Kevin Mulrane

Experienced Revenue Leader with a demonstrated history of building and scaling revenue teams across sales development, new business acquisition, retention & expansion, sales operations, and sales enablement. Skilled in Negotiation, Revenue Growth, Customer Relationship Management (CRM), Team Building, Sales Operations, Customer Experience, and Deal Closure. I have worked across different departments such as sales enablement, sales operations, internal recruitment, Customer Experience, and marketing.

VP of Sales

When buyers push back on price, they're rarely only talking about price.  Its usually one of these signals. 


- Business case isn't clear
- Not a huge priority 
- Internal risk of making a change is too high. 

Lowering the price might reduce financial risk but it doesn't reduce strategic uncertainty. Don't just throw out a discount ask questions.  

Try this instead..

1️⃣ Clarify the cost of staying the same
 Instead of defending price, ask:
 – “What happens if you don’t solve this in the next 6–12 months?”
 – “Who feels the impact if nothing changes?”
 – “How are you measuring the cost of the current state?”
If the status quo feels cheap, your solution will feel expensive.

2️⃣ Test real urgency
 – “Is this a Q1 priority or a ‘nice to improve’ initiative?”
 – “What else is competing for budget or priority right now?”
 – “If this doesn’t get approved, what shifts internally?”
You’re not pressuring. You’re diagnosing.

3️⃣ De-risk the internal decision
 Price objections often mask internal fear. Try:
 – “Who would need to feel confident for this to move forward?”
 – “What would make this feel like a safe decision?”
 – “Where do you anticipate internal pushback?”

What else am I missing??

VP of Revenue at BioCentury | Advisor | Pizza and Wine Enthusiast

Most sales teams don't have a coaching problem. They have a feedback-overload problem.

I've seen it happen over and over. A manager listens to a call, spots 10 things wrong, and unloads all 10 in the debrief. They walk away feeling productive. 

The rep walks away confused and deflated.

That's not coaching. That's noise.

The best managers I've been around do something that feels almost too simple. They pick ONE thing. They go deep on it. They don't move on until it sticks.

But here's the part that separates good coaches from great ones...

They ask more than they tell.

"How do you think that call went?" "Where did you lose them?" "What would you do differently?"

When a rep can diagnose their own performance, you've done something that matters. You've built self-awareness. And self-awareness compounds.

I've watched average reps become top performers. Not because they got more talented overnight. But because someone finally took the time to coach them with intention.

Your reps don't need more feedback dumped on them.

They need a coach who gives a damn.

Are your managers actually coaching? Or just filling the time between calls?

May Habib is CEO and co-founder of Writer, a generative AI platform for the enterprise. 

May has worked in NLP and ML for 10 years, and before Writer she founded and built Qordoba, a machine translation and localization software company. She is an expert in AI language generation, AI-related organizational change, and the evolving ways we use language online.

May graduated with high honors in Economics from Harvard University, is a Young Global Leader with the World Economic Forum, and is a Fellow of the Aspen Global Leadership Network.

May Habib

Enterprise AI is at a very different stage now.

Organizations are moving fast and what they need from their partners is rapidly evolving. Now it’s about who can actually help them move AI away from the sidelines and into the center of those revenue-driving, compliance-heavy workflows. And do it at scale.

That means the bar for this entire industry just went way up. A great platform is only half the equation. You need the tech AND the ability to actually DELIVER *flawlessly* across the entire customer journey, every single time. 

That’s the kind of operational excellence the enterprise demands today. And that is exactly why I am SO excited that Brian O'Reilly is stepping into the role of Chief Operating Officer at WRITER.

There is simply no better person to scale our operational engine than Brian. He built our EMEA team from scratch and has lived the reality of taking customers from that initial "wow" moment all the way to a mission-critical deployment. 

Brian has a freakish operational instinct. He can zoom out, see the whole end-to-end journey, and connect the dots in a way that very few people can. He’ll be working shoulder to shoulder with Mina Alaghband, Andy Shorkey, Diego Lomanto, and our entire leadership team to make sure every corner of the biz shows up as ONE WRITER!

We’re creating a truly MAGICAL experience at every touchpoint and we’re SUPER executed to have  Brian leading this charge! 💪

CEO of Writer.com | Enterprise generative AI | Hiring in ML, eng, design, mktg, sales + CS

One thing as a AI native startup you can only learn the hard way — if your product needs forward deployed engineers (FDEs) to work, then it's too hard for the customer to maintain and use for themselves. 

