Gorish Aggarwal

Sybill

Sybill is the AI co-pilot for B2B sellers. We don’t just capture your sales conversations—we automate and execute your follow-ups, CRM updates, and next steps, so you can focus on closing deals, not admin work.

💥 What Sybill Does:
✅ Auto-executes next steps: CRM updates, follow-ups, meeting scheduling
✅ AI-powered research: Pulls prospect insights from the web
✅ Auto-customizes sales collateral
✅ Works where sellers work—email, CRM, and LinkedIn

🚀 750+ sales teams trust Sybill
🔥 70%+ revenue from word-of-mouth
🤖 AI that doesn’t just track, it executes.

Started as AI that read facial expressions on Zoom. Now? The most advanced AI assistant helping sellers close more while doing less.

🚀 Hiring, Partnering, & Scaling—Let’s Connect!

Founding AE and CEO

Humans of Sales

📍 Bringing the human side of sales to life

Sales is more than quotas and cold calls—it’s about people. Humans of Sales shares real stories of sales reps: their wins, struggles, lessons, and moments that make this profession special.

Not a sales blog. No tactics. Just authentic, inspiring stories that redefine the sales narrative.

📅 New stories every Tuesday
🔹 Real Stories. Real Sales. Real People.

Follow #HumansOfSales to join the movement. 🚀

Founder 

Stanford University

Lead instructor of EE 263 in Q4 '19 and '20. Grad course on optimization theory and linear algebra

Lecturer

Samsung Electronics

Senior ML Engineer

CEO @ Sybill | Generative AI for Sales

Once upon a time, I was building AI to cure blindness, predict blood glucose levels, and even make drones land on moving vehicles. Now? I'm making sure B2B sales reps never have to update their CRM again (which, let's be honest, is a far greater cause).

At Sybill, we don’t just take notes—we execute next steps automatically. Follow-ups, CRM updates, scheduling, research—done for you. Do less, close more. 

750+ sales teams trust Sybill to do the boring stuff, so they can close more deals—and we’ve raised $15M to make it even smarter.

Also started Humans of Sales—because sales is more than quotas and cold calls. It’s about real people.

Follow for AI, sales, and spicy takes. 🚀

Member

RevGenius is a community of revenue-generating sales and marketing professionals brought together to learn, share, support, and grow with each other. Our community is remote-friendly, collaborative, and loves to help. You can consider us your alt work family!


If you're not onboarding customers in-person, can you really say you're "customer obsessed?" I kid (mostly) 😂 

Auditoria.AI signed up for Sybill recently, and Nishit Asnani (Hiring Founding AEs) and I got to onboard their team in person.

Did we actually need to be there in person? Not really.

Part of why teams love Sybill is that it's easy to get up-and-running on your own, so there's no real hand holding required.

But the chance to get their feedback, hear their questions, and watch them run Ask Sybill queries in person was worth it's weight in gold.

It also doesn't hurt that they're here in SF.

Cheers to many more in-person onboarding sessions 


Thank you to Akash Bose and David Osborne

My use of ChatGPT and Claude dropped by 99% in one day. 

Sybill has been able to answer directly from our calls and deals for a while now, but last week we shipped document upload and web search.

Now Sybill can search for answers in your calls, emails, and CRM, but if it can't find an answer, it will take to searching the web or working directly from a document I've uploaded.

So I straight up don't need ChatGPT or Claude for almost anything anymore.

It's wild.

If your teams are tired of copy+pasting transcripts from Gong into ChatGPT, let's talk.

Nishit Asnani (Hiring Founding AEs) Soumyarka Mondal Mehak Aggarwal

Yesterday, 50+ people showed up to see how Sybill is different from Gong.

We didn’t compare features.
We didn’t run a bake-off.
We didn’t take cheap shots at Gong.

We showed how Sybill and Gong are built on two completely different foundations with two completely different POVs about how revenue actually moves forward.

And those choices we made create massive differences in outcomes for revenue teams.

Recording in comments 🚀

Gong’s prices keep going up. But is anyone getting more value?

Not according to the sales leaders I talk to every day.

Not too long ago, Gong felt like the future of sales.

