Manny Medina

Executive Chairman of Outreach, the leading Sales AI platform

Outreach is the leading sales execution platform that helps market-facing teams efficiently create and predictably close more pipeline. From prospecting to deal management to forecasting, our platform leverages automation and artificial intelligence to help revenue leaders increase efficiency and effectiveness of all go-to-market activities and personnel across the revenue cycle. Outreach is the only company to offer sales engagement, revenue intelligence, and revenue operations functionalities in a unified platform. More than 5,500 companies, including Zoom, Siemens, Okta, DocuSign, and McKesson depend on Outreach to power their revenue organizations. Outreach is a privately held company based in Seattle, Washington, with offices worldwide. To learn more, please visit www.outreach.io.

this is the most alarming chart I have seen to date

for Saas, shifting to outcomes is an economic emergency.

I used to think it was a choice for the more enlightened ones

not anymore ...

Founder Signals | Co-Founder Silicon Slopes

SaaS isn’t slowing down. It’s getting eaten alive ... cannibalized.

Look at the Aventis Advisors growth chart. The trend isn’t subtle, it’s a cliff.

We went from 36 percent growth to 12 percent. Almost a decade of down and to the right.

With forecasts pointing to 11 percent … and falling, this feels like a pretty big structural shift. SaaS is starting to look like utilities and pipelines, durable and necessary, but no longer where the real upside lives.

And the reason is pretty simple. AI is cannibalizing the very work SaaS used to monetize. 

Here’s what the chart doesn’t show, but every operator feels.

1) SaaS used to sell “workflows.” AI sells “outcomes” (OaaS). Agents do the work inside the tool, so the tool stops being the product. The labor becomes the product. 

2) Budgets (and investors) are leaving SaaS and flowing to digital labor. CFOs aren’t buying more seats. They’re buying fewer humans. AI fits. SaaS doesn’t.

3) Feature parity killed differentiation. Entire categories are indistinguishable. CRM, CX, marketing automation … all the same. AI exposes how thin the moats always were.

4) Enterprises hit peak-SaaS years ago. Now they’re consolidating and cutting 20 to 40 percent of their stack. AI accelerates that purge.

5) AI startups are growing at speeds SaaS can’t touch. When companies hit nine figures in months, not years, investor expectations reset. SaaS looks slow, expensive, and operationally bloated.

6) Value is moving down the stack. The action is in compute, data, agents, and orchestration. SaaS is becoming a UI layer that AI sits on, not the engine driving the work.

The growth-rate collapse isn’t a mystery,  it’s more of a transfer of value. SaaS is maturing into a stable, cash-flow asset class. 

AI is becoming the new growth engine of the enterprise.

That means founders have a choice, build SaaS and optimize it like infrastructure, or build AI agents that replace the workflows SaaS was built to capture.

One path gives you stable multiples, the other gives you growth.

Sign up at Paid.ai. We help AI Agents get paid!

The Rule of 40 breaks with AI.

For those who don’t know, the rule of 40 states that your company is healthy if growth rate + profit margin ≥ 40.

Traditional SaaS has got used to 20% profits with costs breaking down at:
- 20% COGS
- 25% S&M
- 25% R&D
- 10% G&A

20% profit + 20% growth = healthy company. 
Easy. 

In the agent world, with all your LLM and tool calls, COGS often goes up to 60%.

BUT NONE OF YOUR OTHER COSTS GO DOWN. 

That’s why AI companies are often looking at -20% profits.  

Those companies must grow at at least 60% YOY durably to be healthy.

Some are seeing that level of growth, but it’s not sustainable with the current level of competition. 

The party has to end sometime.
Something will have to give. 

One area that will change is sales comp. 

I think we’ll see a lot more companies moving sales commissions from % of revenue to % of margins. 

It’s not a new concept. In many industries this is the norm.

Door to door sellers selling encyclopedias or cookware were doing it before. 
And if they gave a discount, it came out of their own pockets. 

Sellers were incentivized by the same metrics that mattered to the business - more deals, bigger deals, and bigger margins.

How are you compensating sellers in the AI era?

