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# Giving Models an API for the Web, with Tabstack
- URL: https://apisyouwonthate.com/podcast/tabstack-an-api-for-the-web/
- Published: 2026-10-01T11:23:42.000Z
- Updated: 2026-10-01T11:23:42.000Z
- Description: Podcast host Mike talks to Tessa and Steve from Tabstack about building an API that gives standalone models access to the web.
- Author: Mike Bifulco
- Tags: 🎙️ APIs You Won't Hate (The Podcast)

## Show Notes

- Tessa - [https://x.com/tessak22](https://x.com/tessak22?ref=apisyouwonthate.com)
- Steve - [https://x.com/JustSteveKing](https://x.com/JustSteveKing?ref=apisyouwonthate.com)
- Tabstack - [https://tabstack.ai/](https://tabstack.ai/?ref=apisyouwonthate.com)  
  - Steve's PHP Library for Tabstack - [https://github.com/JustSteveKing/tabstack](https://github.com/JustSteveKing/tabstack?ref=apisyouwonthate.com)
- Mozilla - [https://www.mozilla.org/en-US/](https://www.mozilla.org/en-US/?ref=apisyouwonthate.com)

#### Transcript

An API for the Web, with Tabstack

****Mike Bifulco:** \[00:00:00\] Hello, and welcome to APIs You Won't Hate. My name is Mike Bifulco, I am sitting down for a long overdue chat with two of my friends from the internet. I don't think I've ever been in the same room with either of you, but I'm

100% confident I've been in the room with people who've been in the room with you. That's basically like being best friends as far as I'm concerned. Today I'm hanging out and chatting with Tessa Kriesel and Steve MacDougall both from TabStack. Tessa is the technical founding developer go-to-market at TabStack, and Steve is a developer experience works in developer experience at TabStack.

Why don't we start there? Tessa, why don't you give a, a brief intro of yourself. G- give me the the elevator pitch, the 30 seconds on Tessa.

****Tessa:** Oh gosh. Tess is wild and weird and chaotic and crazy. No like engineer by trade, really love just like building things. Got pulled into go-to-market about 10 years ago, which started in dev rel and it just unfolded from there. And I would say most recently becoming somewhat of an AI whiz, really learning all the tools, all the things, getting back into engineering big time for sure.

And just really enjoying this like kind \[00:01:00\] of chaotic world that we're living in where it's like, oh, I'm like engineering my go-to-market and building things in a matter of hours. And yeah, that's a good summary of me.

****Mike Bifulco:** Yeah, right on.

****Tessa:** I did forget part-time dairy farmer.

****Mike Bifulco:** Oh, that's cool. I'll have more questions about that without a doubt. Steve, how-- welcome as well. How about you? What's what's been going on with you? And tell us the intro on Steve.

\[00:02:00\] I think, so. Yeah, that makes you and I star-crossed kindred opposites, 'cause I'm the API guy who really likes the front end part of things and yeah we're like linked for better or worse to one another's work, I think.

Hey, look, everyone has their expertise.

I'm here just to do what I'm good at, all right, so you're both working with TabStack. Can you tell me about TabStack? For folks who haven't heard of TabStack before, what is it?

****Tessa:** So TabStack is what I think of as like a amazing Swiss Army knife, like in your tool belt, in your agentic world. And you can obviously use it outside of, an agentic system, but TabStack essentially gives you access to the internet.

And I know that sounds silly, but like in the agentic space, right? Claude and ChatGPT and all the frontier models have this beautiful harness that's trained. They know how to access the web. They know how to get data. They know how to cite research calls, right? They know how to go out and do things.

But all these other models that we wanna work with, maybe we don't want the frontiers or maybe they're gonna become \[00:03:00\] unaffordable very soon. I just saw someone get kicked off of a $200 plan on like ChatGPT, and I was like, "Oh, this is weird." So we're all gonna be thinking about we need these other models.

We need models that we control, dive into the open source side of things, right? It's just gonna be the evolution of the ecosystem. And so as you do that, you're gonna have to train those models on how to scrape the web, how to do research calls, how to go do things, how to get things, right? Give them browser infrastructure.

