Totally Prepared for 2026

Summary

Paul Ford and Rich Ziade kick off 2026 with a predictions episode, centering on a spirited debate about whether AI-accelerated startups can disrupt entrenched platform companies. Paul takes the maximalist position: with code becoming nearly free to produce, small teams of 10-12 people can spin up competitors to platforms like Seamless, DoorDash, and Uber, attracting VC funding and chipping away at incumbents. Rich pushes back hard, arguing that platform building is a tiny fraction of what makes companies succeed — network effects, people, culture, old habits, and the messy reality of serving restaurants with non-English-speaking delivery workers are the real barriers.

The debate plays out through a vivid thought experiment where Paul progressively builds his hypothetical Seamless competitor, adding product managers, automated marketing bots, and AI-powered restaurant onboarding, while Rich keeps raising the stakes with real-world complexity. They reference the People’s Almanac Book of Predictions from the 1970s, where everyone predicted moon colonies by 2000 but completely missed computers. Paul frames the current moment as the “space age era of AI” where people overestimate the velocity of social change. Rich ultimately agrees that cheap platforms will attract VC money and attempts at disruption, but insists the ones that simply replicate existing services will fail — only those offering genuinely different experiences have a shot.

Highlights

”We’re in the Space Age Era of AI”

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“I think we’re in the space age era of AI where people are like it’s all going to be this and only this forever. The cultural change transformation narrative is very similar to that of the space age where we were all going to be literally in orbit by now.” — Paul Ford, 3:06

”The Gatekeepers Are People”

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“The thing that people get wrong more than anything around technology is they forget that the gatekeepers are people. Almost every time. The guard in front of that gate? Old habits. Old patterns. Status quo and culture and power. And the truth is, people often win.” — Rich Ziade, 4:04

”Someone Could Make Seamless Next Year”

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“Next year someone could make Seamless or GrubHub or DoorDash. They can make their own. They can launch it. It will be cheaper and better. It will be AI enabled. You’ll just take a photo of your menu, upload it, it’ll make a website and set everything up for you.” — Paul Ford, 6:20

”They Send Someone to Your Restaurant”

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“One of the things these platforms do is they send someone to your restaurant to set you up with a laptop for 3 days and take pictures of your food. Because otherwise it just isn’t going to happen. Nobody wants to click on anything. There are armies of salespeople. It is a nightmare. It is an absolute nightmare.” — Rich Ziade, 12:15

”Making a Platform Is a Small Component of Succeeding”

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“Making a platform is a small component of disrupting and succeeding. Disrupting an existing status quo and succeeding. The cost of making a platform just went from many millions of dollars to tens of thousands of dollars. But that’s not what determines success.” — Rich Ziade, 14:30

Key Points

• People’s Almanac Book of Predictions (1:52) - Paul references this 1970s book where all predictions were wrong — everyone assumed moon colonies but missed computers; people overestimate velocity of social change
• Space age era of AI (3:06) - Paul compares current AI hype to space age enthusiasm where everyone assumed we’d be in orbit by now
• Gatekeepers are people (4:04) - Rich argues the biggest barrier to technology adoption is always people: old habits, culture, power structures, and status quo
• People often win (4:50) - When technology threatens to steamroll power structures, people find ways to co-opt it and say “look, I got this for you”
• Paul’s maximalist prediction (6:20) - Someone will make an AI-enabled competitor to Seamless/DoorDash with a team of 10 people and VC funding
• Rich’s objection: invisible iteration (7:00) - Current DoorDash/Seamless products are results of years of iteration, friction, and learning — like discovering delivery people needed non-English, visual-only apps
• Network effects as moat (9:00) - Three cohorts (delivery people, customers, restaurants) create tight network lock-in that’s extremely hard to break
• Automated marketing counter (9:30) - Paul proposes texting 3 million New Yorkers, AI-calling restaurants, offering $100 coupons — aggressive undercut strategy
• In-person onboarding reality (12:15) - Rich reveals platforms send armies of people to physically visit restaurants, set up laptops, and take food photos for 3 days
• Platform cost collapse (14:30) - Cost of building a platform went from many millions of dollars to tens of thousands, but building a platform is a small component of success
• Chowound and Arro precedents (15:30) - Previous attempts to disrupt Seamless (Chowhound) and Uber (Arro by NYC taxi commission) both failed despite having advantages
• Voice interface opportunity (18:00) - Rich predicts AI-driven voice interfaces will reset how we interact with technology beyond just going to ChatGPT
• Rich’s mom as use case (18:30) - Rich’s mother calls him to order food and Ubers, essentially using him as a human ChatGPT concierge
• New experiences matter more (16:30) - The startups that succeed won’t replicate existing platforms but offer genuinely different experiences, like conversational food ordering with dietary negotiation
• 36,000 egg foo young orders (19:30) - Paul predicts we’ll hear stories about AI ordering disasters in 2026
• Letter-sized paper analogy (20:30) - Word processors still think in pages; humans resist changing forms they’ve already agreed on