I’m hosting a roundtable on this topic soon. DM me to get on the guestlist.

🧲 Uncle! we’re finally hiring a Founding AE Paid
We’ve built double digit millions of qualified pipeline in a month. 
It's just Manoj Ganapathy and I closing
Now we need help! 

🚀 You’ll own the sales motion end-to-end
From strategy to signature. Manoj and I will personally close together with you to make sure you are successful
Our deals are $250K ACV and above. Sold to the full SaaS exec team (CEO, CFO, CRO, CPO, CTO).

You’ll be the person who makes Paid happen inside the world’s best software companies.

🧠 We’re looking for a builder who can sell
We’re not looking for a “closer.” We’re looking for a builder who can sell.

Here’s what that looks like:
Winner: You are competitive. Like to win. All the time. 
Curious: You love untangling complex problems and asking the next question.
Customer-obsessed: You can talk to a CFO about ROI and a CPO about workflow pain.
Technical: You will work closely with our FDE to build what the customer needs and close the deal. Our engineers are sellers 😳 
Strategic: You build internal champions, navigate orgs, and multi-thread
Some Experience: You’ve closed a few $250K–$500K+ enterprise deals in the last 6 months. so you know what's like
Founder energy: You move fast, thrive in ambiguity, and love building. 
High-Agency: You make decisions independently. 

💼 The work
Partner directly with our cofounders (Manoj Ganapathy Raj Dosanjh and I)  to grow the business
Co-Create repeatable sales playbooks as we scale.
Shape the GTM motion — pricing, messaging, and process.

💥 Why Paid
At Paid we sell success - not software, not services - just outcomes!  
It high-stakes work. We don't differentiate between software and services. 
Our customers winning is ALL we care about 

We’re early, ambitious, and moving fast.
This is an opportunity to join at the foundation — massive upside, full agency and autonomy and the empowerment that comes w it..

👉 Let’s Talk
The job is in-person in SF/Bay area. First few weeks in London.

If this is you - DM me.

We’ve seen a lot of firsts since launching Paid earlier this year. First hires. First office. First customers.

Yesterday was another big first for us - first team day! 

Normally elite teams are locked in delivering alpha.
So asking for a pause to go for an outdoor activity was a big deal.

It was incredible watching the team come together and getting to know everybody outside of the office.

I already knew this team was amazing, but learning more about their backgrounds and what drives them personally was just - wow.

We are small team that punches way above our weight class.

We are hiring for a founding AEs - if you want to be part of this elite team - DM me.

How do you raise a seed or series A? 

This came up at Slush this week and I wanted to share my 2c.

There is a tactic for seed fundraising that makes it way faster. 

FIRST: Find all the different seed stage VCs that agree with your hypothesis. With your view of the world

There are more seed VCs than stars in the Milky Way. But there’s no magical database. You have to dig in. Trust me though, you’ll get bored before you run out.

A handful of these WILL be into your hypothesis. Probably more than 10.

So find them all.

Be diligent. Dedicate a day a week to finding these people, connecting with them and seeing if they agree with your hypothesis. Develop that relationship. Show them progress. 

This will take a couple months but it will be worth it. And it will save you time later. 

SECOND: Find out where they will take risks. 

There’s 2 types of risk VCs take:
- Those that take market risk - they find amazing technologies and assume that the market will be there. Like a16z. These are great fits to strong technical founders.
- Those that take technical risk - they identify markets that are huge and find founders/technologies that can deliver value for those markets. Like Sutter Hill.

Find the one that is right for you.

Those people will be willing to write you a small check to find out more.

It’s like a game of poker. Show your cards. If they’re interested, they add chips to the pot. 

Your job? 

All you have to do is convince them that you are the right founder for this time for that space. 

Land five believers and one will go all in. That’s how rounds start.

Thanks Slush for an amazing event. It was super energizing to spend time with so many founders of different types and backgrounds, all coming together to help each other and grow the industry.

Shout out to Alexander Schmitt for joining me on the founder’s stage.