And so TabStack has essentially three very distinct endpoints, but about five different features that allows you to essentially go out and either scrape data make a research call to get a cited, get cited information back on something you're looking for research info on, or send it out to go do a task, right?

"Hey, can you go on the web and fill out this form for me? There's five forms, go grab my data and go do this task and come back." And so that, that's the automate endpoint, and I actually use that one quite a bit. So that's kind of TabStack in a nutshell, of just really being this like beautiful Swiss Army knife to give your agent or your application, if they're working with LLMs, \[00:04:00\] access to the web if they don't have it.

****Mike Bifulco:** I think those are the things that as soon as you start doing things, touching agents and start to dream about, "Hey what can I make this thing do?" It starts to reach out into the web and touch more and more things. But there's a lot of questions about that as a developer type, and there are many things as a...

Gosh, I'm trying to include the voice of the, the newly technical non-developer who is making things, who just have maybe some assumption that "Of course my robot ally can use the web." And there's a whole lot that comes along with that, and I'm eager to ask you a lot about this.

But before I go any further, the thing I wanna say, too, is that when Steve reached out about this interview, he told me "Hey, I have something I wanna talk about," and he gave me the pitch for it, and I basically said, "Say no more. I don't wanna know anything about this until you tell me about the project as we're talking."

And I'm looking up the exact direct quote that he sent to me was "We're working on w- on a product at the moment with Mozilla that is basically API access to the web." And of course, with our squad and API developers, that's those are the keywords I need to hear. What on earth does that mean?

What are we talking about today?

\[00:05:00\] Yeah

****Tessa:** So one thing that I built when I first joined Tapstack is I built out this competitive intelligence tool that essentially is only powered by Tapstack. And so what it does is it goes out and it keeps a radar on every single one of our competitors, and it shows \[00:06:00\] like what's a recent blog, like all their founding information, if their messaging changed, if their jobs board changed, like just finite details.

And so when I started at Tapstock, A, it was my way to learn the API and build with it, but when I joined I was like, "Haha, I've got all my information on my competitors," right? And it's, that's like a tool that a go-to-market person wants right next to them. Then I would say on the contrary end, like we've talked about, I don't know, Steve, d- did we ever build the reverse job board?

We talked about doing a reverse job board.

Yes When you break down the different kind of like endpoints of what you can do really, like the extract endpoint is very JSON driven, and so it's got that schema defined around it. And so when you think about like web scraping in general, you're constantly having to like map to IDs or map to wherever, right?

Or oh, here's the identifier. Where this is like schema based and there's intelligence behind it, and so it can go to any \[00:07:00\] website and you're not gonna have a broken scraper the next time you use it because it's gonna be able to adapt and evolve and figure out what it needs.

****Mike Bifulco:** I think one of the first questions I have is it sounds like there's a handful of things that are the core use cases or maybe like the base endpoints. I've heard scrape and research and automate. What is the balance of those things being deterministic and like an API that will always return the same versus agentic and something that is gonna go kick off a the black box workflow that an LLM would run through?

\[00:08:00\] Sure

****Tessa:** the citations are arguably like, I guess maybe deterministic. Like we were just working with somebody where he was consistently looking for the same type of data, but we were gonna use a research endpoint to go grab that data and then validate via the citations URL to make sure that the data was like, oh yeah, that's exactly what we're looking for each and every time.

But that is definitely a little bit more open-ended on the research endpoint We actually run a, like a subset of a whole bunch of different kinds of evals that happen internally behind the scenes. And so what we're doing is consistently evaluating whether or not people are getting some of those deterministic results, right?

We're not consistently gonna always be the same because we're still surfacing the internet. It's the live internet that it's going out and actually working with, and the research stand-standpoint, it also has a live corpus of data that is \[00:09:00\] also not live, right? And so it can compare both. And so anyways, as we're running those evals, we try to think about those things, right?

