Dharmesh Shah

Founder and CTO at HubSpot. Helping millions grow better.

Career startup guy.

Author of the book &quot;Inbound Marketing&quot; (http://InboundBook.com)

Specialties: Entrepreneurship, Software Development, internet marketing,SEO

Founder and CTO

Founder of HubSpot, a venture-backed software startup.  HubSpot offers the industry's first inbound marketing system for small businesses.  The software is available as a hosted service (SaaS).

Here's a quick tip on how to build an effective presence on LinkedIn.

Too many people on LinkedIn are "performing" for their current (and future) followers.

Instead of self-centered performing, focus on generous *sharing*.

We all have something to share that will be helpful/useful to others. Things we are experts in or passionate about. What's often even better is sharing mistakes we've made and lessons we've learned. 

Share, don't perform and you'll pull people in.

* I fall into this "performing vs. sharing" mode sometimes too.  

** "effective presence" is not just about the number of followers, likes or comments. It's about having genuine impact on somebody's thinking -- even if just for a moment.

Lots of people much smarter than me have been talking about this compelling new idea called the "Context Graph". I love the idea, but am a wee bit skeptical of far away we are from it being something businesses can use.

A concept is making the rounds in AI circles right now that has many people very excited: context graphs. Foundation Capital published a piece calling

Open article: Context Graphs: Capturing The "Why" In The Age of AI by Dharmesh Shah • 4 min read

Context Graphs: Capturing The "Why" In The Age of AI

We've long known that the best people have IQ + EQ.

When it comes to AI agents and their effectiveness, there's a new element — and it's multiplicative.

Agent Success = IQ  x EQ x  CQ

IQ = How well does it reason?
EQ = How well does it collaborate?
CQ (Context Quotient) = How well does it know YOU?

And because it's multiplicative, if an agent has a zero context quotient, it has zero value. (Apologies for revisiting grade school math).

Here's a quick thought exercise:

You can choose between two agents.

Agent A: 200 IQ. Bonafide Genius. Knows nothing about you.
Agent B: 150 IQ. Brilliant. Knows your business cold.

You pick Agent B. Every time. Why?

Agent A can solve PhD math problems.
Agent B can help solve YOUR business problems.

Raw intelligence without context is just confident guessing. (Also known as "management consulting"). 😀 

AI models know a lot about the world, but you need agents that know about YOUR world.

The real game isn't How smart is your model? It's How are you increasing the agent's CQ?

Imagine if it had...
...your top rep's call recordings.
...your angriest detractor's NPS comment.
...your happiest promoter's renewal notes.
...and everything else swirling around in your company

The agents that help you win aren't the ones with the highest IQ. They'll be the ones who know you best.

This is what we're furiously working on at HubSpot, because nowhere does context matter more than in GTM and nowhere is there more unified context than the HubSpot platform.  (Disclosure: As founder/CTO, I'm biased). 

We're excited about the progress the AI companies are making on delivering smarter LLMs  (higher IQ). We need that to build great agents. Meanwhile, we're working on delivering agents with higher CQ. (And stay tuned for the EQ part -- have thoughts on that too).

Anyhoo...

Key takeaway: In the age of AI agents...

IQ gets attention.
CQ gets results.

Woo hoo! Shipping an early release of a new AI app I've been working on. (Look at me, shipping something in the middle of the day instead of 2am!)

If you're curious about premium website domains and their underlying prices and trends, I think you might enjoy playing with this app:

domainsales .ai (yes, I like simple domains).

You can  ask questions like:

 "what were the top .ai domains sold this year."  

"what was the average price for .org domains every year".

"what's the sales history for chat .com "

All feedback appreciated. Feedback is a gift.

Thanks.

-Dharmesh

NOTE: I'm using this (and other) AI apps to test out new Agent.ai platform features that allow you to use any vibe coding tool to build apps and integrate them into the marketplace. That way, you benefit from 2.5M+ users, shared context and a bunch of tools you can use in your agents.  More on al this next week.