FDEs are all the rage now, but in 12 months, every company deploying them will have rebuilt its product to not need them — or will not exist. 

The reality is that the hardest bottleneck to overcome — line-of-business talent at the customer that can be trained to think agentic-first — can only be solved the hard, old-fashioned way: 

1 — UIs that are intuitive and don't need heavy training (we call it "kid with an iphone" easy; you don't need to show your kid how to use the ipad)

2 — Helping power users go viral in their organizations: the best way to learn how to be agent-native is to watch colleagues use WRITER to do killer sh!t! 

3 — Making sure c-suite is hands on and engaged and are power users themselves. When they are, they recognize agent-native talent in their orgs for the precious resource that it is, and they reward it — which creates more power users. 

Point 1 is really the hardest. 

Which is why I'm so incredibly proud of what the WRITER team has done over the past few months to radically reimagine all of our product workflows for simplicity. 

Customers who needed us hands on keyboard building flows for them can now literally speak to WRITER and those same end to end agentic workflows just appear and just...work!! 

The result is powerful end to end agents that don't require engineering to work — not from WRITER FDEs, not from the customer's own IT team.

The business builds, IT governs. The way it should be in agentic AI.

A lot of CEOs are daydreaming about "Jack Dorsey-ing" their company right now. 

Ever since Block cut almost half of their staff while the business was still growing, a lot of leaders have started viewing layoffs as the "solution" to the agentic era. They think a one-time cut will solve their legacy issues.

But whether you cut heads or not, the agentic era is here. And one way or another, you’re going to have to face it. 

Yes, that’s a MUCH harder path. It means leaders are going to have to rethink org charts, ownership, incentives, and workflows. 

If you default to cutting half your org, how do you know you cut the right half? How do you know who thrives in an agentic operating model if you haven’t given them the chance to work in one?

Three shifts I’m seeing the best leaders make TODAY:

1. They rebuild for radical simplicity. They take a machete to the complexity that has calcified across legacy systems and legacy org structures.

2. They redefine how their people grow. This disruption sets us up to create completely new ways for companies and humans to grow. Work won’t look the same. Why fear that?

3. They expand the boundaries of ambition. The leaders we work with are already operating on a different plane, completely unbound by yesterday’s constraints.

I see forward-thinking leaders every day (most of them WRITER customers) who get this. I’m in boardrooms and on Zooms with these folks and they're building the most badass, incredible things. These people are JAZZED. They’re asking what else they can finally build.

I shared more on the “AI Leadership Reckoning” in Fortune:

Open article: The AI leadership reckoning is here | Fortune by fortune.com

The AI leadership reckoning is here | Fortune

Every leader should be trying to get their employees’ token budgets way up. 

At WRITER, we celebrate when non-engineering employees hit the 1B token / month club.

It's pretty straightforward to get into billions of tokens a week/month when you're coding. But for business users — they need to conceive of their jobs pretty differently to get there. 

It's a huge testament to the creativity and productivity of the WRITER org that dozens of business users are consuming billions of tokens monthly.

For most of the G2000 though, getting hundreds of line-of-business employees (let alone thousands) to billions of tokens a month is nearly impossible today.

Why?

Let's say you're an enterprise of 10,000 people and you're in the enviable position of having 100 power users in the business capable of using 1B tokens / month productively.

The list price for 100B/month tokens today is $3-$5M/month with the lowest cost frontier models. A month.

Now check out the screenshots attached — these are the activities our top token consumers are using AI for.

None of the use cases most business users use agentic AI for are really "batchable" (which is what could reduce that $3m-$5m/month cost) and the fact is, the mental overhead of thinking about constraining cost while our users experiment would have been another barrier to adoption.

So what's our solution?

(1) Cheaper frontier models, better infrastructure — our LLM architecture fundamentally changes our economics and (2) we don't penalize people for jurisdictional job overlap.

Users just GO. They don't need to stop and ask "is this my job or someone else's?" They don't hit arbitrary token limits or get blocked because they're crossing organizational boundaries.

When you remove the friction of "who owns this workstream" and "did I just burn through my token budget on someone else's use case," you get what we're seeing — business users hitting billions of tokens doing actual productive work.

That's the unlock for the enterprise. 

Enterprise-grade frontier LLMs. 

And rules for AI that support those brilliant employees in the business who are ready to re-architect their own jobs and pave the way for others to do the same.

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taplio

The Battle

Kevin Mulrane

May Habib

Followers

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Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Kevin Mulrane's LinkedIn Performance

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