackle.

- Employment commitments
- Newsletter outlines
- Research projects
- Creative concepts

Without clear priorities, you chase after the loudest demand. 

The urgent takes precedence, while crucial tasks fade into the background.

So I flipped the order.

Now, the first 30 minutes of my day belong to silence.

Phone stays face down.
Do Not Disturb stays on.

The chaos can wait.
It always can.

What happens in stillness:

- You remember why you're building this.
- You reconnect with purpose before productivity.
- You create space between stimulus and response.

The notifications don't disappear; they just lose their power over you.

Here's the tactical version:

- Phone charges outside the bedroom
- First 30 min: prayer, reading, journaling
- No screens until stillness is complete
- Only then does the world get access

Simple. Not easy. Worth it.

The irony of building with AI and automation:

The more systems you create, the more noise you generate.

More notifications. More dashboards. More metrics.

Stillness is the counterbalance. It keeps the machines from running you.

I've noticed a pattern with burned-out operators:

- They're never alone with their thoughts.
- Every gap is filled with podcasts, scrolling, content consumption.

The mind never rests. The soul never recalibrates.

Breakdown becomes inevitable.

Portfolio careers demand more from you. More output. More context switching. More plates spinning.

But they also demand more stillness. More clarity on what matters. More space to hear what the noise drowns out.

If your mornings start with other people's emergencies, you've already lost the day.

Take back the first 30 minutes. Let the chaos orbit, but protect your center.

That's where purpose lives.

Calm man meditating cross-legged on floating platform, glowing "PURPOSE" orb at chest, muted apps and notifications hovering around him.

"Move fast and break things."

This advice works for startups.

It destroys enterprise GTM teams.

Don't learn this the hard way deploying AI with 50+ stakeholders.

Here's what actually works:

Startup reality:
→ Founder can mandate adoption
→ 5 stakeholders to align
→ Pivot takes a meeting
→ Failed experiment = learning

Enterprise reality:
→ 50+ stakeholders across departments
→ 90-day security review before touching data
→ Failed experiment = 12 months distrust

In startups, breaking things costs a weekend.

In enterprise, breaking things costs:

→ Trust with sales leadership
→ Budget for future initiatives
→ Political capital with executives
→ 6-12 months rebuilding credibility

The stakes are different.

The playbook must be too.

Enterprise Constraint #1: Security Review

Startup: "Let's try this tool today!"

Enterprise: "Every tool needs 90-day security review before touching production data."

Solution: Start with cloud-based tools that have existing enterprise compliance (SOC2, GDPR).

Enterprise Constraint #2: Stakeholder Alignment

Startup: CEO says go, team goes.

Enterprise: Sales, Marketing, RevOps, IT, Legal, Finance must align.

Solution: Build coalition before deployment.

Sell different value to each stakeholder.
Adoption follows buy-in.

Enterprise Constraint #3: Behavior Change

Startup: Small team, fast adoption.

Enterprise: 50+ people with established workflows.

Solution: Pilot with 5-10 users first.

Prove value → Document wins → Expand slowly.

Don't mandate AI. Earn it through results.

The Enterprise AI Playbook:

Week 1-4: Stakeholder mapping + buy-in
Month 2-3: Security review + pilot design
Month 4-6: Small pilot + edge case discovery
Month 7-9: Documented wins + expanded rollout
Month 10-12: Full deployment + optimization
Slow is smooth. Smooth is fast.

What actually works in enterprise:

Stage gates, not timelines
Stakeholder buy-in, not mandates
Documented processes, not tribal knowledge
Human-in-the-loop, not full automation
Proven pilots, not big bang launches

Boring? Yes.
Effective? Absolutely.

Reframe the goal:

❌ "Deploy AI as fast as possible"
✅ "Build organizational capability that compounds"

The company that deploys AI in 18 months with full adoption beats the one that deploys in 3 months with 20% usage.

Speed of deployment ≠ speed of value.

The enterprise truth:

Technology is 20% of AI adoption.
Behavior change is 80%.

You're not racing competitors.

You're building systems that compound for the next decade.

Move deliberately. Build coalitions. Earn trust.

That's how enterprise AI actually works.

The hardest season of my career became the foundation for everything after.

Here's what I learned building toward a portfolio career:

A few years ago, everything shifted.

The traditional path felt uncertain.

Instead of panic, I chose differently:

→ Rebuild intentionally
→ Stack skills strategically
→ Document everything

Here's what worked:

Lesson 1: Time is your most valuable asset.

Amanda Goetz talks about ruthless prioritization.
I mapped my week in 30-minute blocks.

The result:

60% of my time → 10% of outcomes.
Clarity changed everything.

Lesson 2: Your skills compound.

Myron Golden teaches that wealth follows value creation.

Instead of chasing any opportunity, I doubled down:

→ GTM systems
→ AI automation
→ Content creation

Three skills. Top 25% in each.
That combination is rare.