Was recently on a podcast with Manny Medina from Paid.

Was a great conversation around business strategy, pricing and of course, AI.

I'm not used to being on podcasts (not my natural habitat), but I think it turned out pretty well. Hope you like it.

Dharmesh Shah helped write the SaaS playbook.
Now he’s explaining why parts of it are about to get ripped out.

In today’s episode of Get Paid, the HubSpot co-founder doesn’t sugarcoat it:

AI agents aren’t a feature.
They’re a platform shift.
Seats still matter. For now.
Credits are inevitable.

And most “AI strategies” are just SaaS habits in disguise.
They go deep on why reasoning models changed the game, why vibe coding won’t save you, and why pretending this is a normal upgrade cycle is how incumbents quietly die.

If you’re building AI and telling yourself “we’ll figure pricing out later,” this episode is a warning shot.

🎙 New episode is live. Link in comments.

Nice to see folks combining the flexibility of Agent.ai and its access to a rich set of AI capabilities and data with the power of HubSpot Workflows for automation.

Senior Software Engineer | HubSpot-Focused Integrations & CRM Automation

I've been having a blast combining Agent.ai workflows with HubSpot automation lately, and the results have been impressive.

Here's what I've been able to automate:

Buyer Intent Detection -> Agent.ai monitors signals across multiple channels and automatically scores leads based on engagement patterns, content consumption, and behavioral triggers. When intent spikes, HubSpot workflows kick in with personalized outreach.

Company Intelligence Gathering -> No more manual research. The system automatically enriches company records with technographics, funding data, org structure, and relevant news. Everything flows directly into HubSpot properties, keeping our CRM current without lifting a finger.

Lead Qualification & Routing -> AI agents assess fit based on ICP criteria, then route qualified leads to the right team members with full context. Sales reps get notifications with a complete brief, not just a name and email.

Follow-up Orchestration -> Based on engagement signals, the system determines optimal timing and messaging for follow-ups. It's like having a sales ops team working 24/7.

The real power is in the combination: Agent.ai handles the intelligence gathering and decision making, while HubSpot executes the workflows and maintains the source of truth.

For teams drowning in manual research and qualification work, this stack has been a game changer.

Huge thanks to Dharmesh Shah for making this technology accessible and for his visionary presentation on AI at INBOUND this year. The future he outlined is already here, and it's incredibly exciting to build with these tools.

Want to automate your workflows with AI? Whether you're looking to streamline sales processes, enhance lead management, or build custom integrations, I'd love to help. Drop me a DM or comment below with what you're trying to solve.

#AIAutomation #HubSpot #SalesAutomation #AgentAI #CRMIntegration #MarketingAutomation #SalesOps #AIAgents #WorkflowAutomation #B2BSales #RevOps #SalesTech #AITools #BusinessAutomation #LeadGeneration #INBOUND2025

I am pioneering the Future of Reskilling, at global scale, with urgency, and with a clear blueprint to prepare humanity for the AI age.

Across Fortune 500 boardrooms and refugee camps alike, the need is the same: talent that is AI-literate, outcomes-driven, and future-ready. That’s where I focus my life’s work.

With two decades of leadership at Infosys across the Americas and Europe, I’ve led transformation at the intersection of business, technology, and human capital. But in 2019, I turned that experience toward a more ambitious goal: to reskill and employ 1 million underserved individuals, especially youth in refugee camps and overlooked communities, using AI not just as a tool, but as a force multiplier for economic mobility.

Today, through StepUp.One and Human-Edge.ai, I’m building a new kind of workforce infrastructure, one that is digital, distributed, and deeply human. We partner with global enterprises, development agencies, and impact-focused leaders to deliver results, not just programs.

At the heart of our model is a 3-part Reskilling Formula designed for real-world ROI:

Master the Topic – This is where Today’s Learners Stop when they get their certificates.

Master the Skill – Apply the knowledge to deliver outputs. Use AI to amplify your results.

Master the Outcome – Drive Outcomes from Outputs. When they don’t come, Change your strategy, structure and execution.

