Marcos Rivera

Most B2B SaaS leaders build value.
But forget to capture it.

Let me guess:

- You’re guessing your price
- You’re losing revenue
- Scaling feels stuck

What if pricing could drive growth?

Here’s what I help you do:

→ Capture more value
→ Make pricing your edge
→ Build pricing confidence

Why should you trust me?

- 25+ years in tech pricing
- Ex–Head of Pricing at Vista Equity
- Priced 400+ SaaS products
- Author of *Street Pricing*
- Trusted by MBAs and SaaS CEOs

Beyond coaching, 

I’m an:

→ Investor 
→ Speaker
→ Entrepreneur 

passionate about helping businesses unlock their full revenue potential.

Ready to take control of your most powerful growth lever—pricing?

Checkout my featured section.

Founder and CEO

We help growth-stage B2B SaaS companies design the right pricing model to scale up

Ready to shift your pricing from guesswork to framework?

For the first time in my career, I lowered our growth forecast.

A few weeks into 2026, and I made a decision that felt counterintuitive: we're going to grow less this year. On purpose.

Here's my thinking.

I've been watching F1 lately, there's a scene in the new movie where Brad Pitt tells the pit crew: "Slow is smooth, and smooth is fast."

That line stuck with me.

What got us to 25 people and on the way to $10M bootstrapped isn't going to get us to the next stage. 

We're about to launch our first product. 
We're shifting from pure services to technology-enabled transformation.

That's a pivot. And you can't pivot at full speed.
The sports analogy holds up everywhere. 
Tennis, basketball, skiing, you have to slow down before you change direction. 

Get your balance underneath you. 
Build momentum. 
Then move.

Business is no different.

Here's what slowing down actually looks like for us:
→ Keeping quality at 98% satisfaction instead of chasing volume.
→ Reducing the number of engagement types. Fewer SKUs, less variability.
→ Saying no to projects that don't fit the middle of our fairway, even when the money's good.

Why? Because it's way harder to recover from a quality drop than a revenue dip. 
One bad quarter of delivery can undo years of reputation.

If you're considering a similar move, here's my framework:

1/ Identify the pivot. 
2/ Reduce variability first. 
3/ Protect what got you here. 
4/ Get alignment before you announce. 

The target is lower now. 
Less ambitious. 
But it's more achievable, and it sets us up for what's actually coming.

Sometimes slowing down is the most aggressive move you can make.

What's a decision you've made that felt counterintuitive but turned out right?

CEO of Pricing I/O • Award-Winning Author • Sought after Slayer of Bad Pricing

Everyone told me I was crazy to leave.

High-paying role at a PE firm. 
Direct access to a billionaire's inner circle. 
I was flying to portfolio companies on 24 hours notice, promising boards 18% revenue increase, and delivering.

But I was hitting airline status in two months flat, with a 4-year-old at home and a daughter on the way.

So I walked away and started Pricing I/O with a credit card and my savings.

That was the beginning. 

We're 25 people now, approaching $10M, and I still get a little stunned when I see how many seats we fill at team get-togethers.

I sat down with Mark Osborne, MBA, CEPA® on the B2B Growth Blueprint podcast and got into the full journey—the leap, how we actually scaled, and the leadership framework I use to run the business today.

Watch the full conversation:
→ https://skd.so/kPle2t

Most SaaS companies are pricing blind.

They copy competitors who are also guessing. 

They slap "AI-powered" on the pricing page and hope it justifies a premium. 

They build credit systems because everyone else is doing it, without understanding why credits work for Audible but might destroy their business.

And then they wonder why sales cycles drag, why customers push back on renewals, why the board keeps asking uncomfortable questions about unit economics.

We all have seen this pattern. Right?

→ The CEO who approved a "usage-based transformation" only to watch churn spike 40% because customers couldn't predict their bills.

→ The VP of Product who spent 6 months building an AI feature, then gave it away for free because nobody knew how to price it.

→ The founder who copied HubSpot's model without realizing HubSpot has 15 years of pricing iteration behind every decision.

Here's what I've learned: pricing isn't a simple math problem. 
It's a strategy problem disguised as a spreadsheet.

