Jackie DiMonte

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Jackie DiMonte

Jackie DiMonte

@jaydimonte

🏗️🏭🚛

Katılım Aralık 2015
591 Takip Edilen2.4K Takipçiler
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Jackie DiMonte
Jackie DiMonte@jaydimonte·
We all know about "crossing the chasm" when it comes to starting with early adopters and moving on to the majority A necessary action for any startup pursuing scale But, this framework isn't helpful for industrial startups...
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Jackie DiMonte
Jackie DiMonte@jaydimonte·
Lots of AI companies look like they have product-market fit. Some may only have product-event fit. AI created one of the largest shocks software has ever seen. It became the “why now” behind nearly every new opportunity. The harder question is: how long will it last? The strongest companies pair a shock with a shift. 🔵 The shock creates urgency. 🔴 The shift sustains demand. I published a framework for thinking about startup timing: shocks, shifts, why the best markets combine both, and the rare companies that create their own conditions. Link in comments.
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Jackie DiMonte
Jackie DiMonte@jaydimonte·
Series A is the new B? Try again. A is the new C. The median Series A in 2026 is nearly $20M 🟰 Series C round a decade ago 🟰Series B in 2020. The median Series B is now about $40M, roughly what a late-stage growth round looked like six or seven years ago. Meanwhile... Seed rounds are up, but they haven’t kept up. 📈 The median seed round is ~$3M… up 2.3x over 10 years versus 4.3x for A and 3.6x for B. At the same time, companies are expected to accomplish far more before each subsequent round than they were a decade ago. Rational at the letter rounds, but harder to do with seed. The bar for an A has grown faster than resourcing. Perhaps one reason seed-to-A conversion keeps falling.
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Jackie DiMonte
Jackie DiMonte@jaydimonte·
🦄 AI unicorns are in a league of their own. Bad news for the class of 2021. Roughly 30% of unicorns minted before 2022 still haven't raised another round. After a few years of pullback, unicorn creation is accelerating again. This year is on pace to surpass 2022. Will we see the same rate of zombiecorns out of this cohort? Maybe not. The dynamics are different. Volume is back to 2022 levels, but dollars have blown past them. The implications are significant: ➡️ Venture is becoming more concentrated. Instead of hundreds of breakout companies attracting capital from individual firms, we're increasingly seeing dozens of mega funds concentrated into dozens of companies. ➡️ Outcomes become more correlated. The industry's returns become increasingly dependent on the same small set of winners. ➡️ The incentives change. When many of the largest funds own meaningful stakes in the same companies, they also have the capital and incentive to keep supporting them.
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Tim Latimer
Tim Latimer@TimMLatimer·
In hardtech, engineering innovation is what gets you started but supply chain is how you win.
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Jackie DiMonte
Jackie DiMonte@jaydimonte·
@ColinGardiner red dot keeps moving clockwise x.com/jaydimonte/sta…
Jackie DiMonte@jaydimonte

AI slop is coming for the enterprise. Today, the 𝘱𝘦𝘰𝘱𝘭𝘦 𝘣𝘶𝘪𝘭𝘥𝘪𝘯𝘨 𝘵𝘩𝘦 𝘮𝘰𝘴𝘵 𝘸𝘪𝘵𝘩 𝘈𝘐 are early adopters. The 𝘤𝘰𝘮𝘱𝘢𝘯𝘪𝘦𝘴 𝘸𝘪𝘵𝘩 𝘵𝘩𝘦 𝘮𝘰𝘴𝘵 𝘱𝘦𝘰𝘱𝘭𝘦 building with AI are early-adopter companies. That won't last. As these tools improve, more people will use them across more companies. It won't just be the tech-natives. It'll be everyone. 🙅‍♀️ It'll be Pam from procurement who builds her own agent… that promptly rejects a PO from a new vendor for critical parts. 🙋‍♂️ It'll be Max from marketing who spins up a web app… that burns through $100K of compute when his branded meme generator goes viral overnight. Now multiply that across every employee, every department. Think about how many mistakes we've already seen very capable people make with the release of clawdbot. Then scale that to the rest of the enterprise. We're not yet in the age of "everyone builds." But when we get there, the real question won't be how. It'll be for how long. Then it's back to permissioning, security, and… SaaS again. It's one of the reasons behind why Grid is focused on net new operating systems and outsourced services [🔗@jaydimonte/p-159090810" target="_blank" rel="nofollow noopener">substack.com/@jaydimonte/p-…]. Everything in between feels somewhat cyclical at the enterprise.