This framework works equally well for a VP in New York, a jobseeker in Nairobi, or a student in São Paulo. It bridges the global reskilling gap not with hype, but with orchestration—pairing advanced AI agents with trained human operators to deliver performance at scale.

Our conviction is simple but radical:

Human + AI = Outcomes

But reskilling is only the starting point.

We go further by embedding this trained talent into AI-powered delivery pods that support everything from enterprise sales and marketing to fundraising, recruiting, and digital operations.
Whether it’s helping a Silicon Valley startup scale faster, or enabling a Fortune 500 firm to enter a new market with agility, our model proves this: underserved populations, when equipped with AI and structured support, can outperform traditional teams at a fraction of the cost.

If your mandate is to lead transformation—across markets, models, or mindsets—let’s talk. Because the future of work isn’t just about automation. It’s about inclusion, leverage, and creating a globally distributed workforce that wins.

Let’s build that future—together.

Mohamed Anis

Your founder spent 4 hours yesterday building prospect lists. 

Amira spent 4 years in a camp with a business degree, waiting.

We didn't train 1,400+ refugees from scratch. They brought degrees, language skills, work ethic. 

What we gave them: AI tools and access to what they'd been denied and dignified work.

The assumption has always been that refugees need charity until they 'integrate.' 

The reality: 80 million people with skills, stuck in systems that waste both their potential and your startup's runway. 

This isn't about aid.
It's about employment. 
Not pity, just execution.

What if the talent gap and the refugee crisis were never separate problems?

#RefugeeEmployment #HumanPlusAI #DignityOverDependency #TalentHasNoBorders #StepUpOne

We are your fractional Fundraising & Growth team.

We use proprietary AI to do the grunt work (list building, signal tracking, thesis matching), so our experts can focus on closing meetings for you.

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Raising money doesn’t fix startups.
It exposes them.

Fundraising doesn’t start with investors.
It starts with founder clarity.

Fundraising isn’t about finding more investors, it’s about finding the 80 who are already looking for you.

Most founders don’t get rejected.
They just show up at the wrong time.

Fundraising isn’t a numbers game. It’s an intent game.
80–120 investors > 1,000 random names.

Single-channel outreach is why your response rates are stuck at 2%.
Orchestration is how teams get 30–40%.

Personalization isn’t a growth tactic.
It’s respect.

Here’s where my head’s been lately:

In 10 years, most “websites” will look embarrassingly primitive — the way brochures feel today.

Not because design gets prettier.
Because the unit of value changes.

Right now, we publish pages and hope humans will:
	•	find them
	•	read them
	•	connect the dots
	•	take action

That’s a very 2005 workflow.

What’s coming is presentation as a living system, not a document.

A website won’t be a place you “browse.”

It’ll be an interface that:
	•	recognizes intent
	•	asks one sharp question
	•	generates the right view (investor, buyer, auditor, candidate, regulator…)
	•	proves claims with evidence
	•	adapts in real time

Same for pitch decks, RFPs, DD reports, industry analysis:
We’ll stop shipping static PDFs and start shipping interactive arguments.

Think of it like this:

A website today is a menu.
A website tomorrow is a chef.

The chef doesn’t hand you 12 pages of options.

They ask: “What are you hungry for?”
Then they serve exactly what matters, with the ingredients list if you’re skeptical.

Devil’s advocate: most people will misuse this.

They’ll generate endless “personalized” fluff and call it innovation.

The winners will do the opposite:
	•	fewer claims
	•	tighter proof
	•	clearer point of view
	•	faster path to decision

The real competitive advantage won’t be “content.”

It’ll be credible, queryable truth — packaged for both humans and machines.

Curious: if your website had to convince an AI buyer first (before a human ever sees it), what would you delete… and what would you prove?

Fundraising doesn’t start with outreach.
It starts with strategy.

AI ranked our investors. Humans fixed it. 
Here’s why that step matters more than the model.

From 847 investors to 80 that actually matter.