🎯 Great conversation with Camilla Bier at tonight's event Granola 

Two questions really hit home and sparked some candid discussions:

Question 1: 
"How do you evolve from being a founding AE who takes ANY deal just to prove the product works, to actually caring about ACV and deal quality?" 📊

The truth? It's painful but necessary - so as an early AE your move is to get ahead of it. 
In the early days, every logo matters. Every dollar validates your existence. But there's a moment when you realize that ten $10K deals don't scale 
And most take the same effort as one $100K deal 😳 - except the latter actually lets you build a sustainable business. 💡

Question 2: "What happens when you build an SMB motion, hit $10M ARR fast, raise your Series C, and suddenly need to go enterprise?" 🚀

This one got real. Here's what I shared:

When you go from Series A → B → C at breakneck speed, you become what I call a "scale company in a startup's body."

It's like going from eating Cheerios as a 12-year-old to suddenly having a mortgage and three kids in the span of a year. 🥣➡️🏠

Your Series C investors are spreadsheet warriors. They're pattern-matching you against every other company that hit $10M, and they expect enterprise-grade revenue quality. 

But 

your entire DNA - your team, your processes, your product - was built for velocity, not enterprise complexity. 📈

The brutal reality? You can't just "level up" an SMB team to enterprise overnight. 
Different people, different playbook, different everything. 🎭

My advice: Start building your enterprise motion BEFORE you need it. Plant those seeds at Series A. Because trying to transform your go-to-market strategy while hitting aggressive Series C growth targets? That's a recipe for disaster. 🔥

The best companies don't wait for the board to tell them their revenue isn't "high quality" enough. 

They see around the corner and evolve before they're forced to.

Fix it before it's too late. Your future self will thank you

xoxo

There is no more technical moat.

I know that sounds shocking.

But I just spoke with four AI companies today.
All building customer service agents.
All using the exact same technology.

And they’re all thriving.

Why?

Because each one serves a tiny market incredibly well.

One sells to car dealerships.
One to e-learning companies.
One to car washes.
One to healthcare.

They tailor everything — sales, marketing, delivery — to that niche.
They show value in the customer’s own language.

The difference isn’t in the tech.
It’s in how you deliver it.
How deeply you understand the customer problem.
And how clearly you prove it’s solved.

That’s the moat now.
That’s the money.

Six months ago, I posted LLM, tool calls, and other AI Agent features that were upending SaaS economics. 

I said margins were dropping from ~80% to 60%.

I was wrong. 

It's much worse.

Bessemer Venture Partners' State of AI 2025 report just dropped a bombshell: The fastest-growing AI companies are operating at 25% margins.

25% !

The hottest AI startups are running NEGATIVE margins, burning cash to steal your customers.

They use every tool possible to win business.They’re going to undercut your pricing. They’re going to beat you in deals. They’re going to steal your customers.

The old SaaS playbook is dead, and adding credits to seats will not cut it.

Racing to the bottom on price? That's a game you can't win against companies willing to lose money on every deal.

The solution isn't to panic. It's to evolve. Don’t be stuck in race-to-the-bottom pricing with a dozen scrappy AI-natives?

Then you need to figure out to charge for value.

Your pricing model should:
- Make you invulnerable to competition
- Highlight value
- Be proprietary to your solution
- Be mutually beneficial for you and your customers

DM me to join a roundtable I'm hosting on this very issue.

We're rewriting the rules of value-based pricing in the AI era.

Saas seat compression now comes from two places

1- no or low usage. 

As Satya mentioned, Saas has gotten away charging a lot for a seat with low MAU - monthly active usage.
Well not any more. 
Upon renewal, procurement departments are lopping the bottom 10-20% of users with low MAU. 
That's contraction! 

2- layoffs

The great transformation has began. 
It started with decrease in hiring for entry level jobs (employment for those aged 22-25 declined by nearly 20% this year) 
And it's now spreading to the broader population of white collar jobs

Saas may not be dead, but being on a seat-based monetization sure looks like a road to a grave

time to move to AI agentic pricing - either task based, human replacement based, or outcome based 

pick one
pick quick

our team was consuming $500 of beef jerky per month! 😳

so we decided to buy in bulk and throw in some creatine and share the savings w our customers!

sign up for Paid - get fit!

