Founder of StrategyBreakdowns.com

TLDR: Worked in strategy consulting → Joined strategy team at Atlassian → Started writing strategy case studies → People liked them, so I left my job and went full-time

Tom Alder

8 things I've learned while living in Valencia for the past month:

1/ The "slow" culture made me realise how much day-to-day urgency you experience everywhere else.

2/ Europe is the best timezone - 4 hours of deep work before US Eastern gets online.

3/ The city is easy-going and beautiful, but not efficient. Restaurants with lines out the door and empty tables, busses show up 15 mins late (or not at all), 'the system is down' is almost a daily occurence.

4/ I love a siesta but find it nearly impossible to refocus afterwards. Better for marking the transition from work → life.

5/ Meeting people as a digital nomad requires more intentionality than I thought. 

6/ Everywhere you look, you see someone's creative touch. Tiles, balconies, door handles. Everything is decorative, even if in a small way. 

7/ I didn't see a single person on a laptop in a cafe. 

8/ Paella is more than just a regional dish. Everyone is quick to recommend their favourite spot, share tips and rules for ordering it correctly, and tell their Paella-based memories. People worship it here (rightly so!)

—

👉 P.S. If you enjoyed this post, you'll love my newsletter - a 3-minute breakdown of the strategy playbooks and growth hacks behind the world’s greatest companies.

Join 100,000+ strategy nerds from companies like Google, Meta, Atlassian, and Netflix: https://lnkd.in/g2FWfXGR

The team at beehiiv just showed me what they're launching next week.

I've analysed hundreds of product releases.

This one I'm gonna join live.

Most companies make tweaks and add tiny features.

beehiiv have been quietly building something that got me absolutely hyped.

Tyler Denk 🐝 and team have cracked something fundamental about how creators grow and monetise.

I can't share specifics (NDA), but here's what I can say:
If you're building a creator/media business in 2025, you should join us at the launch event!

Register here → https://lnkd.in/gh3tKmCZ

People always ask "How did you decide when to quit your job and go all-in?"

3 months after launching Strategy Breakdowns I told my boss I was leaving.

This was my napkin math:

The business was making just under $3k/mo.
~$2.2k from newsletter sponsorship, rest from affiliate revenue.

→ I was publishing 1 newsletter every 2 weeks
→ If I ran them weekly, that'd 2x sponsorship + 1.5x affiliate revenue

→ I had 1 sponsor per newsletter
→ If I had 2, that'd 2x sponsorship revenue again

→ I had 20k subscribers
→ If I grew to 50k, that'd 2x sponsorship + 1.5x affiliate revenue again

Q: If I quit my job, would the extra 40hrs per week be enough to publish 1 extra newsletter every 2wks, sell 4x as many ads, and speed-run an extra 30k subs by reinvesting all revenue into subscriber growth?

Once I laid out all the inputs, it became an easy 'yes'.

I could probably hit $10k/mo within a month or 2, even factoring some contingency if I couldn't sell 100% of my ad inventory.

Then if I kept growing the newsletter, and added new ways to monetise, I figured it wouldn't be too much drama to get to $20k/mo.

Quitting a high-paying tech job for a $3k/mo newsletter = crazy, risky, scary
Quitting a high-paying tech job for a (soon-to-be) $20k/mo newsletter = makes sense

Same business. 
Different frame.

Don't be afraid to math it out.
Goes a long way in building up conviction.

—

👉 P.S. If you enjoyed this post, you'll love my newsletter - a 3-minute breakdown of the strategy playbooks and growth hacks behind the world’s greatest companies.

Join 100,000+ strategy nerds from companies like Google, Meta, Atlassian, and Netflix: https://lnkd.in/g2FWfXGR

Valve makes $50 million per employee.

Microsoft? $18 million.
Apple? $2.4 million.
Meta? $1.9 million.

How does a 350-person gaming company eclipse every tech giant on the planet?

→ They built a 30% tax on PC gaming.

Every game sold on Steam. Every microtransaction. Every indie hit and AAA blockbuster. If it's sold on their platform, Valve takes 30%.

They do develop games themselves, but vast majority of their revenue comes from infrastructure, maintenance, and collecting.

