
Co-Founder of https://teapawt.net/t.co/MFTAmna8Lm, 🇨🇦 ex-@twilio, @microsoft, @hearsaysystems. Loves building, developers, communications and skiing.
San Francisco, CA
Joined August 2012
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Mark Gilbert retweeted
AI’s ability to make tasks not just cheaper, but also faster, is underrated in its importance in creating business value.
For the task of writing code, AI is a game-changer. It takes so much less effort — and is so much cheaper — to write software with AI assistance than without. But beyond reducing the cost of writing software, AI is shortening the time from idea to working prototype, and the ability to test ideas faster is changing how teams explore and invent. When you can test 20 ideas per month, it dramatically changes what you can do compared to testing 1 idea per month. This is a benefit that comes from AI-enabled speed rather than AI-enabled cost reduction.
That AI-enabled automation can reduce costs is well understood. For example, providing automated customer service is cheaper than operating human-staffed call centers. Many businesses are more willing to invest in growth than just in cost savings; and, when a task becomes cheaper, some businesses will do a lot more of it, thus creating growth. But another recipe for growth is underrated: Making certain tasks much faster (whether or not they also become cheaper) can create significant new value.
I see this pattern across more and more businesses. Consider the following scenarios:
- If a lender can approve loans in minutes using AI, rather than days waiting for a human to review them, this creates more borrowing opportunities (and also lets the lender deploy its capital faster). Even if human-in-the-loop review is needed, using AI to get the most important information to the reviewer might speed things up. The ability to provide loans quickly opens up the market to new customers in need of rapid funds and helps customers who need a quick positive or negative decision to accept the loan or move on.
- If an academic institution gives homework feedback to students in minutes (via sophisticated autograding) rather than days (via human grading), not only is the automation cheaper, the rapid feedback facilitates better learning.
- If an online seller can approve purchases faster, this can lead to more sales. For example, many platforms that accept online ad purchases have an approval process that can take hours or days; if approvals can be done faster, they can earn revenue faster. Further, for customers buying ads, being able to post an ad in minutes lets them test ideas faster and also makes the ad product more valuable.
- If a company’s sales department can prioritize leads and respond to prospective customers in minutes or hours rather than days — closer to when the customers’ buying intent first led them to contact the company — sales representatives might close more deals. Likewise, a business that can respond more quickly to requests for proposals may win more deals.
I’ve written previously about looking at the tasks a company does to explore where AI can help. Many teams already do this with an eye toward making tasks cheaper, either to save costs or to do those tasks many more times. If you’re doing this exercise, consider also whether AI can significantly speed up certain tasks. One place to examine is the sequence of tasks on the path to earning revenue. If some of the steps can be sped up, perhaps this can help revenue growth.
Growth is more interesting to most businesses than cost savings, and if there are loops in your business that, when sped up, would drive growth, AI might be a tool to unlock this growth.
[Original text: deeplearning.ai/the-batch/is… ]
Mark Gilbert retweeted
When enterprises go AI-first, a mistake to avoid is to think about the existing finite amount of work that already happens, and to use AI to reduce the cost of that work.
Instead, the full power of AI is that it lets you finally get around to the types of things that you didn’t or couldn’t work on before, because of the cost of hiring or outsourcing that work was just too expensive; or it lets you automate away the kind of drudgery work that was preventing you from doing the stuff that really matters.
In most businesses there’s a near infinite backlog of this kind of work if you just start to ask the question of “what if X thing was all of a sudden 100X cheaper or more accessible, what more could you do?”
Companies adopting an AI-first approach should be thinking through what it means when they can write code, review contracts, generate leads, run projects, create marketing collateral, do research, or handle customer requests at a far faster rate than before.
Where are the new revenue generating opportunities? How can you enter new markets? How do you get new breakthroughs to customers faster? How can you onboard customers at a faster rate? And so on.
And, eventually when there are areas of direct cost savings on existing work, I’d bias toward a “keep what you kill” approach to AI adoption, where orgs that get productivity gains can reuse the upside in their function. You will end up driving more adoption of AI, driving a positive flywheel of usage vs. resistance or avoidance.
Ultimately, when you drop the cost the cost of intelligence to near-free, you can begin to do far more than what was possible before. This is the real potential of an AI-first enterprise.
Awesome @ascend_vc !