What kind of results are we getting, and how do we make sure that the API is performing at peak? Because when you are working with an LLM, it's... You don't know what you're gonna get, right? And so we're still trying to as humans, figure out how to put those little harnesses or those kind of barriers around these LLMs.

And so we feel like internally we've tried really hard to do that.

****Mike Bifulco:** Let's start here then. If I'm signing up t- for Tapstack for the first time, what does "Hello, world" look like?

Ah, cool \[00:10:00\] Right And so like from \[00:11:00\] the jump, you're able to test things out and start using the functionality and

probe around with it?

And so the API part of this then, if it sounds like I can in-invoke these these things programmatically in some sense too tell me about that. Is that tool calls with an MCP in addition to like SDKs? How does that all work?

Hey \[00:12:00\]

****Tessa:** Yep

****Mike Bifulco:** Yeah, that's a workflow I think we're all getting used to as builders of things is like we not very long ago lived in a world where it was do something, it comes back, do something, it comes back. And now our UX being interrupted in that sense is a really interesting case, and it's turns out like far more natural in a lot of ways.

But as a I'm used to telling the computer to go add two numbers and it gives me those numbers back, and then I do the next thing. It's a very different experience. Tessa, I'm curious, as you're approaching this, what does it look like for you? Like what are the types of people that you're identifying as developers who should be taking a look at this or like who have interesting use cases?

How are you identifying and finding the types of people that should be diving in and giving Tab Stack a go?

****Tessa:** So we actually are, like, in the middle of our reposition. If you go to Tapstack today as we're recording this, you're gonna see our old positioning, but if we go-- \[00:13:00\] If you go there the day that this is live, it'll likely be our new positioning. And so we're, like, right in the middle of that pivot, and so actually to speak to that, 'cause I think it, it makes really good content, honestly, to share these testimonials and s- true stories is that we had Tapstack launched as a, essentially like a, a similar to how we're talking about it, right?

But we weren't seeing a ton of actual adoption and retention. And so it was like, okay, what does that mean, right? That means we're not solving the right problem. And yes, we were solving some problems, talked to as many users as we could and all the things, and just started to realize that where Tapstack really shines is where The web is really hard to access, right?

And like I was saying earlier with Claude and ChatGPT, it's easy to access that way, but not so easy to access if you're picking up an open model or doing anything that's non-frontier, right? And so with that reposition, it's been shifting over to you're working with your own models, and that's the A number one like identifier for our ICP, is that they're working in their own models.

And it's not that you can't use Tabstack if you're not working in your own models. I use it every single day in my Hermes agent, and \[00:14:00\] I'm a Claude and Codex and GPT user, right? But it's just that the pain is so annoyingly painful when you're using a local model because you don't realize, like you said, that you don't have access to the internet inside of these very core base level models.

And so that's like the A1 info- identifier, right? Is are you working in that local model? But then it's for the most part building agentic systems. So it's not that, again, you can't use Tabstack and bring it inside of an app and have no, artificial intelligence in there at all.

You absolutely could. Tabstack is all managed, and so the artificial intelligence is all managed inside of that call. So we go make that intelligence call, come back, make sure you get the right result, and feed that back to you. So you could hypothetically use it in any kind of app instance. But again, not what we're looking for.

We're really looking for that dev that's working with those local models, that's bringing in this agentic system. Maybe they're working with an agent, maybe their app is working in this way and they just need access to the web. And they need... Ideally, what I'm thinking is the rest of their stack is \[00:15:00\] probably pretty secure because Tabstack is managed, and so that call happens inside of Tabstack.

It goes out, it reaches out to the LLM, it uses the browsers it needs to, it does what it needs to do, and it comes back and it gives finished output. So you're not dealing with, "Oh, hey, I've got a search API that's gonna go give me a whole list of results, and then I still have to decipher all those results."

It's very much about, "No. Hey, give me this finished output so we can feed it back in." And so Mozilla's stance of being very trust-driven, very privacy by nature really resonates there. And I think with the Mozilla mission, that's really the direction that we're going just because we- For a whole multitude of reasons, but I have this hunch that like these frontier models are gonna get overpriced.