Lesson 3: Build in public.

Every problem I solved → documented.
Every framework I developed → shared.

This did two things:

Built credibility
Attracted opportunities I couldn't manufacture

SODOTO: Solve Own problems, Document, share. Others pay you to solve Theirs.

Lesson 4: Portfolio beats all-in.

One income stream = single point of failure.
I stopped chasing one big break.

Started building multiple smaller ones:

→ W2 stability
→ Content leverage

Different risks. Compounding together.

Lesson 5: Faith over fear.

The hardest part wasn't tactics.

It was mindset.

Trusting that disciplined action over time produces results.
Even when you can't see them yet.

"The plans of the diligent lead surely to abundance." — Proverbs 21:5

The key word: diligent.

Not frantic.
Not desperate.
Not scattered.

Diligent.

Consistent effort. Clear direction. Patient execution.
That's what builds foundations that last.

If you're in a season of transition:

The foundation you build during difficulty becomes the platform you launch from later.

Don't waste the struggle.

What season are you in right now?

I built a Second Brain in Notion that powers all 5 pillars of my life from one system.

Most knowledge systems fail because they're built for storage, not action.

Here's how I built mine differently:

Why most Second Brains fail:

→ Too complex to maintain
→ Capture everything, use nothing
→ No connection to output
→ System becomes a burden, not leverage

Information isn't valuable.
Information connected to action is valuable.

I rebuilt my system around this.

The SODOTO Framework:

Solve Own Problems
Document the solution
Teach Others

Every note I capture must pass the SODOTO test:

"Can I use this to solve a problem, document it, and teach it?"

If no → don't capture.
If yes → capture + connect.

My Notion Structure:

1. Inbox → Everything starts here
2. Projects → Active work 
3. Areas → Ongoing responsibilities (5 Pillars)
4. Resources → Reference material
5. Archive → Completed/inactive

Based on PARA, adapted for portfolio career.

I organize around 5 Life Pillars:

→ Faith (spiritual growth, social impact)
→ Fitness (health, longevity, energy)
→ Family (marriage, kids, homeschooling)
→ Finance (operator + creator)
→ Freedom (location independence, systems)

Every note connects to a pillar.

My Capture Workflow:

• Podcast insight → SuperWhisper → Notion inbox
• Article highlight → Readwise → Notion database
• Meeting note → Quick capture → Tag project
• Content idea → Voice memo → Inbox for processing

Capture is fast. Processing happens weekly.

Weekly Processing (30 min):

1. Empty inbox completely
2. Connect notes to projects/areas
3. Identify SODOTO opportunities
4. Create content ideas from learning
5. Archive what's not actionable

No note lives in inbox longer than 7 days.

Backlog = system failure.

The key: Connect to Output

Every learning connects to:

→ Blog post idea
→ Newsletter topic
→ Tweet thread
→ Consulting framework
→ Work project

I don't just capture.

I capture → process → connect → create.

The Second Brain feeds the Content Engine.

The Stack:

• Notion → Second Brain home
• Readwise Reader → Article/book highlights
• SuperWhisper → Voice to text
• Claude → Processing + connections

Total cost: ~$30/month

ROI: Entire portfolio career runs on this system.

The principle:

Don't build a Second Brain for storage.

Build it for action.

Every capture → connects to a pillar
Every note → passes SODOTO test
Every week → processing clears inbox
Every learning → becomes content

Information + action = leverage.

Start there.

Most AI transformations fail in the first 90 days.

Not because of bad tools.
Not because of bad timing.

Because teams skip Stage 1.

I built a 3-stage framework that changes everything:

The popular narrative:

"We need AI agents!"
"We need automation platforms!"
"We need the latest tech!"

The reality I keep seeing:

Teams are layering new tools onto broken systems.

You can't AI your way out of bad processes.
You can only accelerate them.

The GTM Stack Maturity Framework:

→ Stage 1: Optimize current stack (Foundation)
→ Stage 2: Layer agentic workflows (Intelligence)
→ Stage 3: Integrate automated workflows (Scale)

Each stage unlocked by completion + stakeholder buy-in.

Not calendar.

Stage 1: Optimize Your Current Stack

Before you add AI, ask:

• Is CRM adoption at 90%+?
• Is data quality above 85%?
• Are processes documented?
• Does each tool have measurable ROI?

If you can't answer "yes" to 80%+ of these...

You're not ready for AI.

Stage 2: Agentic Workflows

Start with internal, non-customer-facing tasks:

• Lead Research Agent (enrich leads with intel)
• Meeting Prep Agent (brief reps in 2 min vs 20)
• Competitive Intel Agent (monitor landscape)

Cloud-based = faster security approval.

The hidden value of Stage 2:

You're not just testing AI.