From building AI agents → to building agent gains.

Creatine? Check.

Jerky? Check.

Lifting belt? Obviously.

Agentic intelligence meets anabolic energy.

Who's in?

check out my conversation with Raj Dosanjh on Forward Deployed Engineers and why every engineer at Paid does at least one FDE customer tour. 🎯

The FDE role is having a moment - every AI startup is hiring them 
While the LinkedIn old guard dismisses them as "consultants with a fancy title."


FDE isn't a job title. It's a philosophy.

The philosophy is simple: The customer's problem matters more than your product roadmap. 

Full stop.

If we're truly solving the organization's most critical problem, then our most talented (and yes, expensive) engineers should be on it. 

Even if that means building something custom. 
Even if it doesn't scale immediately.
The abstraction layer?  The productization?
That's our problem to solve, not the customer's.

This philosophy does three things:

🥷  It creates radical customer empathy. 
When your best engineers sit with customers, they stop building features nobody asked for.

🥷 It signals priorities. Both internally and externally
it says customer problems > roadmap. Always.

🥷 It builds founders. 
FDEs learn to balance technical excellence with business reality. They become mini-CEOs.   It's why Palantir has produced the most amount of founders.

The critics who call FDEs "professional services with extra steps" don't get it. Professional services implements your product. FDEs reshape your product around reality.

At Paid, this isn't a hiring strategy. It's how we think about building.

Every engineer. At least one FDE tour. No exceptions.

Because the best products aren't built in conference rooms. 

They're built in the trenches with customers.

A chasm is forming in SaaS sales teams.
on one side: reps who know how to sell seats.
on the other: reps who can monetize agents.

most are stuck in between - they know the old playbook: logins, features, $x per user per month.

now your best rep sits across from a prospect who asks, “How much does the agent cost?” and they have no answer.
- "it’s $50 per seat" - but agents don’t need seats
- "it’s usage-based" - but what’s the unit?
- "it’s outcome-based" - but how do you quote that in Salesforce?

so the default bundling creates zero incremental revenue captured

Reps can’t configure quotes because pricing isn’t in their systems.
they can’t articulate value because there’s no data on what agents deliver.
they’re not trained on outcome-based selling.
 They over-discount because they’re unsure.

across the chasm, the question is more "What outcomes matter most?" and not "how many seats".

Your reps can’t compete with a seat-based playbook.
Crossing the chasm means giving sales team new infrastructure, not just a new pitch deck

Throw back to this gem from Pat Grady earlier this year:

A lot of the companies that are ripping right now have negative gross margins.
That's okay.

If you have negative gross margins because you're chronically underpricing your product, that’s not good.

But you have negative gross margins because you are sub scale and you can see a path toward getting to 60-80% gross margins over time, that's okay.

People are getting a little more reasonable on data privacy. Instead of needing local instances in every European country, for example, you can have a single instance that spans European country.

For enterprise customers, instead of needing dedicated instances per customer because they're worried about their data leaking into somebody else's results, people are now accepting multi-tenancy.

There are lots of different things allowing capacity utilization to go up and COGS per unit to go down.

So, if your gross margins stink today, you might actually be okay as long as you can chart the path to having healthy gross margins over time, which obviously Paid can help you with 😉

Full episode on Youtube or wherever you get your podcasts. Search 'Agent Talk #7: Pat Grady (Sequoia) - What actually works in AI startups'

The agent economy just found a $2.7B hole in state revenues.

We partnered with Commenda on the first agent tax study (PLRs across states).

Two companies doing the same work:
1/ Classified as SaaS → taxable in 22 states
 2/ Classified as managed outcomes → taxed in 4
Both are legal. Structure is destiny.

