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

I'm  a massive fan (and daily user) of agentic coding tools like Claude Code and Codex CLI.

One of the questions we'll need to ponder in 2026:

How do you make sure that the compounding value you are getting from the use of agentic coding exceeds the interest on the technical debt that AI creates along the way?

The hope is that we'll be able to use AI itself to pay off the technical debt as the models and tooling get better.

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

Christopher S. Penn is an internationally renowned keynote speaker who energizes audiences with his expertise on artificial intelligence in marketing. A recognized thought leader, he demystifies complex AI concepts, providing practical strategies that empower marketers to achieve breakthrough results. Christopher’s insights on leveraging AI for data analysis, content creation, and strategic decision-making have shaped five key trends in the marketing industry: Google Analytics adoption, data-driven marketing and PR, modern email marketing, marketing data science, and AI/machine learning in marketing. His journey in AI began in 2013, a decade before tools like ChatGPT brought the technology into the mainstream, giving him a deep understanding of its potential and practical applications. His engaging and informative presentations leave attendees with actionable takeaways they can implement immediately.

As co-founder and Chief Data Scientist of Trust Insights, Christopher leads a team of experts dedicated to helping businesses unlock the full potential of their data using cutting-edge AI solutions. His proven track record of success includes building AI-powered systems that have delivered double-digit ROI for prominent brands such as Cisco Systems, T-Mobile, Citrix Systems, GoDaddy, AAA, McDonald’s, Twitter, and many others. He is a 2025, eight-time IBM Champion in IBM Data and AI and co-host of the award-winning Marketing Over Coffee marketing podcast. He is a published author in the Journal of Applied Marketing Analytics, and his work is also reflected in over two dozen marketing books, including the bestselling “Almost Timeless: 48 Foundation Principles of Generative AI“.

Learn more:
ChristopherSPenn.com
trustinsights.ai
MarketingOverCoffee.com

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Christopher Penn

One of the ways I stay grounded is a morning walk with my spouse and dog. We follow the same general route each morning, and we bring along a trash bag and a trash picker. Along the way, we pick up litter. The first few times I did this, it was weird. Then it became routine. Then we found other people doing it, and entire organizations of local, like-minded folks who want to do something to support their communities.

I can tell you the names and professions of over half the people who live on my street, just because we've run into them during one or more dog walks. And people have said to us, "Oh, we see you all the time." They notice. They feel like we're part of the glue of our community.

There's a lot about the world we can't change. There's a lot about the world we can change but definitely shouldn't discuss in public spaces online. But what we can do right now, in this moment, are little things like cleaning something up every day. You don't have to make grand gestures or huge announcements.

Why? Because when you do something little over and over again, you become present in your community.

Look outside your window. How many people do you see out and about? That epidemic of loneliness you hear about? It's partly because we don't make use of the communities around us. Yes, it's amazing to have digital communities, but it's much more difficult to go out to coffee or lunch with most of them.

Communities thrive in presence and wither in absence.

When you go for a walk, you trigger a virtuous cycle. Humans are pack animals and copycats. When you pick up a piece of trash, you signal to the people around you that your community is worth making an effort for. It's the opposite of broken window syndrome.

And here's the thing that folks who work in security know—the more present you are, the easier it is to detect changes. You see the ebb and flow of daily life—and you know when something's amiss in ways that you can't if you're just behind a screen all day.

Go for a walk. Pick up a piece of litter. Say hello to a neighbor. If you're not present, others don't know they could be as well.

Co-Founder & Chief Data Scientist at TrustInsights.ai, AI Expert, AI Keynote Speaker

"Figure out 3 workarounds."

One of AI's superpowers can be summed up in this sentence, especially when you're doing work like coding, stats, analysis, or other similar kinds of work.

Very often, our human brains get stuck. We run into an obstacle, and we bang our heads against the obstacle. "What do you mean, WP Engine no longer supports .htaccess files? That's so stupid!" or "What do you mean, my favorite analytics trick doesn't work here? That's so stupid!"

We get stuck. We're so used to doing things a certain way, our way, that our ego and stubbornness block us.

Guess who doesn't have that problem? Generative AI. AI doesn't have an ego unless we give it one (don't). It only knows to be helpful, to try to fulfill our directives. Which means if you're good at delegating, good at giving instructions, then it's trivial to tell it something like:

"Here's what I want you to do. Here are the limitations, obstacles, and challenges you'll face. As you plan this task, figure out 3-5 workarounds for these limitations while sacrificing no functionality or outcomes."

It will do a better job than we do, for two reasons. First, it doesn't have strong opinions about the "best" way to do something. It will look at all the probable ways to accomplish a task. Second, it has a much wider view than we do of our task. We all suffer from the curse of knowledge, from what's in our heads. This applies blinders to us for any given task. Asking a machine with a broader perspective to come up with workarounds takes that bigger picture into account.