Clear value prop. Big campaigns. Category pioneer. Everyone wanted it.

But here's what sellers tell me now:

→ Prices are going up… again.
→ AEs pay $$$ for licenses but use it like a notetaker
→ Their AI can’t think it’s way out of a box
→ Forecasting is the only feature that works
→ CRM still needs manual updating after calls
→ No more innovation; copying competitors
→ Too many dashboards, not enough action

The real question: Has Gong become the ghost of revenue AI’s past?

We'll answer this question at next week's webinar:

Sybill vs. Gong: “The Ghost of Revenue AI's Past.”

(Can you guess our answer? :P)

We’ll cover:
→ How sales AI has evolved since Gong's hay day
→ Why Gong’s multi-agent architecture hurts, not helps
→ How Sybill uses AI to keep deals moving forward
→ Why some rip/replace Gong and others layer Sybill
→ And why sellers at Warmly, Aligned, Deal, Drata, and Perplexity are choosing Sybill for sales AI and execution.

Thursday, 12/4 at 8am PST.

Register and get all the deets below.

The moment you win a customer is also the moment you’re most likely to lose them.

The customer handoff.

That’s when momentum is fragile.

Excitement turns to uncertainty.

And one clumsy handoff can undo months of trust built during the sale.

Case in point: Cloudingo, a Salesforce-native data quality SaaS with a lean, full-cycle sales team.

Their sellers run everything - from first touch through renewal - juggling outbound, partners, demos, and onboarding.

When every deal crosses multiple hands, it’s easy for key context to slip.
And buyers feel it instantly.

As their VP of strategic alliances puts it: “We wear a handful of hats. What we needed wasn’t a heavyweight platform; we just needed to make sure the handoff from sales to onboarding didn’t feel like starting over.”

When we looked at their handoff flow, a few friction points stood out:
➡️ Long sales cycles with multiple discovery and demo calls
➡️ Onboarding starting with “remind me what you bought again?”
➡️ Notes scattered across calls, emails, and Slack

The result: slow onboarding, frustrated buyers, and lost momentum right after the close.

Here’s how we helped them fix it with Sybill.

1. Deal insights captured automatically
Sybill summarizes every call and email. Then then it writes details like pain points, goals, integration requirements, and migration risks straight into Salesforce fields automatically.
No manual entry. No missing context for customer success.

2. Standardized handoff templates
Before onboarding begins, reps use a saved templates in Sybill to generate a concise (and standardized) summary: what was sold, who the stakeholders are, and what matters most to them.
Everyone gets the same summary format. No surprises.

3. On-demand context for the next owner
Onboarding and CS can ask Sybill:
➡️ “What did we commit to during sales?”
➡️ “Who’s the main champion?”
➡️ “What are the success criteria for this account?”

And instantly get a clear, context-aware summary spanning every interaction.

The results?
➡️ Faster onboarding kickoffs
➡️ Fewer dropped balls between teams
➡️ Stronger customer momentum after the close

Because the sale isn’t really “won” when it closes.

It’s won when the customer’s confidence carries through to value.

Want to tighten your transition between sales and CS?

We built a free customer handoff AI prompt template, similar to the recent customer, a Salesforce native. uses to keep every customer handoff consistent and fast.

Link in comments below.

Another year of using Gong has come and gone, and here’s your Gong Wrapped.

➡️ 219 transcripts you copied into ChatGPT
➡️ 646 recordings you dug through to get answers
➡️ 37 trackers you made, still missing competitors
➡️ 429 times double-checking the AI summaries
➡️ 20+% pricing increases

And all the headaches that came with your “revenue intelligence”.
 
If this Wrapped feels familiar, come to our webinar tomorrow.

👉 Sybill vs. Gong: The Ghost of Revenue AI's Past 

We’ll put Gong and Sybill head to head, covering:

• Why Gong's legacy architecture can't match Sybill's AI-native architecture.
• Intelligence: How Sybill reasons across every deal, call, email, and CRM field
• Mid-Deal Execution: Why centering the AE is the way to improve sales performance long term
• Pricing: Why many sales teams say Gong feels like an overpriced notetaker
• Switching Paths: How teams either rip-and-replace or layer Sybill on top of Gong with zero workflow change

🗓️ Thursday, Dec 4 (tomorrow)

⏱️ 8am PST

🔗 Link to register in comments

Gong Wrapped Carousel

Sales teams don’t need 100 AI agents. Sorry.