Filing: Seattle VC firm Ascend raising third fund to back more startups in Seattle and beyond geekwire.com/2025/filing-sea…
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Mark Gilbert retweeted
AI Agents will be the biggest shift to enterprise software business models that we've ever seen.
The typical business model of enterprise software has generally been that one user on the system equals one licensed seat. This model is obviously logical in a world where most users get roughly the same amount of value from each license of the software.
But it's also had the limiting effect where your TAM is naturally constrained by the employee headcount tied to the particular use-case of your customer. Historically, this has meant that the only solution to growth is going after larger and larger seat-based categories of software. There are exceptions recently in vertical SaaS that have made a killing on flipping the trend, but even they get TAM-limited too soon.
In a world of AI Agents, clearly this is going to be very different. Agentic workflows have no upper limit on how much they can be deployed by an enterprise. And all of a sudden the software categories that were once constrained by seat volume, have no such limits anymore. We're already seeing examples of AI Agents in coding, research, legal work, and other advanced categories that are being billed at multiples of their prior seat-based software equivalent price.
This provides a completely new growth vector for software companies in AI, and has major implications to software business models. For a wide number of use-cases, there may be little to no connection between the number of users on a platform and the total amount of usage of AI Agents that use the software -- and what the value is that those Agents can deliver. And for many use-cases, the idea of a user seat being tied to the agentic workflow altogether is unnecessary when agents are just running around completing work in the background for an enterprise.
We're still very early in discovering how this will ultimately evolve, and a big open question will be how the industry lands on the units of measurement of these AI Agents. AI Agents may logically be represented by a single agentic user performing an action in a system (like a superuser of the platform), but there's little architectural difference between having 100 agents complete one action a minute vs 1 agent completing 100 actions a minute.
No matter the ultimately pricing construct -- which will likely have to correlate to the amount of output the AI Agents are producing -- it's clear that this will lead to a TAM increase in software. Very exciting times ahead.
Mark Gilbert retweeted
I am so proud that @UWaterloo is finally getting its recognition as a world class school. When I first came to the valley in the late 90s, I continuously had to explain that Waterloo is Canada’s top technical university and not just a historic battle from 1815.
How has @Uber gotten so bad? I’ve tried them 3 x in the last 2 weeks, have a 4.89 rating and nobody will pick you up in SF or at SFO. I think the only team ⬆️ business is ads which play while they don’t find you a car. I can just imagine that team celebrating in exec reviews.
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Mark Gilbert retweeted
Twitter just shared plans to revamp its business at a private investor's presentation.
Both Elon and new CEO Linda Yaccarino attended.
Here are 3 ways that Twitter will change:
Mark Gilbert retweeted
OK Seattle - #FoundersBash 2023 registration is open!
Last year we had 400 founders in the bldg to chill w @djtopspin vibes, good food and zero content or salespeople :-)
Remember, FOUNDERS ONLY. We're checking.
(VC friends DM for access)
eventbrite.com/e/founders-ba…
Mark Gilbert retweeted
A new wave of generative AI companies is already here. But they're invisible on market maps that over-index on incumbents.
So we tapped our network to reveal the up & comers. Early-stage companies showing signs of future greatness.
Meet the AI Hot 75.
nfx.com/post/generative-ai-h…
Excited to see @HashlessApp launch!
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Mark Gilbert retweeted
Don’t worry that you’re X years old. Appreciate that in ten years you’ll wish you were ten years younger. And today you are.
Mark Gilbert retweeted
Note to graduates: Now may be a great time to start a company - wisdom from founder @clarashih @HearsaySystems wsj.com/articles/graduating-…
Congrats on the new role @michaelhlock, and great move @shasta!
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Mark Gilbert retweeted
Thx to Clara & the whole team at Hearsay! dig-in.com/news/amfam-taps-h…
Congrats @yasminzarabi ! – at Burlingame, CA
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Hearsay is officially on Microsoft's AppSource! @MSFTAppSource @MSFTDynamics365 https://teapawt.net/t.co/BXqF9hsVoP
Mark Gilbert retweeted
Last day in my office! When I moved in, I put these words of wisdom on the outside of my door. They were given to me by a mentor, and I am passing them on to the next generation. In every transition, it’s important to leave a place a little better than you found it #walkthewalk