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Colin Gardiner
Colin Gardiner@ColinGardiner·
Software as a Service is dead. Slop as a Service is booming.
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Jackie DiMonte
Jackie DiMonte@jaydimonte·
Angels make the world go round. 😇 Per AngelList, the median commitment size for a... <$5M fund is $10K. $5–20M fund: $50K. $20–250M fund: $100K. Fund commitments at these check sizes are overwhelmingly coming from HNW individuals… and likely a lot of overlap with folks that are (or would be) angel investors. This shows up in the data: 50% of dollars going to <$20M funds come from individuals (vs. family offices and institutions). But that participation is slowing, and that’s meaningful. I've written before about the decline of angel-led rounds in the last few years. The slowing of small fund fundraising might trace back to the same pullback. All to say, just like angels in early companies, those first LPs into emerging funds are special. At Grid, a number of those folks backed us fast and early. Forever grateful for their partnership.
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Jackie DiMonte
Jackie DiMonte@jaydimonte·
Is AI delivering real value? The answer may surprise you. Almost 20% of the 81K AI users Anthropic surveyed say AI has not delivered value to them. That's more than people who say AI is a great thinking partner (17%), helps them learn new things (10%), or synthesizes research (7%). The one exception is productivity, with 30% of users seeing gains. For me, the biggest takeaway is that we're still experimenting with what AI is, how to use it, and where to extract value. And as models get better and more capable, they restart the experimentation process entirely. What features were not helpful a month ago are dramatically more useful today. Will be interesting to see the next time they publish data. Will "no value" still be among the top rankings?
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Jackie DiMonte
Jackie DiMonte@jaydimonte·
SPVs are booming. But where the money is going tells a different story than where the deals are. Great data from Sydecar on SPV activity last year: 📈 SPV deal count 2x+ last year and capital invested 2.5x+ But look at the split: 🔵 Primary SPVs account for 75% of deals but 54% of value 🔴 Secondary SPVs made up 25% of deals but 46% of value In other words, secondary SPVs are fewer deals with much bigger checks: 🔵 Primary SPVs tend to be angel groups and smaller syndicates pooling capital into early rounds 🔴 Secondary SPVs are for accessing proven (hot?) opportunities As the exit slump continues, my guess is secondary SPVs are becoming one of the primary tools for getting capital in (and out) of late-stage positions. Expect 2026 to be more of the same.
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Jackie DiMonte
Jackie DiMonte@jaydimonte·
We’re in the early innings of AI, and no one really knows what comes next. Ramp published data on the percentage of their customers purchasing AI tools, and it's wild. Some notes: Almost 50% of businesses are paying for AI, up from 5% roughly three years ago. Increased adoption of 🟢 OpenAI and 🔵 Claude is fueling most of the growth. The former was quick out of the gate, the latter is accelerating fast. 🟡 Google, despite a built-in distribution advantage, hasn't seen meaningful incremental spend. What's different this last year is that businesses are spending on 🟢 🔵 🟡 MULTIPLE platforms. Early last year was the first time we saw meaningful overlap. Now, nearly 20% of volume comes from companies paying for more than one provider. We've framed this market as a battle of the models, perhaps so much so that there will be one "winner." In reality, there'svery little loyalty and data moats aren't creating lock-in. But unlike prior startup battles (i.e. Uber vs. Lyft), competition is happening through product advancement, not price. LLMs are not commodities (yet?). With a prize so big, platforms are sprinting at it. New capabilities on what feels like a daily basis. For now, the consumer is the winner. Excited to see how the next 3 years play out.
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John Palmer
John Palmer@johnpalmer·
someone should do a VC firm that's "founder-demanding" vs founder-friendly, and it's akin to the navy seals. hardcore people only.
John Palmer@johnpalmer

I think a lot of founders who could otherwise be great are failing due to a lack of oversight / discipline. There are so many startups out there funded by top VCs that are just kind of…messing around. No focus, wasting money, shipping slowly. I think it would be great for everyone involved to bring back a more hardcore investor relationship that is constantly pushing the founder in the right direction.