Mentions

Companies

• Seamless/GrubHub (6:20) - Food delivery platform; central example of entrenched network effects; been around ~20 years
• DoorDash (6:20) - Food delivery “monster”; example of platform with invisible years of iteration
• Uber/Lyft (6:50) - Ride-sharing platforms cited as examples of entrenched incumbents
• Aboard (24:00) - Paul and Rich’s company; ships custom software at a fraction of former cost
• Chowhound (15:30) - Attempted to save restaurants from Seamless/DoorDash fees; still around but didn’t disrupt
• Arro (15:50) - NYC Taxi & Limousine Commission’s Uber competitor; failed despite institutional backing
• EcoBee (18:30) - Wi-Fi thermostat with complex settings; example of technology that’s hard to use but could benefit from AI interfaces

Products & Technologies

• ChatGPT (17:30) - Referenced as current state of AI interaction; tactical amazing things like writing, images
• Google Home (18:30) - Rich still has it wired to his house; example of voice control ecosystem that’s “a disaster”

People

• Paul Ford (0:00) - Co-founder of Aboard; takes maximalist AI disruption position
• Rich Ziade (0:02) - Co-founder of Aboard; argues for power of network effects and people

Surprising Quotes

“People absolutely think the technology will move faster. They think the wrong technologies will move faster and they don’t even notice the ones that are about to move quickly. In the 70s, everybody assumed we were going to be living on the moon. They didn’t see computers happening at all.” — Paul Ford, 2:09

“Everybody’s like, ‘the tech is coming and is going to steamroll all of you.’ And people win most of the time. That’s what people don’t get.” — Rich Ziade, 4:50

“It turns out they didn’t expect that most delivery people would be non-English-speaking. And they found they couldn’t get drivers or bikers. The app had to be visual and easy to use and zero training. I guarantee they stepped in probably a dozen times till they got to that point.” — Rich Ziade, 7:30

“You picked a really hairy one. You picked one where there are three cohorts that have to be orchestrating together — delivery people, customers, and restaurants — and all of those people are on this platform and a really tight, taut network effect is kicked in.” — Rich Ziade, 9:00

“When you use a word processor, it still thinks in pages. We like that stuff. It’s hard to disrupt existing forms if humans have already agreed they like them. Letter-sized paper — we’re going to have that until we die.” — Paul Ford, 20:30

Transcript

0:00 Hi, I’m Paul Ford. And I’m Rich Ziade. And this is the Aboard podcast. It’s the podcast about how AI is changing the world of software. And man, is it. Well, it’s 2026, Rich. Happy New Year. Happy New Year. It just happened. We’re doing it again. Here we go. Back for another one. And so, let’s talk about just very rough a couple just very broad predictions. But let’s play that theme song first. Let’s do it.

0:43 Richard, how are you doing? I’m doing fine. This is a big exciting new year. I think it’s going to be a very interesting year for us. That’s where I start. I think I’ll be frank, things are kind of chill at home. I got two 14-year-olds, twins, which is a lot different than having two 12 and 13 year olds. People are doing good in school. Vacation’s over. God bless. Personally I’m counting on my bike and I’m counting on a good year here. Good year working with my business partner. This sounds like a Pepperidge Farm ad. Today we’re going to talk about artificial intelligence. It’s wholesome and good. How are you doing? I’m good. Same. Kids are amazing. Family’s amazing. Very blessed.

1:35 All right. Here we go. It’s the beginning of the year. Not a lot of news out there right now. Or too much news depending on how you look at it. I think we should just do a couple broad predictions about how things go. We got our predictions book here. I have this book. It’s the People’s Almanac Book of Predictions from the 70s. You see it on YouTube, it’s bright yellow.