Scale comes from AI.
Quality comes from humans.
Outcomes come from both.

You can’t sell what you don’t deeply understand, and most GTM teams never touch the product.

Silicon Valley just spent $180B discovering what we proved in a refugee camp 18 months ago.

The AI pragmatism revolution?

We've been living it since day one because we had no choice.

While VCs now celebrate "smaller, smarter models," our question remains: Why did anyone think removing humans was ever the answer?

We've trained 1,400 refugees in Kakuma to leverage the same AI tools your company pays six figures to deploy.

Same GPT-5.

Same Claude Opus.

Same Gemini.

The gap was never the technology.

The results speak for themselves:

Yasmin in Kakuma achieves an 18% response rate using Claude for outreach.

Your $10K automation stack? 1-2%.

Our teams book 24x as many meetings as pure AI workflows.

They close deals that bots labeled 'unresponsive.'

Not because they're special, but because they're human.

Yasmin doesn't just execute prompts.

She catches when a prospect's "not interested" actually means "wrong timing."

She reads the three-day message gap as a budget freeze, not rejection.

She knows which cultural contexts require formal language and which require casual rapport.

AI generates outputs.

Humans create outcomes.

Now TechCrunch writes about "AI pragmatism."

IBM sells "human-in-the-loop deployment."

Gartner predicts "the hybrid workforce model."

We didn't predict this.

We lived it because refugees can't afford to waste money on automation theater.

The future of work isn't coming.

It's already here, running in places you've never heard of, powered by people the world overlooked.

So far, we have paid $800K+ in wages to refugees who outperform your automation.

Not charity.

Competitive advantage.

We're solving two crises simultaneously: displaced talent seeking dignified work, and companies burning cash on AI that doesn't convert.

The solution was never either/or.

So here's my question for every executive buying the "AI efficiency" pitch:

If the industry's smartest minds just figured out that smaller, focused AI works best—why are you still trying to remove the humans who make it actually work?

The pragmatism revolution isn't about better models.

It's about finally admitting you need Yasmin.

#AI #FutureOfWork #RefugeeEmployment #HumanInTheLoop

When your biggest customer can't pay their bills, do you invest $2B or admit your growth story has a dependency problem?

NVIDIA's CoreWeave move isn't a bailout; 

It's vertical integration dressed in partnership PR.

They're locking in demand for next-gen chips while ensuring their distribution channel doesn't collapse under $18B of debt.

The real risk isn't the investment, it's what happens when every AI infrastructure play is funded by the chip maker who needs them to buy chips.

Is this ecosystem genius, or are we watching the AI hardware market eat itself from the inside out?

Thoughts? 

#Nvidia #AI #TechDrama

https://lnkd.in/ePNhXcF2?

Open article: Nvidia Invests $2 Billion in CoreWeave in AI-Factory Collaboration by wsj.com

Nvidia Invests $2 Billion in CoreWeave in AI-Factory Collaboration

We thought we were selling AI-powered project management.
Our customers told us we were selling something very different.

10,000 emails. 8,000 burned prospects. Zero pipeline. 
Here’s what actually killed this outreach.

Teaching Chemistry to AI Might Be Teaching Weapons Design

We've been teaching frontier AI to refuse dangerous requests while ignoring that its benign outputs become training data for models that won't refuse.

Anthropic's research shows frontier models don't need to write bomb recipes. 

They just need to explain chemistry well enough that smaller models connect the dots during training.

This is a safeguard theatre.

We police what models say while ignoring that their explanations become the curriculum for less-aligned models.

Every helpful chemistry explanation becomes tomorrow's training data.

Every refusal teaches the workaround; when models explain 'safe' alternatives, smaller models learn the underlying principles anyway.

The question isn't what models refuse to answer.

It's what the next generation learns from everything they do.

#AISafety #AIAlignment #MachineLearning #AIEthics

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The Battle

Dharmesh Shah

Mohamed Anis

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The Battle

Dharmesh Shah

Mohamed Anis

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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);}Dharmesh Shah's LinkedIn Performance

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