They need just ONE truly agentic AI assistant.

There’s a growing trend in AI right now: everyone’s building “multi-agent architectures.”

Sounds impressive.

Like you get a whole team of AIs, each with their own specialty.

But here’s what most people don’t realize:

Agents ≠ Assistants.

An AI agent is a narrow tool triggered by rules you manage.

An AI assistant is one unified system that can perceive → reason → plan → act 
- with shared memory and context across everything it does.

In practice?

Most “multi-agent architectures” are just a bunch of glorified workflows passing half-understood context back and forth (like Zapier automations rebranded).

Agent A pulls notes from a call.
Agent B writes a follow-up.
Agent C drafts a Slack update.
Agent D updates the CRM.

Except none of them share a global memory, so each one is working off a slightly different version of reality.

Early on at Sybill, we had the same choice: build a multi-agent platform or a single-agent assistant.

We tried multi-agent. It broke constantly.

What we discovered was this:
Multiple agents retrieve slightly different contexts. 
They reason independently. 
They have no unified brain.

Every additional agent multiplies communication protocols, context handoffs, and error-handling headaches.

The truth: most teams building this stuff are running distributed chaos, not distributed intelligence.

So we do it differently now.

Sybill is one agentic system - not a swarm.

One reasoning brain with depth, not a collection of shallow task bots.

One shared memory across deals, not 100 disconnected mini-brains.

One autonomous assistant that takes initiative, not a stack of tools waiting for triggers.

When it learns something new about a deal, it applies that understanding everywhere, from follow-ups to CRM updates to coaching recommendations.

When we improve retrieval or reasoning, the entire system gets smarter overnight.

The tradeoff?

We give up the illusion of “more agents = more power” for something far more valuable:

Coherence. Reliability. Compounding intelligence.

Don’t buy the hype (or the headache).

Most “AI agents” out there are marketing sizzle, not real agentic AI.

Real agency isn’t about how many bots you have.

It’s about how well one system can understand, reason, and act.

I used Gong at my previous company, and I knew I didn't want to bring it here.

We hear a version of this all the time. 

Because teams aren't looking for another system to watch deals.

They want a system that actually works the deal with them.

That's the shift happening in revenue AI right now:

➡️ From dashboards ➡️ to decisions
➡️ From analysis ➡️ to action
➡️ From monitoring reps ➡️ to empowering them
➡️ From fragmented "agents" ➡️ to a single unified brain

Gong was designed for the last era.

Sybill was built for the next one.

And on Dec 4, we're breaking it all down.

Where Gong is going. Where Sybill already is.

Sybill vs. Gong: The Ghost of Revenue AI's Past
🗓️ Thursday, Dec 4 (in two days)
⏰ 8am PST

🔗 Link to register in comments

What we'll cover:
• Architecture: Why Gong's multi-agent stack can't match Sybill's unified AI brain
• Intelligence: How Sybill reasons across every deal, call, email, and CRM field
• Mid-Deal Execution: Why centering the AE is the only way to improve sales performance long term
• Pricing Reality: Why many sales teams say Gong feels like an overpriced notetaker
• Switching Paths: How teams either rip-and-replace or layer Sybill on top of Gong with zero workflow change

See you there!

Ghost of Gong

Nothing beats watching customers go to bat for you.

Thanks, Jeremy! ❤️

graphical user interface, text, application

Most sellers I've met are verbal processors.

They think out loud, talk through objections, and refine their pitch by saying it, not writing it.

But when it comes to prepping for calls or researching accounts? They're stuck typing into a search bar.

That's why we just launched Dictation in Ask Sybill.

Now you can ask questions about your pipeline the way you naturally think - out loud.

Just ask.

P.s. We'll be covering a ton of other new features in tomorrow's What's New webinar.

Link: https://lnkd.in/gq2W-b6W

I'm a CEO, but I am also a seller.

And I love and hate it.

I love the feeling of nailing a pitch, watching a prospects eyes light up when they see what Sybill can do.