We're gonna get pushed out of them. Some of them will maybe get to use them in work, but in a personal level, we won't have access to them. But also we're just gonna want more freedom. And so I'm just seeing that ecosystem is gonna build up. And so the nice thing is like now I get to go position ourselves in a fairly small total addressable market where we can learn the players, learn the ecosystem, get involved in \[00:16:00\] local meetups, get involved in sort of newsletters, right?

Because the local model space is actually fairly it's fairly young, right? In general, we're seeing some fairly young technology and AI across the board, but I think what's really cool is being able to get into an ecosystem that just so beautifully aligns with Mozilla's like values and what they go after.

So that's a whole long thing, but it is I guess one little TLDR Bo is it's like stupid simple to honestly install and if you're comfortable in any kind of a agent situation, even if you're using Claude and you're a go-to-market person and you don't code, it's the install is so like easy and it's so powerful that it can very well be for other cases.

But I do think that it's gonna be, fairly technical that are working and building in these, these kind of newer ecosystems. So

****Mike Bifulco:** Yeah, it sounds like the ability to wrap an, a existing model with the sticky bits that let it pull things from the internet with a predict- in a predictable way is something that I guess those, like the great big companies are able to do because they can hire, armies of engineers to do that.

But if you're \[00:17:00\] using a smaller model or developing your own, like that surface area isn't necessarily there.

****Tessa:** Yep,

exactly

****Mike Bifulco:** Yeah. Let's talk about the costs a little bit. So you mentioned on signup there's some free credits and whatnot. What is it actually I guess how is it metered?

Like Cost structure look like?

****Tessa:** Yeah. So each of the different calls have a different credit criteria to them. So like for example, a research call is 250 \[00:18:00\] credits. And so for context, when you join, the free tier gets 10,000 credits. So if you do all the math there, you can actually run quite a bit of free calls with that credit balance.

I think extract runs anywhere from 50 to 100, depending on how you're asking for the shape back. Automate I believe is a little bit higher. I wanna say at 350\. Somewhere in that range. And then you get that, those 10,000 free credits, and you get those every single month, so you do get to keep kinda piling on with those free credits.

I think we do actually have a lot of users that are like, "The free credit tier is good for me," 'cause they're just adding it onto their agent, their Hermes or their OpenClaw agent. And it's just like a great additive tool, and they don't use it a ton. They're just making a few research calls every once in a while.

But we do have different tiers, right? And so there's like a $10 sort of personal level, and then we kinda go up from there. Like a $100 level, that's more for okay, yeah, you're making a lot more calls. You're doing things that are more reliable. Like I would say my competitive intel tool, I don't know what my usage is, but I'm definitely the top user of TabStack.

And I think my competitive intel tool runs quite a few calls. So I would say like just thinking about like you're building a full-fledged app, you're probably looking at that kind of $100 \[00:19:00\] range. And then there's a $500 plan for a team that's kinda using it across the board. And I would say that's actually where I'm trying to position us is can we come in and try to actually address teams that are working with local models that all want that kind of web access that's added onto that team model that they have, we shall see though, right? The world tells us when you put marketing into it.

****Mike Bifulco:** Sure

****Tessa:** Yeah.

Marketer's nightmare, honestly. \[00:20:00\] there's a really cool organization inside of Mozilla it's called New Products. And so what New Products is intended to do is to build new products. But the goal of that organization is to actually drive revenue back into Mozilla, the foundation, and the organization as a whole. So for anyone who doesn't know any- that, know about Mozilla it is a non-profit foundation backed organization.

And so Mozilla has been around for a very long time, just stewarding good web, really caring about trust and data privacy. And so they're the builders of Firefox, if you're familiar. And so how Mozilla plays into that is that Tab Stack is actually a product inside of New Products. And so it's just one of the sort of different kinds of bets that we have going right now that we think could potentially drive revenue back to Mozilla.