Is to understand the psychology behind why customers say yes, and structure their pricing to remove friction, not add complexity.

That's why I built this playbook.

A single page with the frameworks we actually use when we're in the trenches with B2B SaaS clients.

It's dense, but I can send you the high-res version. 
Comment "playbook" ↓

Today Satya Nadella leads a $3 trillion company with 228,000 employees.
But when he took over in 2014, Microsoft was stuck.

Losing mobile. 
Windows-obsessed. 
Falling behind Amazon in cloud. 
→ Market cap at $300 billion while competitors lapped them.

Most people expected a safe, incremental CEO.
Instead, Satya rewired the culture without burning it down.

Killed the stack-ranking system that turned teams against each other. 

Replaced "know-it-all" with "learn-it-all." 
Bet everything on cloud when Azure was still a distant second to AWS.

That bet alone now generates $75B+ in annual revenue.

But what I admire most isn't the strategy.

Technical depth. Emotional intelligence. Business instinct. 
Most leaders I've worked with have one, maybe two. Satya has all three, and deploys them quietly.

No theatrics. No ego. 
Just calm, steady decisions at a scale most of us can't comprehend.

He turned a legacy software company into the world's second-most valuable business by doing what every great leader must: read the room, commit to the shift, and bring the whole organization with you.

That last part, bringing people with you, is the hardest part of any transformation. Pricing, product, culture, doesn't matter.

I've seen it across hundreds of companies. 
The team leading the change matters more than the change itself.

A decade of selling B2B SaaS to PE firms teaches you something most pricing strategists never learn firsthand.

James joined us as a Pricing Strategist after years on the other side of the table.

If you've ever sold to PE, you know, they understand value as well as anyone, and they're ruthless about ROI.

That experience shaped how James thinks about pricing: always tie it back to quantifiable business outcomes. Never be vague about value drivers. Surface the trade-offs so clients can make better decisions, not just hear what they want to hear.

That mindset is exactly why we wanted him here.

What surprised him most about joining?
"We're a lean organization that punches well above its weight. Everyone on the team is incredibly sharp and moves fast."

He also mentioned being staffed on two client projects in his first week. That's not an accident, it's a vote of confidence in what a sales background brings to strategy work.

His mindset says it all.
Sales and product team alignment is the most crucial step in executing any pricing strategy.

Simple. True. And something most companies underestimate until it's too late.

Oh, and his karaoke song is "Escape (The Piña Colada Song)."

Make of that what you will.

Glad to have you on the team, James.

"Claude, let's code this SaaS, try not to hallucinate this time."

Honestly? We're getting there.

Recently we watched founders spin up products in weeks that used to take engineering teams 18 months.

→ Claude writes the code
→ Cursor ships the features
→ Bolt scaffolds the whole thing

But then the product is live, and someone asks: 
"What do we charge for this?"

That's where the vibe coding stops.
Because pricing isn't a code problem.

It's a "which metric scales with their success" problem.
It's a "what does your customer actually value" problem.
It's a "what does your board need this to say about your business" problem.

I've worked with 400+ SaaS companies. 
I've never seen a model spit out the right answer to those questions.

Not because AI isn't smart enough.

Because the answer lives in your customers, your data, your market, and someone who's seen enough patterns to know the difference between a pricing model and a pricing strategy.

That's still a human job.

If the pricing conversation is already giving you a headache, that's exactly what we do at Pricing I/O.

Let's talk.

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$285 billion wiped from software stocks in 48 hours.
The reason? Investors finally realized what we've been saying for 2 years, per-seat pricing breaks when AI agents replace human users.

Salesforce lost 7% in a day. ServiceNow, Adobe, Workday, all hit.

But here's what's wild: most SaaS companies I talk to are STILL running per-seat models with zero backup plan.

The "SaaSpocalypse" wasn't a surprise. 
It was a pricing model catching up with reality.

If your revenue model depends on headcount growth, and AI is shrinking headcount, and just like that: you have a monetization crisis.

"Rapid pricing experimentation" is dangerous advice.

I keep seeing the same pitch from billing platforms and entitlement tools: configure your pricing, launch a test, learn fast, iterate, repeat.

Sounds great in theory.

If you're selling a $9/month product to 100,000 users? Sure. 