But I hate, hate, hate the massive pile of mindless tasks that comes with being a seller.

The email follow-ups, the document collection, the calendar invites. They feel small when you're only doing one or two, but work 10, 20 deals and the "little" tasks add up.

It's like suffocating by 1000 small tasks.

And for my brain, it's a massive drain.

So when I say that the AI task execution our team built straight up changed my life, I'm not kidding.

I'd love to show it to you.

This Thursday Collin Mayjack and I are running What's New in Sybill, an hour live demo of all the newest stuff we've built.

No fluff. Just straight up before and afters of what our team has been building.

12/10 at 8:30am PST. Link in comments.

Amanda Zhu

Co-Founder

Recall.ai

✔︎ Who gets results using Recall
∙ Product teams at fast-growing startups who want to go to market in days instead of months. 
∙ Engineering teams that don't want to burn engineering hours maintaining their meeting bot integrations.

✔︎ Here’s what we do
We provide one API for meeting bots on every video conferencing platform. We abstract over differences between meeting platforms (even for platforms that don’t have an APIs). We run, monitor, and scale the complex real-time video infrastructure.

Interested in learning more? Go to: https://recall.ai 🌐

Perfect Recall (W20)

Grew to thousands of users, signing on annual deals with customers like Faire and Quora

Edisoft Inc

Software Engineer

❗Your engineers are wasting 6+ months building meeting integrations.❗

Why? Because every platform (Zoom, Google Meet, MS Teams) has different APIs, constant updates, and hidden edge cases.

❌ Building in-house = wasted engineering time.
❌ Maintaining it = ongoing distractions from core product development.
❌ Scaling it = reliability nightmares that break at the worst time.

That’s why we built Recall.ai.

✅ One API to handle every meeting integration for you.
✅ Ship in days, not months.
✅ Powering 1200+ companies, from early-stage startups to billion-dollar SaaS teams.

🚀 See how Recall.ai can save your engineers months of work

Amanda Zhu (Hiring SEO Manager)

YC W20 Demo Day: Our batch mates raised $5M, $10M, $20M.
We raised $300K.

We went home with a handful of meetings and a lot of “maybe later.”
A few people told us to give up.
Some said the market was too small.
A few more said, “If Demo Day didn’t pop, it’s probably not going to work.”

For a long time, it felt like they were right.

We spent the next five years building.
No big announcements.
No attention.
Just customers, product, and the same question every year:

“Are we still alive because we’re onto something… or because we’re too stubborn to quit?”

This year, when we announced our Series B, we finally used the LaunchHN we never used at Demo Day.
It felt like closing a loop we opened five years ago.

Demo Day results don’t predict outcomes. The work after does.
We’re grateful for YC and want to support other YC companies however we can.

If you’re YC (any batch), drop a comment with what you’re building. Would love to connect and help where we can.

The API for meeting recording | Co-founder at Recall.ai

No alternative text description for this image

I’m COO and co-founder of a $250M company. At our company, COO doesn’t mean “operations.”

It means owning whatever the company needs most that the CEO shouldn’t.
At Recall.ai, that’s GTM.

The COO role took us through 4x growth YoY and into consistent enterprise inbound.

My co-founder and CEO, David, owns product, technical direction, and long-term vision.
I own making the machine that attracts and closes customers.

That includes:
- how we market
- how we price and package
- how sales, marketing, and self-serve actually work together

The COO role isn’t a template.
It’s a response to a constraint.

Some companies need someone to scale customer operations.
Others need someone to build a sales machine.
Others need someone to turn early traction into repeatable growth.

We needed someone to own GTM end to end.

And once that constraint moves, the job changes again.

Closed my 5th seven-figure deal last month. Finally saw the playbook everyone says doesn’t exist.

Yes, there’s no script, formula, or guaranteed sequencing for enterprise deals.
But there is a scaffold.

Every seven-figure deal eventually hits the same checkpoints:
First meeting → demo → technical validation → PoC → PoC sign-off → procurement → security → legal → contract.

But the real work isn’t the checklist.
It’s what you do when you’re stuck between checkpoints.