You're building a living wiki of edge cases:

"Research agent struggles with subsidiaries"
"Reps want briefs in Slack, not dashboards"
"Deals over $100K need human review"

This is your change management gold.

Stage 3: Automated Workflows

Now you connect everything:

Trigger: High-intent visitor identified

→ Enrich with data tools
→ Call Lead Research Agent
→ Create CRM lead
→ Route to correct rep
→ Notify via Slack
→ If >$100K, trigger human review

Zero manual work.

The principle that changes everything:

"Automation amplifies what's broken."

Broken process + automation = dysfunction at scale.

Optimized process + automation = compounding returns.

Automation is an amplifier, not a fixer.

Fix first. Automate second.

Technology is 20% of AI adoption.

Behavior change is 80%.

Don't sell "AI transformation."

Sell:

→ Sales: "Clean CRM = accurate forecasting"
→ RevOps: "Documented processes = less firefighting"
→ Executives: "System compounds over time"

Adoption follows trust.

Don't chase tools. Build systems.
Don't skip stages. Earn progression.
Don't optimize for speed. Optimize for compounding.

You're not racing to deploy AI first.

You're building capability that compounds for the next decade.

Follow for more.

There are only 4 ways to multiply your operational capacity.

Master all four, and you'll outpace competitors who only use one.

I call them the Four Powers.

Here's how they work together:

Power 1: AUTOMATE

Use AI to handle repetitive work.

Every task you automate is a task you never do again.

But automation alone isn't enough. It just makes you faster at what you already do.

The leverage comes from combining it with the other three.

Power 2: BUILD

Create custom tools without coding.

No-code platforms, AI builders, templates.

Build it once, use it forever.

The best operators don't just use tools—they create tools that fit their exact workflow.

Power 3: CREATE

Generate professional content across media.

Written, visual, video.

Content that teaches, attracts, and converts—without requiring your constant presence.

Your ideas, multiplied.

Power 4: CONNECT

Communicate clearly and build audience at scale.

Relationships are still the foundation. But technology lets you maintain more of them.

Authentic connection. Systematic reach.

The compound effect:

AUTOMATE frees time → More time to BUILD
BUILD creates tools → Better tools to CREATE
CREATE builds audience → Larger audience to CONNECT
CONNECT drives opportunities → More work to AUTOMATE

Each power amplifies the others.

The mistake most make:

They master ONE power and ignore the rest.

→ Great at automation but no audience
→ Great at content but drowning in ops
→ Great at networking but manually doing everything

The leverage comes from the combination.

How to assess yourself:

AUTOMATE: How many hours/week do I save?
BUILD: How many custom tools have I created?
CREATE: How much content am I producing?
CONNECT: How many relationships am I maintaining?

Score 1-10 on each. Find your weakest power.

The progression:

Start with AUTOMATE (free up time)
Then BUILD (create your toolkit)
Then CREATE (build your audience)
Then CONNECT (convert to relationships)

This sequence compounds faster than random skill-building.

Your turn:

Score yourself 1-10 on each power.

Which is your weakest?

That's where to focus next.

What's your lowest score?

Product Designer with 10+ years of experience in B2B SaaS, focused on solving complex user and business problems through data-informed design, user research and cross-functional collaboration. Proven track record of shaping product strategy and delivering intuitive solutions in HR tech, travel tech and developer tools.

Axel Lessio

I don’t think the design job market is broken because AI is replacing designers.

I think it’s broken because too many companies struggle to create meaningful products. Fewer products that deliver real value means fewer paying customers. Fewer paying customers means tighter budgets. And tight budgets don’t hire designers.

AI just gets blamed because it’s visible.

At some point, I realised nothing really fixes this from the outside. Not better portfolios. Not more tools. Not waiting for the market to bounce back. The only durable fix is companies that actually create a lot of value.

And here’s the uncomfortable part: creating that kind of value usually requires great design. Which means hiring designers. Which means we’re stuck in a chicken and egg situation.

That’s where design-led founders quietly change the equation.

For some designers, the odds are simply better building something small and useful than competing for a shrinking number of roles. Finding 500 customers willing to pay you 300 a year can be more realistic than finding one company willing to pay you 150k.

Not because entrepreneurship is easy. But because value creation is still rewarded, even when hiring slows down.

I don’t think every designer should become a founder. But I do think more designers underestimate how close they already are to solving real problems people would actually pay for.

2x dad. 10+ years designer. Still learning every day.

taplio

The Battle

Kevin Payne

Axel Lessio

Followers

Posts

Engagements

Likes

Performance ScoreKevin Payne's LinkedIn Performance

Performance ScoreAxel Lessio's LinkedIn Performance

Ready to grow your LinkedIn presence?

taplio

The Battle

Kevin Payne

Axel Lessio

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);}Kevin Payne's LinkedIn Performance

Performance ScoreAxel Lessio's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScoreKevin Payne's LinkedIn Performance