1:52 The reason I like to bring it up is all the predictions are wrong. And I’ll tell you why predictions are wrong. People absolutely think the technology will move faster. They think the wrong technologies will move faster and they don’t even notice the ones that are about to move quickly. So in the 70s, everybody assumed we were going to be living on the moon. They just seen the moon landing. We’re going to get to Mars in 50 years. We’re going to do all this stuff. And they didn’t see computers happening at all because they were really big expensive machines. And everybody assumed that like weed would be legal by the 80s and cocaine by 2000. Weed showed up. But they assume everybody assumes a very high velocity of social change based on their internal understanding of what needs to change.

3:00 If you see somebody say like this is going to change everything around a technology, it’s safe to assume that it’s going to plateau and something new is going to come along. So I think we’re in the space age era of AI where people are like it’s all going to be this and only this forever. It’s so futuristic. It’s so wild. We’re all going to just do this — talk to bots and have agents. And I’m not saying, look, this is our business. I’m not saying it’s not the most important thing that we’re doing right now. But I don’t know if the cultural change transformation narrative is very similar to that of the space age where we were all going to be literally in orbit by now. And so I think that’s where we are.

3:38 I think that’s a good observation and I think it’s the right one. What most people forget about technology is they forget that the gatekeepers are people. Almost every time. You can look at pretty much every Gartner report that plots things on a chart about what’s going to happen. What’s a gate? Adoption. So, someone is standing in front of a gate labeled adoption. Who is the guard? Old habits. Old patterns. Status quo and culture and power.

4:30 When technology shows up, that’s why right now it’s so dramatic, because there’s all this insinuation that the power structures, my job as VP, my bonus next year because I resell software that everybody’s telling me is going to be obsolete, is under threat. That is the big prediction. And the truth is, people often win. That’s what people don’t get. Everybody’s like, “the tech is coming and is going to steamroll all of you.” And people win most of the time. They find a way to co-opt the thing, make it their own, and say “look, I got this for you.” That’s already starting to happen.

5:30 We had a conversation last night on WhatsApp where I was like, man, this is moving fast. I’ve been doing lots of vibe coding and I figured out some really good approaches. So I threw a thought experiment out and when I do this, what I tend to do is tell you something’s going to change and then you say shut up it’s not going to change like that and then we fight. That’s how we do thought experiments. I tend to take a maximalist forward motion because Rich tends to think in terms of organizational transformation and I think in terms of technological progress.

6:20 So, I yesterday was like, listen, next year someone could make Seamless or GrubHub or DoorDash. They can make their own. They can launch it. It will be cheaper and better. It will be AI enabled. You’ll just take a photo of your menu, upload it, it’ll make a website and set everything up for you. And they will do that and they will get some VC funding and they will absolutely start to conquer the incumbents. That was my hypothesis. And what did you say? Absolutely not.

7:00 That’s my prediction by the way. You’re going to see next year VC funding and a lot of people approaching “can we attack and take over the incumbents who have a lot of lock-in with their platforms.” DoorDash, Uber, Lyft. Can we take them over with AI-accelerated, rapidly built platforms that are probably five-person teams as opposed to 500-person teams? I think you’re completely wrong on like 11 levels.

7:30 Reason number one. Seamless has been around for about 20 years. And you would think… the current version of DoorDash or Seamless is not the first version. It is a product of change and resistance and friction that had to go into place for it to exist successfully. You have no clue in your basement what iterations these platforms had to go through. For example — they didn’t expect that most delivery people would be non-English-speaking. They couldn’t get drivers or bikers. The app for the delivery person didn’t support their native language. Many of them are almost illiterate. It had to be visual and easy to use and zero training. I guarantee they stepped in probably a dozen times till they got to that point. Now you’re going to show up and spin up this app. I gave you one tiny example.

8:30 But hold on. How long did it take DoorDash to address that at a platform level? Probably months. What if as an AI maximalist I told you I can build a pretty good working version of everything you just described in like a day? Yeah, that’s fine. Okay. First off, you have to find out about these hitches. I gave you a hitch in hindsight. You’re going to find out a bunch of other hitches and then you’re going to have to react. Why don’t I just take some of my VC funding and go get a product manager from one of those companies to come? Oh no, you’re bringing people into the mix. Yeah, sure. I’m ready to spend a little money.