Here are the things that have actually moved our seven-figure deals forward:

- Backchanneling to learn who’s worried, who’s confused, and who’s blocking silently
- Flying out when a senior stakeholder joins late and wants to “reassess”
- Hosting a small dinner to align teams who weren’t looped in until mid-PoC
- Getting warm intros from investors or any mutual connections
- Running security + procurement in parallel so they don’t choke the timeline later
- Showing up early to events stakeholders are speaking at
- Going backwards a checkpoint when something collapses, instead of forcing the next step

None of these moves look like “selling.”
None of them follow a proper sequence.

That’s why people say there’s no playbook.
But there is a framework and checkpoints you have to hit.

What’s the most creative thing you’ve done to get to the next checkpoint?

Today, running a $250M company, I have 60 minute 1-1s with every person in our GTM team. This is why this works.

As the company scaled, I was tempted to compress 1-1s, but I found 30 minutes to be too short for anything real to surface.

In 60 minutes, people bring up things they wouldn’t say in hallway conversation or a weekly standup:
- the complex problem they’ve been stuck on but can’t articulate yet
- the thing they “don’t want to bother you with”
- the early signs of misalignment that only show up in long-form conversation

And once you hear those things through, 90% of the time, the solution becomes obvious because your direct report finally had room to talk through it.

The hour matters because:
- trust takes time to reveal itself
- sometimes the problem is unclear until it is said out loud
- a single good conversation can make the next two weeks dramatically more productive

It’s also a very inexpensive and effective use of the hour.
One hour every two weeks prevents months of misalignment.

The only reason I know this is because I started to skip them.
And I felt the disconnect immediately.
Problems started to compound.

This has been the highest-ROI GTM habit I’ve kept.
Even at this stage.

I sent a $1.2M contract way too early. Their CTO shut the deal down on the spot, and that’s what saved it.

The VP of Engineering was excited and wanted to move fast.

No demo.
No deep-dive.

His team validated the technical fit in a day and told him, “We can run this in production.”

So after the disco call, we kicked off everything in parallel:
- Security
- Procurement
- Legal
- Commercials

Five separate threads. 
None of them talking to each other.

On Day 5, the VP asked for the contract.
I sent it.

Two hours later, the CTO rejected the contract and replied:
“Do not move forward.”

The email exposed the problem:

Finance hadn’t synced with Eng team.
The CTO had no context at all.

The urgency was still there, but the contract exposed the lack of alignment.

It forced every stakeholder to raise their hand.
It gave us the full buying committee in one shot.

Once everyone surfaced, the work was straightforward:
security review, pricing, fallback plan, legal terms, technical requirements.

The contract kicked off what I should have done from the start.
Coordinate.

The deal closed on Day 47.

In enterprise sales, a “no” isn’t a rejection.
It’s the moment the deal finally starts.

Here’s how I got my first 100 customers using Google Search and a Word doc.


2021. No fancy tools.

The hardest part wasn’t writing the email.
It was knowing who to send it to.

I started with one simple question:
“Who needs this now?”

Not “who might be interested.”
Not “who fits a persona.”
Literally: “Who records a lot of meetings?”

That gave me the first 10 names.
Those turned into a seed list.
Then I Googled their competitors.
Then their lookalikes.
Then anyone launching adjacent products.

My entire list came from:
- “{Company} alternatives”
- “Tools like {Company}”
- “Best {category} software”
- “Companies hiring {ICP role}”

Every name went into the Word doc.
Every name got outreach.

That’s how I got our first 100 customers.
And it’s even easier now.

There are tools that can make this faster today:
- Clay 
- Apollo.io 
- ZoomInfo 
- Lusha 
- BirdDog 

But it all still comes down to the same thing:

If you don’t know who needs your product, no tool will save you.
If you do know, even Google Search is enough.

The list is everything. The outreach is just execution.

Who am I missing? What tools or strategies do you use to build your seed list?

If you’re not a YC founder, give up.


If you didn’t IPO before kindergarten, give up.
If you didn’t vibe code a chatgpt wrapper in the womb, give up.

It’s satire, but the anxiety underneath it is real.

Truth is, there is always a valid reason to not start.

The odds will always be stacked against you: too old, too young, too late, too competitive, too uncertain.