We shall see, right? I think-- I joke that Tab Stack came a year too \[00:21:00\] late because it would've been perfect to add onto Claude a year ago when it couldn't access the web, right? Or in today's day, it's a year too early. I think that local models are gonna be quite popular a year from now. And so it's a bet that I'm hoping that we can keep making at Mozilla to play into this ecosystem, alongside of a couple other new products that we're working on the same team.

Yeah.

Ooh, our team is actually quite small. So in terms of full-time folks, there's five, six of us now. Six of us. So Steve is on the team part-time, although I feel like once we've got all these products built, Steve is gonna be, like, a full-time thing where we're gonna need someone who's dedicated to this.

And so we are growing the team because we are adding and we're bringing in new tools, and so I think we'll get into a little bit of what we're building here in a second. But we are growing and we're very specifically growing as you can imagine, in sort of the web kind of, side of things.

But also very much on the AI and kind of agentic side and how we can, bring all of that together. And really looking for \[00:22:00\] engineers who I would say have experience in either side of that, right? If you can come in and you're, you've been in AI and ML and really have experience there, there's definitely gonna be a key opportunity I think probably later this year or soon.

And then also on the other side if you've got experience with browsers or if you're alumni from Firefox, actually. If you are a Firefox alum and you hear this, please reach out to our team. Like we-- that's like a target for us is to bring some, some folks back that used to work on kind of original Firefox.

Yeah, super small team, but we bring in really great contractors like Steve and have them for long term so we can kick butt. But small and scrappy in the team size.

Oh, it's so exciting. Okay, so we're working on two, arguably three things. And so I can't give all the details on all the things, \[00:23:00\] and so I'm gonna kinda like allude to a few different things and let folks imagine. But Mozilla is definitely pushing for really being a trusted company in the, in our technical ecosystem.

And so as you think about that details about Tabstack that we didn't kinda get into is just really listening to where we're allowed to be and where we're not allowed to be, and really deeply caring about data privacy. So one thing we didn't say is there's absolutely zero data retention on Tabstack, so we'll keep your calls for 90 days only if we need to support you in some way, shape, or form.

Those are dumped after 90 days. It's a marketer's nightmare because I've gotta take snapshots of results and understand where things came in and then make sure that I'm like, everything is data privacy. I can't even speak to some of the results of my marketing work because I'm like, "I don't know."

The developers don't wanna be f- they don't wanna be, like, identified, so we don't know. And so I think that's really the beautiful thing there. And so thinking about kind of that whole ecosystem and just awesomeness there, right? And we're thinking about sort of agentic systems and on the, the same line as browsers, right?

We're digging \[00:24:00\] into where does the browsers go in the new world and in the agentic world, I should say. And so just thinking about what does that infrastructure look like? What does the browser experience look like? What does kinda all those things look like? How do we actually evaluate these types of systems, right?

Going back to Tabstack and our internal evaluations the whole team, there's a few folks in Firefox and, a part of some other organizations that are working on some really cool evaluation type of stuff. All those things I can say without the details, but one of the things will be launched, I think, later this year, at least getting into a private beta.

So if that is something that interests you, definitely reach out to me, reach out to Steve, or just join Tabstack or w- join our mailing list because you'll get notifications through that channel as well. So exciting stuff.

\[00:25:00\] I have never seen someone write such amazing developer content and I cannot say enough good praises about Steve's content. For me, yeah, if I am TessaK22 pretty much across the whole internet.

So if you're on any platform and you wanna find me that's pretty much it. I'd say LinkedIn and X are where you can probably find me most actively. Yeah, tessacrescel.com if you're into that. I don't blog very much, but there's a few, there's a few blogs

****Mike Bifulco:** And what about Tab Stack?

****Tessa:** So Tabstack's over at tabstack.ai, so T-A-B-S-T-A-C-K.A-I.

That's pretty easy

****Mike Bifulco:** Hey, look, it's been amazing having both of you here. I appreciate you coming through and chatting. Steve MacDougall, Tessa thank you a ton for joining us for APIs You Won't Hate. We'll catch you next time.