What makes it even more remarkable:

Zero traditional management mechanisms.

Valve operates with a completely flat hierarchy. No managers assigning work. No executives approving projects.

Instead they pioneered several radical workplace practices like choose-your-own team, and peer-reviewed bonuses.

Your colleagues (not your boss) determine your compensation based on your contributions. The entire company votes on your impact.

The result:
336 employees shared $444 million in total compensation in 2021. That's an average of $1.3 million per person.

And the company is on track for $17 billion in revenue in 2025.

They proved something most large corporations forget:
You don't need more people. You need the right structure (business model + organisational model).

—

📖 If you liked this post, you’ll definitely enjoy my newsletter article Why Valve has no managers!

Take a look here: https://lnkd.in/gyDPxJQ5

Imagine you are a marketing manager working for Coca Cola in 1971.

To make your most important decisions, you might have access to things like:
• Sales info
• Customer surveys
• Financial metrics

IF you spend a few days (possibly weeks) digging around the company for them. Remember, no computers back then.

Now, imagine you had instant access to:

→ The 5x highest performing newspaper/billboard/bus-stop ads out of the 10,000’s of ads Pepsi Co are running globally.

→ Real-time dashboards showing the number of daily, weekly, and monthly walk-ins for a McDonalds store that you’re doing a deal with.

→ A system that tracks every soft drink consumer in the world, showing you exactly what magazine they are most likely to get their beverage news from, and accurate trend data showing you a spike in conversations about “sugar-free”.

All entirely for free, fully self-serve, without ever needing to contact any Pepsi staff, McDonalds partners, or magazine analysts.

That is the world we live in.

But most people don't fully appreciate this. 

Every internet user and interaction leaves digital footprints. These footprints (if you know where to find them) reveal insights that make traditional ‘strategy theory’ feel like guesswork.

Not leveraging an 'information advantage' for your most important decisions, projects, products etc today is like voluntarily boxing yourself into a cubicle at Coca Cola HQ in 1971.

My vote: let’s use the tools available to us!

That's why I created 'Websites & Traffic' - a training that transforms you into a modern data-driven strategist.

If you want to skyrocket your persuasiveness, impact, and progression (but you’re looking for a modern-day approach that doesn’t involve slugging through more abstract ‘strategy theory’), this is for you! 

→ https://lnkd.in/gcWA7dyd

Why change fails. Brilliant. 

Source: Lippitt-Knoster Model - The 5 Components of Organisational Change.

Amazon website from every year since 1997, in chronological order.

—

👉 P.S. If you enjoyed this post, you'll love my newsletter - a 3-minute breakdown of the strategy playbooks and growth hacks behind the world’s greatest companies.

Join 100,000+ strategy nerds from companies like Google, Meta, Atlassian, and Netflix: https://lnkd.in/g2FWfXGR

The Amazon website every year since 1998

AI NEWS: Fyxer AI ($1→25m ARR in 12mo) just dropped the biggest upgrade to their core product since launch.

Here's everything you need to know:

Fyxer's core product "Drafts" lives inside Gmail/Outlook, and it auto-drafts email replies in your voice for you to review, edit (if needed), and send.

They just released "Drafts 2.0" with a wall-to-wall revamp of product improvements:
→ better context searching (remembers past conversations to reply how you would)
→ dynamic tone detection (adapts to who you're emailing - client, manager, colleague etc)
→ smarter call scheduling (handles time zones automatically and finds times that suit everyone)

The result: users are now sending *twice* as many email drafts without edits.

Check out the draft it wrote below.

For anyone spending an hour+ on email: this is one of the apps that actually saves me tangible time + focus on a daily basis. 


For the product-led-growth nerds - onboarding is slick too. Starts working in 30 seconds with Gmail or Outlook signup. Automatically learns your voice. Zero setup or learning curve.

I love startups like this - simple idea with perfect execution.


Oh and I convinced the Fyxer team to give my readers a special signup offer https://lnkd.in/gsuYEPQP (Partner link)

This is how you print $$$ by running ads in newsletters:

(And no, it's not generic copy + CTA to 'sign up now')

I've run 100s of ads in my 100k reader newsletter.