And those justifications are all true - at least statistically.

But if everyone listened to the statistics,
There would be no exceptions.

Every breakthrough we celebrate today comes from someone who started despite the numbers, not because of them.

So it might’ve been better if you started earlier.
But you’re not too late to start now.

We 3x’d revenue, raised a Series B, shipped a new product, and launched self-serve. And somehow… it’s not even the end of the year.

This was a rewiring year.
Three things hit at once:

-----

1/ Product inflection: Desktop Recording SDK expanded the entire surface area.

We had to rewrite how we:
- pitch the product
- allocate engineering time
- talk about Recall.ai in one sentence

Multi-product changed how we describe the company.

-----

2/ GTM inflection: self-serve forced us to rebuild the funnel.

Pricing, onboarding, docs, support load - everything we assumed was “done” had to be rethought.

The questions changed too:
“Is the pitch working?” became “Which product is the pitch for?”

-----

3/ Sales inflection: larger customers changed the motion.

The deals went from:
- one stakeholder → buying committees
- simple technical validation → multi-threaded reviews
- one product fit → cross-product conversations

We had to learn a new type of selling.

-----

The story of this was recognizing that every new product, every new customer segment, and every new GTM motion changes the operating model.

It’s a good reminder that companies don’t grow in straight lines.

People think I’m a masochist.
I spend most of my time with people in this order:

1. my employees,
2. my customers,
3. my friends and family.

And I spend my time on things in this order:

1. work,
2. gym,
3. then friends and family.

A lot of people might find that sad or worrying.

But, to be honest, it doesn’t feel like sacrifice.
It feels like purpose.
Because this is exactly what I want to be doing.

Just like how a painter loves to spend all day painting,
or a surfer loves to spend all day surfing
I love my work and how every day brings a new challenge to solve.

You need to love the game you play.

Novak Djokovic, world-class tennis player, was once asked how he stays at the top.
He said, “I can carry on playing at this level because I like hitting the tennis ball.”

When you love the game, everything becomes easier.

Loving the game doesn’t guarantee success,
but it is a prerequisite.

The goal isn’t to escape the work.
It’s to find the work you never want to escape.


#StartupAdviceToMyYoungerSelf
#SATMYS

We are hiring cracked engineers in SF to build foundational infrastructure for the world’s largest dataset. We ran 18 million EC2 instances last month alone. Running highly-optimized real-time Rust processing 3TB/second of raw video.

If you are cracked please DM me with your GitHub! We have a rigorous candidate review process so anyone who gets an interview with us will get a free bundle of the seminal K&R’s C, TLPI, TCP/IP Illustrated Vol 1 (some staples from around the office).

Three seven-figure deals hit at the same time last quarter. That was the first week I couldn’t keep up.

When it was one big deal, I could brute force it.
Know every stakeholder. Read every email. Maintain perfect context.

But when three landed at once…
My AE had to bring me up to speed.

“Here’s where Deal A is blocked.”
“Here’s what Deal B needs from you.”
”Here’s the one meeting you must take for Deal C.”

I wasn’t running the deals anymore.
I was being deployed.
And I had to get comfortable with that.

Because in seven-figure territory, the AE has 10x more context than the founder:
- They’ve been on 20+ calls you haven’t.
- They’ve built the relationships.
- They see the entire chessboard.

I get parachuted in for one conversation that only I can unblock.
Not to quarterback the whole thing.

The shift was uncomfortable.
Before: I managed the deal, and the team executed my plan.
Now: The team manages the deal, and I execute their plan.

Your instinct is to grab the wheel.
To be “the closer.”
To jump into every thread.

But if you try to personally run three seven-figure deals at once, you will burn yourself and the deals to the ground.

I’m still figuring this out.
Where do you draw the line between stepping in and stepping back?