9:00 You picked a really hairy one. You picked one where there are three cohorts that have to be orchestrating together — delivery people, customers, and restaurants — and all of those people are on this platform and a really tight, taut network effect is kicked in. Give me half a million dollars. I’m gonna make a marketing pipeline that texts everybody. Just going to text all of them. Every New Yorker. Some of it’s going to go to spam, some won’t. I’m going to give them a $10 coupon. Hell, I’ll give them $100 — it’s probably worth it long term. Now I probably need $6 million in VC, but it’s a bargain. My team is maybe 10-12 people. I’m doing automated marketing. My bots are out there saying “I got $20 for you to install this app.”

10:30 And I’ve gone out and said to restaurants, “all you got to do is give me a picture of your menu and we take it from here.” I built a nice website and presence for these people and I give them a guaranteed lock-in of delivery rates never going above a certain amount. It’s 15 minutes to onboard a new restaurant. And I’m going to go talk to three million New Yorkers through automated marketing, texting, robot voice calls. I’ll tell them about restaurants in their neighborhood that bought in. Now it’s going to cost me, but I’ll get them. If I spend enough money, I can get those people and I can give them a coupon. You sound like you want to move fast and aggressive and undercut. I got to kill these guys before they get any bigger because they’re going to be able to build their platforms fast.

12:15 Let me share a really annoying tidbit on this example. One of the things these platforms do is they send someone to your restaurant to set you up with a laptop for like 3 days and take pictures of your food. Because otherwise it just isn’t going to happen. Nobody wants to click on anything. And they have done that. There are armies of salespeople who aren’t just salespeople — they know how to use something like Squarespace to set these people up. It is a nightmare. An absolute nightmare.

13:00 I can fix this for you too. Will you go to one URL as a restaurant person? One website. My AI bot is going to walk you through it and it’ll take any info you give me in any language. Just give me the menu and I’ll price it. I will extract it. I will tell you how much money you’re going to save. I will translate things into all the languages. You’re going to charge the price on my menu? Absolutely. But then you take your cut and now I’m not making any money. Fine, then we’ll up it by 5%. I don’t understand percentages. Then I’ll translate it visually and show you dollar bills stacking up.

14:00 I love the theme of this prediction. Here’s what I believe: I don’t want to go take on Seamless, but I do think that VCs will fund a group of 10 people who are convinced they can do it. So I think you’re going to see a lot of platforms emerge because the cost of making a platform just went from many millions of dollars to tens of thousands of dollars.

14:30 Yes. But making a platform is a small component of disrupting and succeeding. Disrupting an existing status quo and succeeding. I agree. But that’s also what every entrenched platform operator says. And then — is this as disruptive as the web? That you can build these things almost for free? Yes. The web was very disruptive because you no longer got a menu dropped at your door and then called them when you wanted Chinese food. Especially once mobile showed up, it was game over.

15:30 Now I can have all of those experiences plus new ones. For instance, I could call and negotiate with a robot chef to figure out what I really wanted to have for my 12 people coming over. It would set up a menu, present it to me, and send that to the restaurant. You can do something about that. You usually get — I don’t want to go through software. There’s also “I’m going to tell you the truth here. What I really want is General Tso chicken, but also what I really want is to not gain 7 pounds in salt weight tonight. Can you help me out? I need a place with small portions and lots of broccoli.” Like, I could be having that conversation and it could turn into an order.

16:30 What you might be is a player that routes that order to one of the big players. The big players are going to move slow. I’m sure there’s an AI team spinning up at DoorDash, which must be exciting meetings. They all want to make it so the interfaces around getting stuff is easier. My mom calls me to order food and I get on the app. She called you last week to order ramen for your aunt during a meeting with 10 people. No. Your phone just kept ringing for DoorDash in Bay Ridge.

17:30 I think maybe I’ll hijack your idea and give my prediction around interfaces. What’s really taken hold is you can go into ChatGPT and ask it questions, write a sentence better, make an image — the nano banana stuff is amazing. All really great. Now what hasn’t happened yet is grafting that kind of interface — which my mom can use, chat — onto tools that exist today. Meaning chat as the interface.

18:30 I know your mom. She’s super smart. She could absolutely in 10 minutes learn all this stuff. She has chosen that you will be getting it for her. Correct. The interfaces around all these other conveniences — raising the temperature in my EcoBee thermostat, ordering food, getting a car — are very point-and-click. You have to be savvy about how to use the software. We are going to hear stories next year about 36,000 orders of egg foo young getting to people’s apartments.