Worked with the best growth marketers in the world at companies like Atlassian, Clay, Vanta etc and I think I might have the highest renewal rate in the industry.

Here is the no-fluff playbook for getting results from newsletter ads:

1/ Less is more.
Longer ad copy (and longer sentences) ALWAYS perform worse. This may seem counterintuitive, I know it's tempting to write paragraphs about your product, but the quicker readers can internalise your message the more likely they'll read it in full. Aim for ~3 sentences / bullets total.

2/ Scannable format
Our best performing ads have the following characteristics:
- Start with a catchy, intriguing, spicy headline in *bold*
- Short punchy lines/lists with line breaks for breathing room
- Button with unique CTA ("Show me my security score", "I want the free playbook")

3/ Specific objectives.
Don't assume the newsletter knows what you want. People default to impressions/clicks, but every time I dig deeper there's a more important goal: "I want our founding story going viral", "I want a pretty report with data and community screenshots to share with my boss (my promotion is coming up)", "I want to run an isolated test to see if a waitlist/free trial/free plan works for us". 

4/ Don't just run 1 ad. 
I'm not saying this because more ads = more spend. There are 3 reasons you NEED to test with multiple ads: a) it takes multiple touchpoints for decision-makers to take action (when was the last time you saw a brand for the first time and 30s later you're on a $99/mo plan?), b) you test multiple angles to learn what resonates, c) most newsletters do bundle discounts so its cheaper per ad/open/click. 1 ad = throwing money away.

5/ Keep a swipe-file.
Seems obvious but not enough people do this. Collate your highest-performing social posts. Your competitors' best FB ads. Your best-converting landing page. Leverage these for your ad copy - don't ever start from scratch.

6/ You want partnership, not just sponsorship.
If your 'partner' isn't actively helping you tighten your copy, learn from the data, leverage their high-performing assets, investing their own money + time + resources into ensuring you win, you need to run.

7/ Backend funnels are magic.
This might be the most important alpha of all. The sponsors that are ripping right now do some variation of: run ads to a lead magnet/webinar → capture email → survey to segment (optional) → email nurture with education + social proof + objection-handling → sales handoff to book a demo/whiteglove/welcome offer. 1 person can build this in 1 day with AI, and it gets >10x better results per ad.

I have just 3 ad slots in my newsletter left this year, then I'm increasing prices for '26. 

If you're targeting strategy nerds (founders, PMs, devs), DM me!

5 unconventional tactics I learned at Atlassian (your company should copy these):

1. Everyone reads customer feedback (literally everyone)

Every week, every employee gets an automated email with 3 randomly selected verbatim quotes from customers. Bug reports, success stories, feature requests.

Over time you start spotting patterns. You develop intuition for customer sentiment. When you're proposing something, you can back it up with qualitative data you rememeber reading.

2. No PowerPoint allowed, only memos

Good writing is good thinking. You can disguise terrible ideas with pretty slides.

Every idea, every meeting, every project, every roadmap lives as a Confluence page. Writing out your ideas forces you to get specific about what you actually want to say (and why it matters). 

3. Every team has visible KPIs

Based on your team and role, you always knew exactly what metric mattered most. OKRs aren't perfect, but they create MASSIVE clarity of direction.

You also always knew what your KPI was driving at the division or company level (ie. what it "rolled up" to). Month commentary from owners explaining movements makes it easy to tell what matters to teams across the whole company. 

4. Open by default

Jira boards and Confluence pages have full organisational sharing permissions toggled on by default. This is a small but hugely significant product design choice.

Unless you actively close it off, everyone in the company can find, read, and comment on your work. Google Docs and Word don't do this – which means every new doc feels "yours" instead of "ours." 

5. Roll out to employees first

When I worked there, Atlassian had over 10,000 employees. That's a pretty sizable testing ground, and every mature product team would roll out changes to Atlassians first (who were using these tools every day).

This lets you catch bugs and bulletproofs ideas before paying customers see them, and creates a friendly space for candid feedback.

The pattern: make transparency and feedback the default (not the exception) for every product, decision, and idea.

Happy building.