157 YC companies launched last week. We went through YC W20 and know how fast the spotlight moves. These 25 deserve a longer look.

item (YC F25) : the AI-native CRM that works for you

Fixpoint : Uber for AI trainers and human-in-the-loop supervisors

Bear (YC F25) : marketing stack for AI agents

Zarna (YC F25) : AI associates for private capital

Clicks (YC F25) : Computer use agents to automate all back-office work

Claybird (YC F25) : the full-stack AI ad company

Bluma (YC F25) : the new media distribution company

The Hog (YC F25) : AI demand gen for companies

Mantle : build internal agents to automate back office work with one prompt

Karumi (YC F25) : 24/7 AI demo agent for B2B SaaS

Denki (YC F25) : the full-stack AI financial audit firm

Absurd (YC F25) : AI brand and performance ads at scale

Caddy : the voice interface that works proactively for you

Crunched : Excel AI analyst for power users

HireGlide (YC F25) : AI screening and matching for hiring teams

Aside (YC F25) : live answer copilot for enterprise tech sales

Imagine AI (YC F25) : your AI clone for B2B content

Leadbay (YC F25) : discover and qualify leads that couldn’t be found before

Lexi (YC F25) : AI associates for corporate law

Logical (YC F25) : a proactive desktop copilot (Clippy but actually good)

Sciloop (YC F25) : AI co-scientist that automates ML experimentation and analysis

Cranston AI (YC F25) : full stack AI accounting firm

Questom (YC F25) : AI agents for B2B inbound sales

Sorce (YC F25) : Tinder for jobs

Uplane (YC F25) : replace marketing agencies with AI

p.s. to make it 26 ComplyDo (YC F25) : global compliance for enterprises

We get 6k signups every month, and 100% of our pipeline is inbound. But our inbound didn’t start with marketing.

For the first year, everything was founder-led outbound.

No paid acquisition.
No growth team.
No scalable channels.

Just me emailing every team building anything with meetings in it, trying to figure out who exactly needed this infrastructure the most.

Our first dozen customers came in one by one.
And every single one of them shipped fast.

One day a prospect booked a demo and said:
“We asked [Company Name] how they built their meeting recorder. They told us: Recall.ai.”

Then it happened again.
And again.
Different customers.
Same story.

We weren’t doing anything different.
Our customers were.

That’s when I realized inbound comes from density.

For us, it was enough teams in the wild using our product that other builders would bump into and ask how they did it.

Once that happened, inbound went from a trickle to a stream.

Outbound gave us our first customers.
Those customers gave us inbound.

Hired an AE who spent 6 years doing animal husbandry in a therapeutic research lab. Weird background for sales. Perfect background for enterprise.

It’s easy to filter for linear pedigrees: SDR → AE → Logos.
But seven-figure deals aren’t linear.

During the interview, I asked what that early chapter taught her.

She didn’t talk about grit, or passion, or some polished framework.

She said:
“You learn quickly that things don’t move on your timeline.
You show up every day, observe carefully, document what’s changing, and adjust.”

That sentence told me everything I needed to know.

Enterprise sales is filled with:
- periods of silence
- subtle shifts in internal politics
- a champion who loses influence
- a process no one warned you about
- an evaluator who stops replying and won’t say why

You win these deals with pattern-recognition, patience, and a calm emotional baseline.

Her background was evidence she had already lived the part of enterprise sales you can’t teach.

When you’re hiring for high-judgement roles, don’t over-index on linear experience.
Look for the work that shaped how they think.

Oh… and we’re hiring for Strategic Account Executives.

I’ll say the quiet part out loud. 
I landed our first seven-figure deal because someone was willing to stick their neck out for me.

Not because we had SOC2.
Not because we looked like an enterprise vendor.
But because one senior leader said, “I’ll take the hit if this goes wrong.”

What I didn’t understand at the time was that they already liked our product, and were evaluating the risk of working with us.

Could we support them?
Will we be alive in two years?
Would choosing us blow back on them?

And the wild part is that none of these questions get answered in one meeting.

Mid-market = 1 person making a decision.
Enterprise = 15-50 people trying to agree on anything.

Half the calls I had with them were their own teams catching each other up.

I wasn’t selling.
I was project managing a group that didn’t work for me.

Our first enterprise deal actually died twice.
Both times, our champion dragged it back to life.

That was the moment I finally understood who actually closes these deals.

Not the founder.
Not the AE.
The person inside who’s willing to risk their reputation on you.

Funny thing is… every founder I know has a completely different story about how their first enterprise deal actually closed.