Test away. Change that $9 to $9.99 and see what happens. 
You've got statistical significance and low stakes.

But if you're negotiating a $150K deal with a CFO at a Fortune 500?

→ Try explaining that your quote from last week was "just a test."
→ Try telling your sales reps that pricing changed again—third time this quarter.
→ Try building credibility when the prospect remembers seeing different prices six months ago.

Expertise over experimentation. 
That's my stance.

I'm not against testing. 
Testing is essential. 

But blind, rapid iteration creates more problems than it solves: internal confusion, external credibility risk, sales teams who don't know what to sell, and customers who don't know what to trust.

The answer isn't more speed. 
It's more intention.

Informed. Measured. Deliberate.

If your team is about to make a pricing decision too fast, that's exactly what we work through at Pricing I/O. Drop a comment or DM me.

Most SaaS companies blame product for churn.
But the data usually points somewhere else: pricing.

3 steps. 10 minutes. 
You'll know if churn is pricing-driven or product-driven.

Segment by cohort. Compare NRR vs. LTV. 
Read churn surveys for the real signals.

If customers say "can't justify cost", that's not a product problem.

2026 is the year the pack separates.
Not with a dramatic crash, more of a slow exposure.

On one side: companies that are deliberate about AI integration, honest about their metrics, and strategic about pricing.

On the other: the copycats. The aimless AI adopters. The ones chasing "Wishful Thinking ARR" with creative revenue definitions and 50x valuations.

The fallout we expected in 2025? 
I think it shows up in 2026. 

Here's why:
→ AI scrutiny goes up (budgets need justification now)
→ Differentiation pressure increases (the checkbox AI gets exposed)
→ Companies under pressure make desperate pricing moves

And here's the opportunity: the smart operators will start picking up technology AND talent from the companies that couldn't adapt.

Acqui-hiring in 2026 is going to be massive.

The question is: which side of the separation are you building for?

The best pricing leaders are readers.
And these are the 12 books every SaaS pricing expert should read.

Save this one to read later ↓

→ Month 1:
Monetizing Innovation
The Pricing Roadmap

→ Month 2:
Street Pricing
Blue Ocean Strategy

→ Month 3:
The Cold Start Problem
Hooked

→ Month 4:
The Go-To Market Handbook
The Lean Startup

→ Month 5:
Influence
Predictably Irrational

→ Month 6:
The Art of Pricing
The Subscription Boom

If you want to go deeper than books, this is what we work on every day at Pricing I/O.
Drop a DM and let's talk.

After working with 400+ SaaS companies, I see three types when it comes to AI integration, and only one of them survives the next 2 years.

Most companies say they're using AI.
Very few can explain why.

The difference isn't budget. It's not talent either.
It's whether AI is a checkbox or a strategy.

Some companies know exactly where AI fits in their pricing, packaging, and go-to-market. 

They've mapped the ROI. 
They've planned the process change.

Others bolted AI onto a roadmap with no monetization strategy behind it, and their boards are starting to notice.

Where does your company fall on this spectrum?

I almost lost myself to AI news last year.
Every day there was something new. 

OpenAI did this. Anthropic launched that. Google's catching up. Startups raising at 50x revenue.

I was reading everything. 
Trying to understand every perspective. 
Watching every announcement.

And then I noticed something: 
I was paying less attention to my team.

The conversations were shorter. 
The check-ins were surface-level. 

I was physically present but mentally somewhere else, chasing the next headline, the next hot take, the next "you need to know this" thread.

FOMO was pulling me away from the work that actually matters.

Here's what I've been obsessing over instead: clarity.

Not mission statements. Not OKRs. 
Actual clarity, where your team can articulate what they're doing, why they're doing it, and how it connects to where you're going.

It sounds simple. 
It's brutally hard.

I've started asking my direct reports one question:
"Do you understand what we're doing and why?"

If they have a different point of view, I want to hear it. 
If they're confused, I need to know. 

A 10-second answer tells me everything: 
"Yes, I get it, I think we're going the right direction." 

Great. But more often, that question opens a door to something I was missing.