—

👉 P.S. If you enjoyed this post, you'll love my newsletter - a 3-minute breakdown of the strategy playbooks and growth hacks behind the world’s greatest companies.

Join 100,000+ strategy nerds from companies like Google, Meta, Atlassian, and Netflix: https://lnkd.in/g2FWfXGR

Cross-functional operations leader with a Harvard Economics degree and a PhD in Economics from the University of Chicago. I help organizations scale efficiently by combining commercial strategy, advanced systems, and team alignment.

I’ve led companies through rapid growth, international expansion, and large-scale transformation, delivering measurable financial and operational results. My focus is on building adaptable systems, integrating AI-native solutions, and aligning stakeholders around data-driven decision frameworks.

Key achievements:
→ Scaled a B2B inventory management firm from $25M to $75M while expanding into international markets
→ Negotiated and structured 7–8 figure Fortune 500 contracts
→ Implemented enterprise systems and automated workflows, cutting cycle times and driving operational efficiency
→ Designed AI-enhanced workflows (pricing intelligence, candidate evaluation, productivity automation) that delivered measurable business outcomes

I bring both strategic vision and operational rigor, combining analytical depth with relationship-building to lead distributed teams across regions and time zones.

Core strengths:
→ Competitive operating & go-to-market strategy
→ Cross-functional team orchestration
→ Enterprise system & workflow automation
→ AI-driven operational scaling
→ International expansion & P&L growth

I share insights on these themes in my newsletter Operating by John Brewton, exploring how companies can evolve and thrive in the AI-enabled future of work.


John Brewton

The most powerful organizations in the world don’t just have one operating system. 

They run two. 

Behavioral economists call this the “Dual Operating System” of the human mind: 

1️⃣ System 1—fast, automatic, intuitive
2️⃣ System 2—slow, deliberate, analytical

The Kahneman-Tversky Revolution

In 1974, Daniel Kahneman and Amos Tversky published “Judgment Under Uncertainty: Heuristics and Biases” in Science. 

They documented how people systematically rely on mental shortcuts that lead to predictable errors.

This research culminated in their 1979 Prospect Theory. For this work, Kahneman was awarded the Nobel Prize in Economics in 2002, the first psychologist ever to receive the honor.

Two Systems, One Mind

System 1 is the brain’s autopilot, quick, associative, effortless. It lets us read a room, sense danger, or make expert judgments. It thrives in stable environments where experience has taught us the patterns. But it’s also the source of cognitive bias. It prefers stories that make sense over truths that are complex.

System 2 is slow, energy-demanding, reflective. It steps in when we face problems that are novel, ambiguous, or high-stakes. It’s capable of strategic reasoning and long-term planning. 

But it’s also lazy. It tends to rubber-stamp System 1’s conclusions unless explicitly provoked.

Organizational Implications
Teams rely on fast, intuitive System 1 thinking. It works until the environment changes or the stakes rise. Then leaders scramble to switch to 
System 2, rigorous analysis, scenario planning, deep reflection.

The best companies don’t wait for a crisis to make that switch. They design decision triggers—clear moments when deliberate thinking must be activated: when decisions are irreversible, when uncertainty is high, when novelty overwhelms precedent, when the cost of error is existential.

The goal isn’t to suppress intuition. It’s to build an organization fluent in both modes—instinctive enough to act fast, disciplined enough to know when to slow down.

Which system runs your organization right now—and is it the right one for the decision in front of you?

I write about the history and future of operating companies every day.

Subscribe to Operating by John Brewton, the only newsletter you need to become an elite operator (📬🔗 in comments).
Found this valuable?

♻️Repost to help others

Follow me, John Brewton, for more content about operating.​​​​​​​​​​​​​​​​

Further Reading: 

📖 Thinking, Fast and Slow by Daniel Kahneman (2011)  
The definitive exploration of dual-process theory: 
https://lnkd.in/exw33ymn
📄 “Judgment under Uncertainty: Heuristics and Biases” — Tversky & Kahneman, Science (1974)  
https://lnkd.in/eK9ZFG-E
📄 “Prospect Theory: An Analysis of Decision under Risk” — Kahneman & Tversky, Econometrica (1979)   
https://lnkd.in/eArC58aC

Operating Strategist 📝Writer @ Operating by John Brewton 🤓Founder @ 6A East Partners ❤️🙏🏼 Husband & Father

A bubble is when everyone can see the value creation, 
but no one is thinking about the value capture.