If 10% of 2.5M admin roles shift to agents, states lose $2.7B/yr (income, payroll, local), and likely to rise.

for companies, 4 questions determine liability.

window: 3–4 years before rules catch up.

full report (state breakdown + decision tree) → https://lnkd.in/gEjrJdpa

paid.ai

The $2.7 Billion Agent Tax Crisis: First-ever study reveals how AI companies are legally avoiding tax | Paid.ai blog

Commenda

Aashish Peepra

Every single one of our engineers at Paid has been forward deployed - they talk directly to customers, they see the problems firsthand, and they build the solutions.

no CS passing feedback through slack or tickets that lose context by the time they reach them

Engineers can talk to people, they can figure things out. 

We get into our customer's code base. We implement it for them. We help their sellers sell agents

nothing between us and results.

The SaaS playbook just broke.

- SaaS companies added just 30% net new ARR in 2024-25 (Jamin Ball)
- Growth crashed from 36% to 12% (Aventis Advisors)

Billions of dollars are stuck in SaaS no man’s land.

The only way out is to get back to growth.

The good news is that you're already sitting on the solution.

You have a treasure trove of workflow data and operating procedures. 

The companies winning right now are already turning that knowledge - procedures, data, and policies - into AI agents. 

But most are still figuring out how to sell them. And most are getting it wrong.

Here’s 3 ways I’m seeing SaaS companies package their AI products, ranked from worst to best:

🚩OPTION 1: The "mega seat"
Bundle AI into existing seats at a premium.

It sounds safe, but it’s not.

Procurement is already cutting 10-20% of low-usage seats. Layoffs mean fewer buyers. You're fighting seat compression with... more seats? Bigger seats? 

Procurement will tell you to give them the more premium seat for the same price as the last seat if you want to maintain the contract value. 

Congratulations you got yourself a flat renewal! Yay! 

👍🏽 OPTION 2: Seat + credits
Attach AI credits to seats.

Simple to understand. Allows you to start demonstrating value without rocking the boat.

But not so simple to adopt.
How do you retrain customers to use new AI features? 
You have to put work here - otherwise a pure agentic company will convince your champion that you were built 15 years ago and no longer relevant.

This is a great way to get started down the path to … 

🚀OPTION 3: Launch a new product
Package your AI into a brand new product.

Look at Intercom and Fin. Matillion and Maia. Salesforce and Agentforce.

This approach wins because:
- You own the new category before competitors wake up - this category is for you to lose
- Customers pay for results, not seats
- Sales cycles collapse - no one argues with ROI
- You escape the compression death spiral 

The companies already making this shift are pulling ahead. 

The rest are still debating seat pricing while their ARR bleeds out.

I'm hosting a closed-door roundtable with SaaS leaders navigating this exact transition. DM me for an invite.

Love when a legend like Nick Mehta drops tactical gold

Board Member: Gainsight, F5 (NASDAQ: FFIV), Pubmatic (NASDAQ: PUBM)

How do you run client meals that people actually look forward to?

I've led hundreds of customer lunches and dinners over the years. As Erica Mansfield Robin Merritt Emily Wilkes Kat Leong Lauren Olerich know well, I have a very particular (or as some might say, "high maintenance") approach to making sure guests have a special experience.

As a note to myself, this is a partial list of my event eccentricities:

1. Topical Theme: Something attendees are already thinking about.
2. Goldilocks Zone: For one discussion, 20 is too big. But 8 RSVPs mean 5 might show. I've found 14 signed up is perfect.
3. Reply to RSVP: For intimate settings, having to click on a site and fill out a form reduces attendance.
4. Reminder: A second email with who's coming so far has a big effect on reg (social proof).
5. Day-Before Email: Get folks in the right state of mind with an agenda and prep info.
6. Real Private Room: There are so many fake private rooms out there. I've seen ones where a curtain divides the room from the restaurant. Make sure it's truly isolated.
7. Cozy Size: Nothing kills a vibe more than a 40 person room with 10 in it.
8. Turn It Down: Tell the server to cut the music in the room when dinner begins.
9. Mingle: Allocate 30 min before dinner for folks to meet each other.
10. Assigned Seats: Not always required but good way to make sure people meet each other.
11. One Convo: Jeffersonian dinners are special.
12. Active Moderation: Make sure everyone gets a chance to speak.
13. End On Time: Nothing worse than customers feeling like they can't leave.
14. Checkout: Final question - e.g., "one word to describe what you learned today but you can't repeat someone else's word?"
15. Thank You Email: Right after with a summary and contact info.
16. Team: None of it is possible without an epic team like the folks I listed above.