Here's my test:
→ If you have 5 direct reports and all 5 say the same thing about your direction—high five, you're leading well.
→ If all 5 have completely different views of what you're trying to do? That's not a them problem. That's a you problem.

People can feel when you're paying attention. 
They can also feel when you're not.

Forget FOMO. Focus.

2026 isn't the year SaaS dies.

It's the year people finally realize AI needs SaaS as much as SaaS needs AI.

Distribution, data, workflows, customer trust, none of that disappears because ChatGPT exists. 

But the SaaS companies scrambling to slap "AI-powered" on their pricing page without rethinking what they actually deliver? Those are the ones in trouble.

We've watched this play out across hundreds of companies.

Companies treating AI like a feature are missing the real forcing function, the question they've been avoiding for years: what outcome are we actually selling?

Seat-based pricing made sense when humans were the unit of consumption. 

When AI agents are doing the work, you're not selling seats anymore, you're selling results, throughput, outcomes that scale beyond headcount.

Most SaaS companies haven't touched their pricing model in years. 
AI just made that procrastination expensive. 

→ Boards are asking harder questions. 
→ Valuations are getting squeezed. 
→ And every month without a clear answer is revenue left on the table.

To surf the hype in 2026, get deliberate about monetizing what AI actually delivers.

That's what we spend every day working on at Pricing I/O, and the urgency we're hearing from founders and boards right now is unlike anything from the last few years.

The window to get ahead of this is open. It won't be for long.

I had to look in the mirror and ask myself a hard question.
Am I drinking my own Kool-Aid?

I've sat in rooms with founders who had their goggles on. 
Convinced they're smarter than everyone. 
Convinced the market is theirs for the taking.

And I've watched them fail.

Smart. Ambitious. Dedicated. Motivated.
Still failed.

So when I started building our new product, I made myself three promises:

1/ Assume there won't be a warm reception.
2/ Assume my assumptions are wrong.
3/ Assume this is a longer journey than I think.

Mike Tyson said it best: 
"No plan survives the first punch in the face."

We're going to get punched in the face. 
Every product does.

The question isn't whether it happens. It's how we react.

So instead of chasing a blowout launch, I'm building systems. 

Feedback loops. 
Prioritization frameworks. 
Quick cycles to learn and pivot.

How do I figure out how to figure out stuff?

That's the real question.

If we get a blowout launch? Hallelujah.

But I'm planning for the worst and hoping for the best.

Building something new is freaking hard. 
And it's full of trapdoors.

What's one assumption you're making about your business that might be wrong?

I think Mark Benioff is overrated.
I'll say it out loud.

Look, Salesforce is the godfather of SaaS. 
Many people give it that title, and it's earned. 

They pioneered cloud software. Built a $40B+ company.

But I think that was more Mark's team and the great people he had around him than Mark himself.

He's good at sales. He makes smart decisions. He’s a pioneer.  
I'm not saying he's bad.

But I lost a lot of respect for him when he said AI would be easy. 
That he could sell the world on his AI overnight.

That's obnoxious.

AI isn't easy. Anyone who's actually building with it knows that. 
Anyone who's helping companies integrate it knows the complexity, the change management, the friction.

Saying "AI is easy" tells me you're selling, not building.

I'd rather follow leaders who are thoughtful than leaders who are loud.
Give me Satya Nadella's calm over Benioff's bravado any day.

Pricing for the wrong thing is one of the most expensive mistakes I see.
(And still most companies miss this completely)

In a PLG motion, pricing does the heavy lifting early. 
→ It's the packaging, the free tier boundary, the upgrade trigger that converts users before a human ever gets involved.

In a sales-led motion, pricing shows up late. 
→ It's a negotiation lever, a discounting battlefield, and often an afterthought bolted onto whatever the rep promised on the call.

I've seen 400+ SaaS companies try to use the same pricing playbook for both motions. 

It doesn't work, because the moment where pricing creates or destroys value is fundamentally different.

The consequences cascade:
→ Your packaging
Does it need to sell itself on a webpage, or does it need to survive a 6-month procurement process?

→ Your discounting exposure
PLG has almost none. Sales-led can hemorrhage 20-40% if there are no guardrails.

→ Your expansion path
PLG expands through usage and upgrades. Sales-led expands through rep-driven upsell conversations.