Andy Wu nailed the entire AI boom in one sentence.

Pets.com proved pet e-commerce worked. 
Then went bankrupt in 2000. Investors lost everything.

Chewy(dot)com does the same thing today, but with a $10B market cap. 

Same value creation. 
Different value capture.

This is the difference between FINANCIAL bubbles and INDUSTRIAL bubbles.

Financial bubbles (2008 subprime) destroy wealth and leave nothing behind.

Industrial bubbles (dot-com, railroads, AI) destroy investor capital but BUILD infrastructure that outlasts the speculation.

The AI boom is creating $4.4 trillion in real assets: 
chips, data centers, power generation, fiber networks.

MIT research shows 14% productivity gains already. 

These aren't promises. 

They're operational improvements happening in the immediate. 

Will AI stocks crash 50-70% like dot-com? Maybe.

Will the infrastructure disappear? No.

Will society benefit even as investors lose? 

Absolutely.

As operators, we face a different question than Wall Street:

Not "Will the bubble pop?" but "Where does my capital create most value?"

$10,000 in Nvidia stock? Or $10,000 in AI tools giving you 14% productivity gains you can measure, control, and compound?

For most operators, the answer is clear: invest where you control the asset.
You can be RIGHT about value creation (AI will transform everything) and still go BANKRUPT being early on value capture (wrong companies, wrong prices).

Industrial bubbles punish individual timing. But they reward patient builders who inherit the infrastructure at fire-sale prices after the speculation burns out.

Are you positioning for the Pets(dot)com pain, 
or the Chewy infrastructure opportunity?

For more thoughts on bubbles, check out my new article at Operating by John Brewton on Substack: https://lnkd.in/e8t-7P85

I write about the history and future of operating companies every day.

Subscribe to Operating by John Brewton, the only newsletter you need to become an elite operator (📬🔗 in comments).

Found this valuable? ♻️Repost to help others

Follow me, John Brewton, for more content about operating.

The Fed is forecasting the singularity. 
What a time to be alive. 

The Federal Reserve Bank of Dallas recently charted four scenarios for how AI could reshape U.S. economic growth. 

The divergence is staggering.

The Baseline (1.9% annual growth)

Conventional innovation continues. Steady, predictable, uninspiring. This is what we’ve seen for decades.

Modest AI Boost (2.1% annual growth)

A small nudge upward. Incremental productivity gains compound over time. For operators, this means gradual margin expansion and process optimization—familiar territory with better tools.

The Singularity Scenario (Explosive growth)

Superintelligent AI transforms everything. Economic growth reaches levels never experienced in human history. What does “operating a company” even mean when AGI can outthink entire organizations?

The Catastrophic Scenario (Economic collapse)

Mismanaged transformative AI triggers existential risks. Growth inverts. This isn’t science fiction—it’s a credible risk scenario mapped by central bank economists.

The gap between these futures isn’t academic. It’s operational. Your strategic planning horizon just expanded from quarters to decades, but your decision-making window compressed to months.

Which future you’re building toward matters more than your current competitive position.

Are you positioning your company for gradual AI-enabled improvement, or are you preparing for a world where the fundamental rules of business get rewritten?

I write about the history, economics of operating companies every day.

Subscribe to Operating by John Brewton, the only newsletter you need to become an elite operator (📬🔗 in comments).

Found this valuable?

♻️ Repost to help others. 

➕Follow John for content about operating.

The part the headlines, conversation on the socials and amongst friends will miss. 

- j -

taplio

The Battle

Tom Alder

John Brewton

Followers

Posts

Engagements

Likes

Performance ScoreTom Alder's LinkedIn Performance

Performance ScoreJohn Brewton's LinkedIn Performance

Ready to grow your LinkedIn presence?

taplio

The Battle

Tom Alder

John Brewton

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);}Tom Alder's LinkedIn Performance

Performance ScoreJohn Brewton's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScoreTom Alder's LinkedIn Performance