What have you learned about running small customer meals?

So excited to be doing this with Camilla Bier and the Granola team ! 

Sign up - last one sold out quickly 

And once that happens I can’t help you :)

GTM @ Granola

On November 11th, we’re bringing together the GTM and AI communities at Granola for a special event - featuring Manny Medina, Founder of Outreach and Paid.

It’s going to be a great conversation on how AI is reshaping how we monetise and sell.

Join us! Link to sign up is in the comments👇

Welcome Syndi to the world 

Congratulations to Maria Colacurcio and Nimrod Vered  for bringing AI agents to the world of pay equity and fair pay 

Huge disruption in the market !

CEO at Syndio | AI for the Enterprise

In 2017, I was at Starbucks helping plan our first pay parity announcement. That's when I learned about "pay equity analyses." Backward looking. Expensive. Slow. A process companies outsourced once a year to check if they had a problem. I remember thinking: there has to be a better way. What if, instead of fixing pay decisions after the fact, we could guide them in real time?
Rob Porcarelli and I jokingly called it the "Pay Fairy." Little did I know 7 years later, the Pay Fairy would have a name: Syndi. 

This morning, we launched Syndi v1.0, our first AI-native product and the foundation for a new category: Decision Intelligence for Pay. 

At Syndio, we've analyzed more pay data than anyone, over 10 million employees. And here's what nearly a decade of that work taught us: the problem isn't the pay analysis. It's the pay decision itself. Every day, 25 million pay decisions are made across the U.S. and Europe. Each one shapes lives, culture, and performance. Most are made with little context. Pay is often a company's largest expense, yet the least informed.

Across hundreds of conversations with customers, we heard the same painful tradeoff: Pay competitively to win top talent and risk internal inequity. Or play it safe and lose the talent you need. The reality? Most companies are doing both. Chasing market rates in silos, losing candidates to faster competitors, then discovering compression issues and costly remediation later.

Syndi solves what leaders have struggled with for years: how to win talent, maintain fairness, and control costs all at once. It learns your rules, understands your market, adapts to your people and goals. Hidden inside bad pay decisions are inefficiencies that quietly drain billions: misaligned incentives, attrition risk, wasted dollars. Pay tells the truth about a company, what it rewards, what it believes, and what it stands for.

Thank you to all of our customers and advisors who've spent countless hours with us, providing feedback, sitting through prototype sessions, and helping us get this right. We can't wait to continue the journey with you! 

Full blog post in comments ...

the movement to charging for real outcomes generated for customers will start slow 

and then it will happen all at once

Founder & CEO at Artisan 🦄 | Building AI Employees | Hire Ava, the AI BDR Artisan

Your north-star metric should be related to customer outcomes, not revenue

For us, it’s the cost per lead for our customers (the total amount they pay us to get a lead from Ava’s outreach)

Top line ARR is a vanity metric which can be gamed. Focus on generating real value for your customers, and ARR will follow

taplio

Manny Medina's Linkedin Analytics

Manny Medina

Performance ScoreManny Medina's LinkedIn Performance

What is Manny talking about?

Manny Medina's Best Posts (last 30 days)

Ready to grow your LinkedIn presence?

taplio

.css-6ytdur{background-image:linear-gradient(284deg, rgba(39, 43, 72, 1) 0%, rgba(33, 47, 183, 1) 100%);color:transparent;-webkit-background-clip:text;background-clip:text;}Manny Medina's Linkedin Analytics

Manny Medina

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);}Manny Medina's LinkedIn Performance

What is Manny talking about?

Manny Medina's Best Posts .css-1emoo84{font-size:var(--chakra-fontSizes-md);font-weight:400;color:var(--chakra-colors-gray-600);}(last 30 days)

Ready to grow your LinkedIn presence?

Manny Medina's Linkedin Analytics

Performance ScoreManny Medina's LinkedIn Performance

Manny Medina's Best Posts (last 30 days)