19:30 I don’t think the breakthroughs have shown up around interfaces. AI has the opportunity to reset how we interface with technology beyond just going to ChatGPT. The problem is the EcoBee team is another team. Where it can go is I just go into a thing and ask it what I want and it’s a layer on top of what is typically point-and-click UX design software.

20:00 I’m doing this with things I used to be very good at like deploying to web servers. Can all these big companies innovate and be smart about how these interfaces work? I don’t know. But the populations that can take advantage of these things would explode if they were much more accessible. I’m talking about kids and older people who don’t care for tech but want the conveniences. Whether that comes from the big players, I have no idea. It shouldn’t. It doesn’t have to. It’s not hard to make a clean interface to managing the temperature in your house that only requires you to speak.

20:30 There’s a hesitation to bring voice control stuff to AI too quickly. The truth is the voice control ecosystem is a disaster. Like to turn on your Christmas tree and preheat your house through voice — they’re so afraid bad things will happen. “Setting oven to 700.” It’s real messy. But there’s massive opportunity around it. I just think you can do it faster and cheaper and give it a whirl. It’s just so costly around the people. People discount the people side of so much of tech. And that’s a classic misstep.

21:30 I remember when chatbots before AI were going to run the world. Conversational interfaces. Turns out nobody wanted to deal with them. If you’re a nerd who works on the command line, you’re like “yeah, that makes sense to me.” Even VR and web3 — “you’re going to buy real estate in your headset.” All of that nonsense. When you use a word processor, it still thinks in pages. We like that stuff. It’s hard to disrupt existing forms if humans have already agreed they like them. Letter-sized paper — we’re going to have that until we die.

22:00 All right. I’m going to give you my exact prediction. The opportunity to establish new companies that disrupt existing big platform plays — it’s going to lead to an influx of VC and we’ll see a lot of those companies and some of them will start to chip away. In 2026 you’re going to see startups that start to eat at the big networks because you can build so much more quickly. And what we’ll find out is whether the ability to build, own, and operate a platform cheaply can overcome network effects.

23:00 We’ve put those two together culturally. You build the platform and you lock in the network. Now you can build the platform without the network. You don’t even need it. You can just go to town and build all day long.

23:30 I want to take a red line to your prediction. I like it. The red line I would make is I think the ones that try to just replicate existing platforms will fail. I think the ones that focus on pain points and see strange lateral opportunities — like what I described with ordering food conversationally — if you make the experience so different and it opens up opportunity for people who wouldn’t use it anyway and it’s weird and different, then I think that’s really interesting. You have to do something a little different, a twist. You can try because it’s cheap, so why not?

24:00 All right. We’re going to see it this year. What is our company? We are Aboard. We ship custom software at a fraction of what it used to cost. We’re learning something that underlines what I’ve been saying — when you go into places, they have particular problems and you have to talk to them. We can stand up a really good CRM-style platform in like 5 minutes. It’s incredible. But it’s not necessarily what anybody needs. No one is impressed with how fast we can do it. They’re impressed that we can change things quickly to meet their needs.

25:00 It turns out to be less about the one-shot “here’s the app” and much more about “hey, I really need people to be able to put in vacation time in this particular way so it’s compliant with our policies.” And if we can go “yeah, not a problem, let me get that for you,” then they are really excited about us.

25:30 Some people ask “are you guys an agency?” That’s because we walk and talk like one because we spend time with you. The platform we use to deliver is insanely accelerated. We could never deliver it that quickly and cheaply. But we still want to talk to you and spend time with you.

26:00 To be clear, the product is that you license our platform and we work with you to give you the whole thing. You get the power of AI but in a way that is hewed to how you work and safe and reliable. Not a lot of vibe-coded code slopping everywhere, but a real code system. We’re having some fun conversations with smaller businesses that have never been able to get custom software before. It’s very cool. Check us out at aboard.com.

26:30 There it is. Hello@aboard.com if you need us. We’re glad to talk. Give us five stars. Do all the stuff. Let’s start this year off right. Stay healthy in 2026. Any New Year’s resolutions? Just keep going to the gym. That’s what I’m doing. I’m biking a lot. Have a great year, everybody. We’ll be back next week. Bye.