→ Your pricing team's focus
Optimizing conversion rates vs. optimizing deal structures.

Neither is wrong. 

Your go-to-market motion dictates where your pricing has leverage.

If you're not sure your pricing is built for your motion, that's the first thing we diagnose at Pricing I/O. 

To book a free discovery call drop me a DM.

Most companies wait until something breaks to revisit pricing. 
Here are the 7 signals it's time to take a closer look.

In this video I'll talk you through:
→ Triggers that indicate pricing needs attention
→ Why "not the right time" is costing you money
→ Common patterns from 400+ SaaS companies

#saas #pricing

When people ask who I'm being inspired by, I don't have a good answer.

I never looked for figures to follow.
No heroes. No role models I'm trying to copy.

Just me, trying to make more good decisions than bad decisions. 

Keep learning forward. 
Treat people right.

That's it. That's the whole philosophy.

I like outside perspective. I get inspired by others. But what works for them doesn't necessarily work for me.

And I think that's okay.

Not everyone needs a leader to chase.

Some of us just need to stay honest with ourselves about where we're strong and where we're not.

Be introspective. 
Be blunt with yourself. 
Make trade-offs intentionally.

In the end, business is all about getting people to do stuff for you. 

→ Engineers to build for you
→ Employees to work for you
→ Customers to buy from you

Once you figure out how to do that, there's really no limit to what you can do.

No heroes required.

SaaS Founder: Stop copying competitor pricing pages.

That pricing page you're copying was built for a completely different business.

Here's how to fix it.

Watch more pricing insights here https://skd.so/E9ur5M

I'm a co-founder & CEO of Schematic -- an entitlements and monetization platform built on top of Stripe Billing. 

Our thesis is that AI transforms B2B monetization. 

SaaS monetization was static & seat-based. 

AI monetization is hybrid pricing & hybrid selling across multi-product offerings. 

Developers shouldn't have to reinvent the wheel when it comes to implementing & maintaining pricing & packaging. Product & growth folks should be able to control and iterate on monetization without code changes. They should be able to operate with speed and easily align their product roadmaps with continuous pricing & packaging releases. 

The future of monetization looks far more like telecoms in the 90’s than SaaS in the 2010's.

Enough about that.

As a kid, I wanted to play professional soccer, and I pursued that into my early 20’s, playing collegiately & then semi-professionally. 

My professional journey off the field began with a community visioning campaign to help continue Chattanooga TN’s revitalization, then a short, but formative stint with an edtech startup, which got me interested in startups, and then a year at a fund of hedge funds, before founding my first company in 2012, RootsRated.

Founding RootsRated kicked off what has now been a 15-year journey into building startups. RootsRated began as a go-to site for outdoor recreation and adventure travel. We later pivoted to SaaS, launched Matcha, a content marketing platform, and eventually, were acquired by Springbot, an email marketing service. 

After Matcha, I joined Automox, a leading ITOps platform, where I wore multiple hats—Director of Growth, Chief of Staff, and VP of Ops. Among other things, I led pricing at Automox, which led to the founding of Schematic. 

I grew up in Chattanooga, spent the last ~7 years in Atlanta which is one of the great cities, and recently moved to Colorado with my wife, two kids, and two dogs. Attended the University of Richmond, captained the soccer team, and studied International Relations & French (though my French has since atrophied). 

Outside of work, I enjoy trail running and becoming a cycling addict. Occasionally share my thoughts on history and technology on Substack.

Monetizing SaaS:
- Youtube: https://www.youtube.com/@schematichq
- Spotify: https://open.spotify.com/show/5yjegk5duBz3LtvjwOo8ai
- Apple: https://podcasts.apple.com/us/podcast/monetizing-saas/id1757006729

Fynn Glover

Last night James Wood from Northlane and I hosted an AI monetization happy hour in SF.

We had founders, sellers, pricing leads, and product managers at Winedown on Folsom. 