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Jackie DiMonte
Jackie DiMonte@jaydimonte·
📊 45%+ of workers say they “use AI.” The real number is so much lower than that. Most people aren’t using AI the way people in tech mean it 𝘵𝘰𝘥𝘢𝘺. They’re using LLMs to edit emails, summarize documents, or replace search. Meanwhile, the pace of change is so fast that “using AI” isn’t a one-time adoption event. It requires constant learning, unlearning, and tinkering. Every new wave of AI capability resets the adoption curve. So, where we think we’ve hit the majority, it’s still the early adopters leading the charge. I’m seeing two opposing forces at work: 📉 Some people fall off the learning curve completely, adopting one use case and getting stuck there. 📈 Each advancement makes the most powerful features easier to access, pulling new users in. A lot of the anxiety about the future comes from confusing those two curves. We may think we’re "late" but I think we’re just getting started. Think of... what's the best thing you can do with AI now that you couldn't three months ago?
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Cam
Cam@camdoody·
Idk who needs to hear this today, but never ever tell a founder good luck.
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Jackie DiMonte
Jackie DiMonte@jaydimonte·
AI slop is coming for the enterprise. Today, the 𝘱𝘦𝘰𝘱𝘭𝘦 𝘣𝘶𝘪𝘭𝘥𝘪𝘯𝘨 𝘵𝘩𝘦 𝘮𝘰𝘴𝘵 𝘸𝘪𝘵𝘩 𝘈𝘐 are early adopters. The 𝘤𝘰𝘮𝘱𝘢𝘯𝘪𝘦𝘴 𝘸𝘪𝘵𝘩 𝘵𝘩𝘦 𝘮𝘰𝘴𝘵 𝘱𝘦𝘰𝘱𝘭𝘦 building with AI are early-adopter companies. That won't last. As these tools improve, more people will use them across more companies. It won't just be the tech-natives. It'll be everyone. 🙅‍♀️ It'll be Pam from procurement who builds her own agent… that promptly rejects a PO from a new vendor for critical parts. 🙋‍♂️ It'll be Max from marketing who spins up a web app… that burns through $100K of compute when his branded meme generator goes viral overnight. Now multiply that across every employee, every department. Think about how many mistakes we've already seen very capable people make with the release of clawdbot. Then scale that to the rest of the enterprise. We're not yet in the age of "everyone builds." But when we get there, the real question won't be how. It'll be for how long. Then it's back to permissioning, security, and… SaaS again. It's one of the reasons behind why Grid is focused on net new operating systems and outsourced services [🔗@jaydimonte/p-159090810" target="_blank" rel="nofollow noopener">substack.com/@jaydimonte/p-…]. Everything in between feels somewhat cyclical at the enterprise.
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Trace Cohen
Trace Cohen@Trace_Cohen·
You think a corporate team can vibe code enterprise production level code that is secure after meeting 10 times and outsourcing it over seas to a team they never met? Ngmi
dax@thdxr

everyone's talking about their teams like they were at the peak of efficiency and bottlenecked by ability to produce code here's what things actually look like - your org rarely has good ideas. ideas being expensive to implement was actually helping - majority of workers have no reason to be super motivated, they want to do their 9-5 and get back to their life - they're not using AI to be 10x more effective they're using it to churn out their tasks with less energy spend - the 2 people on your team that actually tried are now flattened by the slop code everyone is producing, they will quit soon - even when you produce work faster you're still bottlenecked by bureaucracy and the dozen other realities of shipping something real - your CFO is like what do you mean each engineer now costs $2000 extra per month in LLM bills

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Jackie DiMonte
Jackie DiMonte@jaydimonte·
@volkertdesign Yea, more tongue in cheek. From what I’ve heard it’s too hard to get through IT
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Nick Volkert
Nick Volkert@volkertdesign·
@jaydimonte Technically, yes? I've also heard practically no one uses it though. But I'm sure it's at a lot of people's fingertips because of how Microsoft is pushed on everyone.
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Jackie DiMonte
Jackie DiMonte@jaydimonte·
Building trust with customers is the #1 skill for vertical AI founders today. Especially in markets like manufacturing, healthcare, and construction where tolerance for error is near zero. Once a tool is in production, it has to work... and keep working. At Grid, we spend a lot of time thinking about what makes AI hard to adopt in these sectors. It usually comes down to two things: 1️⃣ Complexity — How hard is the organization, workflow, or task to model? 2️⃣ Criticality — How painful are the consequences if it fails? The higher the C² score (complexity × criticality) the harder it is to drive adoption. That’s why we’re focused on companies solving both the 𝘁𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 and 𝗰𝘂𝗹𝘁𝘂𝗿𝗮𝗹 side of the curve. The ones who know: if you want to transform high-C² sectors, you have to earn your place in the hands of the operator first.
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