My first 97 discovery calls all failed for the same reason.
I didn’t know what I was actually supposed to accomplish in the discovery call.

I knew the end goal was to close the deal.
But I didn’t understand the milestones I had to hit on the way there,
which made every call awkward.

Here’s the core insight:
Discovery → Demo → Trial → Close.
This is the simplest version of a sales process framework.

The goal of discovery is simple: if the prospect is qualified, the next step is to get them on a demo.

In discovery, you want to understand them deeply: use case, timeline, constraints, and decision criteria.
In the demo, they start to understand your solution more deeply.

Once I shifted my disco call goal from “sign the contract” to “book the demo inside the call,”
Everything clicked.

In sales, the goal of every meeting is to book the next one.

This is episode 1/9 of what good discovery calls actually look like.
Stay tuned for part 2: the one question that sets the tone

Adobe overpaid for Semrush.
$12/share in cash for what was trading at $6.89.

Everyone’s talking about the future of SEO vs GEO, but no one’s asking why Adobe paid a premium to buy Semrush now.

1/ Adobe bought Semrush above-market value at $1.9B.
This is no casual acquisition.
Adobe’s going all in on distribution (GEO) and wants control now.

2/ Adobe paid ALL CASH upfront
Everyone sees the shift from Google to Chatgpt,
but paying cash at this valuation signals something different: Adobe believes LLM visibility is the next distribution channel and doesn’t want anyone else to own the “GEO” layer.

3/ Adobe expects to monetize this fast
Cash deals are usually reserved for assets that will drive:
measurable, immediate revenue
direct product integration
a short payback period

Adobe paid a lot for Semrush.
Because in their view, the upside of owning GEO early dwarfs the cost of the acquisition.

My team should feel privileged to work in the office on weekends.


They don’t have to, 
They get to.

As a founder,
I choose the 2 a.m. rebuilds.
The endless emails and fundraising cycles.
The meetings back-to-back.
The weight of decisions no one else can make.

Not because it’s easy.
But because I get to.

“I have to” means pressure.
“I get to” means purpose.

I have to stay up coding another feature.
I get to turn an idea into something real.

I have to pitch again tomorrow.
I get to share a vision that might change how people work.

I have to lead a team through uncertainty.
I get to build with people who believe in the same dream.

That shift doesn’t make the work lighter.
It just reminds you why it’s worth carrying.

how to build $250M lemonade stand in 6 steps:


1. make yummy lemonade (code good product)
2. sell lemonade (sell product)
3. sell 100 lemonades and write down steps, then hire another human to sell lemonade for u (write ur playbook & hire sales)
4. make people know about the lemonade so there is a line out the door (market ur product)
5. line gets long, hire another human to sell ur lemonade (scale sales)
6. line gets short, tell more people about the lemonade (scale marketing)

btw I’m not actually talking about lemonade stands.
im talking about Recall.ai (get pranked).

did i miss any steps?

Our revenue per employee is $1M.
Because I figured out how to scale judgement.

When you’re 2 people, every decision has your fingerprints on it.
When you’re 200, you have to trust people to make calls you’ll never see.

Most founders try to scale process.
But the real unlock is scaling how people think. 

Here’s how we do that at Recall.ai:

1/ Hire for judgement, not IQ
Everyone says “hire smart people.
We look for something narrower:
People who’ve made high-impact calls with 
incomplete information and no safety net. 

You can train skills. 
You can’t train instincts from zero.

-----

2/ Codify your values.
Company values aren’t motivational posters.
They’re a decision-making framework.
When in doubt, they should answer:
Speed or quality?
Autonomy or alignment?
Perfect or shipped?

If values don’t resolve tension, they’re not values.

-----

3/ Run 11-minute daily standups.
Each morning, teams pick one real problem.
I get 60 seconds to say the call I’d make.
The next day, someone else leads.

After a few weeks, you start to see it:
People solving problems the way you would,
even when you’re not in the room.

The goal isn’t just faster decisions.
It’s shared intuition.

-----

You can’t just write judgment into a playbook.
You have to model it until it spreads.

Because your company doesn’t scale with headcount.
It scales with judgment.

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