Conversations that stand out:

- How public companies are navigating the migration from seat-based revenue to usage-based revenue without cannibalizing the core business... and how to frame the shift in a way that wall st rewards

- The difference between outcome-based pricing and output-based pricing (James has great thinking on this)

- How seed stage companies are formally inserting willingness-to-pay conversations into design partner agreements

- How to navigate the different incentives (and egos) of executives to make pricing decisions that fit the company's stage and strategy

- The pricing models getting the most traction right now: pure consumption, base + variable usage, base + hard cap, spend controls

- How to handle pricing when customers start launching hundreds of ephemeral agents that consume your product

Thanks to folks for coming. We're hosting more of these in SF, Denver, NYC, and more, so DM me if you want to be at the next one.

Co-founder & CEO of Schematic | helping SaaS & AI startups monetize smarter and faster

My friend James Wood and I are hosting a group of founders, operators, CEOs, and product leaders on Wednesday March 18th in San Francisco for drinks, food, and conversations about what's working in SaaS and AI pricing, packaging, and monetization.

I first met James when he was advising on pricing at Automox. He's one of the first people who shaped how I think about monetization as a discipline, so I
I'm excited to co-host with him.

Expect a candid group sharing what they're learning, struggling with, and finding success with across hybrid pricing models, credits, custom enterprise deals, upgrade levers, and more.

DM me if you want the details. Wednesday in SF, space is limited.

Hi, I'm Benjamin Papillon. Ask me about entitlements! :-)

I think this is an important read for any CTO or CPO responsible for handling the evolution of pricing & packaging as their company matures into hybrid billing, multiple sales motions, and multi-product offerings. It's written by Benjamin Papillon, Schematic's CTO, and ryan echternacht, who led billing engineering at Crossbeam, before joining Schematic to help us build enterprise grade entitlements infrastructure a new world of monetization.

link in comments to full article

Companies owned by PEs like Vista Equity Partners & Insight Partners have a critical opportunity in front of them as we move into the AI era.

Most of them are sitting on 5, 10, sometimes 20 products acquired through M&A. Each with its own product catalog. Its own billing setup. Its own way of managing what customers can access.

That's not just a technical debt problem. It's a monetization problem.

I was on a call this morning with a finance and engineering team from a PE-backed company that processes billions of dollars in payments annually. 

They're consolidating 5 brands into a unified product suite & moving from simple seat licensing into hybrid usage-based models.

Here's how they framed their situation:

"To date, developers in each business unit have hard-coded entitlements and access permissions themselves. No unified standards, no best practices — just everyone doing it their own way. The question we're asking ourselves, is whether we want this to continue to maintain in house, or is it time to look at a commercial-grade entitlements vendor that helps us better manage multiple products, hybrid pricing models, and both product-led and sales-led buying experiences?"

That question is the right one. And more PEs should be asking their CEOs, "how will you design the monetization stack to support consumption based pricing, upgrades, and price transparency, so our customers feel value is aligned with their investment?"

Here's what we recommend in this situation:

1/ Treat pricing and monetization as a cross-functional architecture.

2 / The foundation is a robust, first-class entitlements system enforced at runtime & decoupled from billing & code. A dedicated system that knows what every customer can do, at what tier, based on what they've purchased and consumed.

When that infrastructure exists, here's how life changes across the organization:

- Engineering stops getting pulled into every pricing change. New package, new limit, custom enterprise term...none of it requires a code deploy. They get back to building product. As a byproduct, CEOs and CTOs don't need to accept 10, 20, 30 person billing engineering teams. 

- Product can iterate on packaging and monetization without redeploys and quarters of waiting. They can test, adjust, and move at the speed the market requires. 

Finance gets auditability. Every customer, every entitlement, every usage event — queryable and reportable. No more hunting through code to answer a QofE question.

- Sales can offer custom terms and exceptions without creating operational chaos. The system can handle it.

The companies that use this moment (consolidation, AI, competitive pressure) to rearchitect their monetization will emerge with a durable advantage. 

The ones that don't will keep fighting their own engineering team every time they want to change a price.

This is a solvable problem. But it requires treating entitlements as mission-critical infrastructure.

one of my favorite things about Schematic is that it allows you to combine product usage data and billing data in the same place and see usage over time against the limits defined in the subscription or the contract. this combination was painfully missing for me in prior roles and companies, which made it so difficult to have a complete picture of customer behavior, churn risk, and expansion potential.