It's time to think bigger, and the way to do that is with AI helping you see a bigger picture.

#AI #GenerativeAI #GenAI #ChatGPT #ArtificialIntelligence #LargeLanguageModels #MachineLearning #IntelligenceRevolution

Are you turning over your prompts?

If you do work for others under contract - as an employee, as a contractor, as a business - there's a good chance somewhere there's a term: "work for hire".

DISCLAIMER: I AM NOT A LAWYER. I CANNOT GIVE LEGAL ADVICE. CONSULT A QUALIFIED LAWYER IN YOUR JURISDICTION FOR ADVICE SPECIFIC TO SITUATION.

In traditional consulting, if you do a work for hire, everything you make for that work is assigned to your client. (for the purposes of this post, client means whoever you work for, whether you're a full timer, contractor, indie, etc.) If you're a programmer and you write code in Python, you turn over your code as your work product. That's what work for hire broadly means - you make a thing, you hand over the thing.

Andrej Karpathy (OpenAI cofounder) famously said back in 2023, "The hottest new programming language is English", speaking about the still-new ChatGPT back then.

Prompts are code. They're just code in English or Danish or Swahili, not Python or Rust or Swift.

Which means if you are creating a work for hire using generative AI, your client is entitled under a work for hire contract to your prompts. Unless you specifically worked with your lawyer to exclude things like prompts, they are entitled to them in the same way they would be entitled to your source code if you were handing over a compiled binary (an app).

Key takeaways:

1. If you're the client, check with your legal team about whether you are entitled to prompts as deliverables.
2. If you're the worker, check with your legal team/your lawyer about how your contracts are structured (for full timers this is your employment agreement) and whether or not you can realistically carve out stuff like prompts as excluded background technology.

Either way, please have a conversation with your qualified legal resources sooner rather than later about whether things like your prompts and agents are yours or not for any given project.

Don't have one? Talk to folks like Ruth Carter (they/them) and Sharon Toerek.

#AI #GenerativeAI #GenAI #ChatGPT #ArtificialIntelligence #LargeLanguageModels #MachineLearning #IntelligenceRevolution

Do you have first principles in AI?

One of the most useful things you can do in AI systems, but especially agentic AI, is have a clear list of 3-5 first principles. These are the overarching guidelines that tell the machine what it always should be doing no matter what.

Part of the reason AI sometimes delivers substandard results is that there are too many conflicting directives and is not sure which to give priority to. You'd feel the same way if someone came to you with 132 things on a to-do list - and some of the tasks were conflicting.

If you had 3-5 first principles that you could use to judge which tasks were most important or which things override other things, you'd have a much easier time getting things done.

Here's an example of some of mine:

1. Fix over create: always update or fix before creating new. The exception is if your fixes exceed the required cyclomatic complexity.
2. Build a reusable test suite: never do one-off tests.
3. Put things where they belong. The orientation file tells you exactly where to put outputs.
4. Never defer necessary work. Whether or not a task is in scope, out of scope, heavy effort, or seemingly trivial, you are forbidden to put it off.
5. Use agents as much as possible.

For me and the work that I'm doing in Agentic AI, these first principles, especially in software development, help keep AI on the rails and understand exactly what it's supposed to be doing at any given time. 

I have additional rules that are project specific, but these first principles nudge it towards correct behavior. And if I give it conflicting instructions, I have to explain myself and why my instructions should override first principles.

Think about what first principles you would develop for all your AI work. You might have ones like "always ask our ICP" or "always use Markdown" or whatever it is that you have to correct AI the most. Keep it within 3-5. More than that, and you're basically making a stew of confusion.

Try this concept out. It will save you an enormous number of headaches.

#AI #GenerativeAI #GenAI #ChatGPT #ArtificialIntelligence #LargeLanguageModels #MachineLearning #IntelligenceRevolution

#ICYMI: Stop chatting with AI and start building with it.

Most people use Claude for basic chat, but if you aren’t using Claude Code in the terminal, you’re missing out on the engine's true power. In our latest "So What?" episode, we break down why this command-line environment is the gold standard for high-level tasks, from custom agents to control with Git.

#claude #code #aimodel #terminal #claudeterminal

In this week's In-Ear #Insights (the @TrustInsights #podcast) @katierobbert & @cspenn ask the big question: Should leaders #Hire, #Retrain, #Outsource, or #Replace with AI? We break down the toughest decisions facing managers today and explain why 'durable skills' are your secret weapon.

#Analytics #Data #FutureOfWork #Leadership #AIEthics

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The Battle

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Christopher Penn

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taplio

The Battle

Dharmesh Shah

Christopher Penn

Followers

Posts

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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