Most SaaS companies launching AI features & products run into the same challenges. 

They move to usage-based pricing to protect margin and better align price with value. 

They want to iterate on packaging continuously. 

They want to manage customer lifecycle to drive expansion.

Then they realize their billing infrastructure is the bottleneck for all three.

They blame their billing system. 

But usually, it's actually not their billing system's fault. 

The root of the complexity and the real bottleneck is how they've implemented entitlements in their product. 

In the seat-based pricing world, when pricing was static, companies would build their own entitlement systems, usually poorly, by hard coding entitlements and tying them to plan IDs in the billing system and then using webhooks from the billing system to update state. 

This meant that engineering teams were accepting permanent responsibility for catching webhooks, retry logic, database schema to store entitlement state, writing enforcement logic into every feature, and maintaining all of it every time pricing changed.

That also mean that engineering sat in the critical path for every monetization decision the business wanted to make.

That was okay, bc pricing didn't change much. Pricing was simpler. But obviously AI has flipped that on its head. And that's no longer true. 

We talked to a CTO this week who described it this way: thousands of legacy plans, a custom subscription sync service nobody wants to touch, and entitlement logic that lives in the application, forcing his team to reallocate resources to support pricing and billing initiatives, and 100% slowing the business down. 

Shar Dara who leads billing engineering at Vercel recently told me that maintaining entitlements in-house usually results in the "codebase becoming garbage." 

The complexity and brittleness and expense you feel in your billing infrastructure, is often not a billing platform problem. 

This is an architecture problem driven by AI.

And the architecture that solves it has two properties.

First, entitlements have to be decoupled from code and enforced in the product at runtime. This implicitly means you should avoid asking your application to know the billing state of a customer. Entitlements should be enforced serverside via a streaming architecture. 

Second, one change should propagate everywhere. Into the product for correct access. Into billing for correct invoicing. Into the customer portal for customer transparency. 

When this is in place, your commercial team can change pricing, run a promotion, provision an enterprise plan, or apply a credit override without filing a ticket.

That is the separation of concerns that lets engineering ship products faster and lets the business own and iterate on monetization.

If you're an engineering or product leader at a SaaS company launching AI products and navigating this problem, reach out and let's chat about what a better architecture looks like.

the rate of entitlements decisions is about to increase by orders of magnitude, and anything hard-coded or loosely defined won't survive it.

we're seeing enterprises look to re-architect monetization & we're seeing startups choosing a decoupled architecture from the very beginning.

There is a big difference between systems that describe limits and entitlements at the plan level versus systems that evaluate and enforce them in-product at runtime. 

The latter tends to deliver a much better developer experience and more business agility once companies pursue usage-based pricing, hybrid selling, or multi-product offerings.

Open article: Who Owns Pricing? by open.substack.com

Auth handles identity. Billing handles invoicing. So who handles what a customer is actually allowed to do with your product?

Most SaaS companies assume the answer is "the billing system." It's not.

Billing systems are responsible for invoicing. They're not responsible for entitlements inside your product... in real time, at the user level, across usage-based limits, add-ons, and custom enterprise terms.

So companies do what comes naturally: they hard-code it. 

It works until it doesn't — which is usually the moment you try to change your pricing, launch a new package, or add a consumption-based component.

At that point, every commercial decision becomes an engineering project.

There's a name for this: entitlements, or commercial permissioning. 

Not who you are (that's auth). Not what you owe (that's billing). But what you can do based on your contract, your subscription tier, your usage to date, and your seat count.

Entitlements have always existed. They're just getting harder.

Companies are moving toward hybrid models: seats plus usage. PLG and SLG running in parallel. Multi-product bundles sold to different personas. 

And rapidly... agents acting on behalf of customers, making entitlements decisions not once per session but thousands of times per workflow.

The companies that hard-coded this for a simple seat-based world aren't ready for what's coming.

Commercial grade entitlement management is critical infrastructure for the world we're moving into. 

They must decoupled from code, enforceable at runtime, and controllable to the business users who own pricing and packaging.

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Fynn Glover

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taplio

The Battle

Marcos Rivera

Fynn Glover

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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);}Marcos Rivera's LinkedIn Performance

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