3544: Make: No-Code, Automation, and AI agents In One Visual Platform

[00:00:03] Today's conversation is about something many organisations are feeling, but possibly struggling to articulate. Because automation and AI, yep, they're spreading across businesses faster than most teams can keep track of them. But my guest today works with organisations that are automating entire business functions using no-code tools, AI and increasingly AI agents.

[00:00:29] But what I want to talk about today is why visibility and governance are becoming just as important as speed, and why many teams are jumping straight into AI solutions without fully understanding the problem that they're trying to solve. But MakeGrid is a new way to visualise a company's entire automation and AI landscape in real time. And I want to explore why this kind of clarity is becoming essential as businesses scale and keep putting more automation,

[00:00:58] more agents into their tech. That kind of visibility and clarity is essential. And my guest will also share a thoughtful perspective on no-code, anarchy, agent sprawl, executive oversight, and what real agility actually looks like when automation becomes core infrastructure rather than just an experiment or nice to have or the next shiny thing. So if you're trying to move fast without losing control, this conversation will surely resonate.

[00:01:28] Before introducing today's guests, I just want to give a big thank you to my friends at Denodo, who are helping enterprises make sense of the data world. Now, whether you are a CIO, architect or analytics leader, Denodo will help you engage faster and deliver real results. And with their partners, you can also modernise without disruption. So if you're finally ready to make sense of the data world, visit Denodo.com today.

[00:01:58] But enough from me. Let's get my guest on now. So a massive warm welcome to the show. Can you tell everyone listening a little about who you are and what you do? Thanks so much, Neil. It's great to be here. My name is Darren Patterson. I'm the vice president of market strategy at a company called Make.

[00:02:21] So Make, if you're not familiar with it already, is an automation and integration platform that's ideally suited to help companies of all shapes and sizes be able to incorporate AI and increasingly AI agents into their core business processes to ultimately make sure that work is happening when they're not working and also make sure that they're able to continually improve their business to optimise for the right outcomes for their customers as well as their internal efficiencies.

[00:02:52] And not only that, before you join me on the podcast today, I was reading about the launch of MakeGrid, which is the first auto-generated real-time visual map of a business's entire automation and AI landscape, which feels quite timely, if I'm honest with you, because at a time where we just seem to be adding more and more stuff into automation and AI, it's easy to lose track of everything. But tell me more about MakeGrid and where that fits into everything for the business leaders listening. Yeah.

[00:03:21] As you can imagine, a launch like MakeGrid, it's been something we've been working on for several years. So we were either prescient or lucky, one or two, or a little bit of the both. But increasingly, observability and understanding of how different systems and increasingly different AI agents and actors interact together, increasingly that's incredibly important for different types of organisations.

[00:03:45] So we see across many of our Make customer base, we actually see customers automate and integrate literally their entire business, from how they acquire customers to how they market to customers, and of course, ultimately provide those customers with the goods and services. So virtually everything about those businesses is fully automated through a no-code technology stack. And that means it's increasingly important for those customers to understand how everything works together.

[00:04:13] One way I think about this is actually thinking about when you're looking at a core process that's automated in your business, you might be staring at a tree. But sometimes you need to take a step back and understand what the entire forest looks like to make sure that you can optimise it and continue to enhance it in the future. Even in some of our larger customers, it might be an entire business function like marketing or HR, where you're looking at everything from how do you recruit the next great talent coming to your organisation

[00:04:41] to how to make sure that they get onboarded effectively and really up and running. So when you think about these processes, they become like they're critical to how you actually run your business on a day-to-day basis. So understanding how everything connects and how to continue to optimise it, it's been really important for our customers. And I'm going to dig in a little bit deeper on some of the offerings there and how it helps businesses and the value add and all that. But before we do, I think one of the big problems now is we go straight into technology,

[00:05:11] straight into solution without understanding the problem. So tell me a little bit more about why current documentation and monitoring tools are failing, fast-moving teams who are moving so much quicker with so much automation and AI at their fingertips now. So what is the problem here? Yeah, there's an interesting piece here. Maybe it actually starts with who in your teams is actually responsible for managing these processes. So if we think about kind of, I don't know, traditional software development of how companies have run in the past,

[00:05:40] very often the people responsible for automating a process or setting up internal integrations and managing these types of things. In the past, very often that was centralized within a team of IT experts. These are people that went to school and understand all the best practices around documentation and setting up observability and monitoring tools. And that works fantastic for lots of processes.

[00:06:06] But increasingly, some of the world's fastest, most competitive and compelling types of companies are moving towards a less centralized model, where they're actually empowering individuals who maybe didn't go to school and with an information technology background. But they have a strong understanding of their particular business function and maybe some technical skills or operational skills to be able to understand how to most effectively automate and iterate on that particular business function.

[00:06:35] So what that means is that we have people who in the past weren't traditionally creating these robust, deep infrastructures and technology, but they've been able to access and really supercharge their ability to get work done effectively through the use of no-code automation tools like MAKE. So of course, that means that they don't naturally think about all the things that are associated with having a system-critical process up and running 100% of the time.

[00:07:04] So MAKE really plays a significant role in helping them not just automate that process, but actually document it in an incredibly visual sorts of way and provide observability into that process as well. So these are things that don't necessarily come natural to the people that are automating businesses today, but can become very easy for them to be able to access and, of course, leverage that. And I've been to a lot of tech conferences over the last 12 months

[00:07:32] and the talk has all been about automation, agentic AI, launching swarms of agents that are all talking to each other as an ex-IT guy and cyber security guy. Bits of that does make me a little bit nervous because it's done with let's go after this first and worry about security and governance and things later. And I've got to ask, from your point of view here, what are the biggest automation pitfalls that you're seeing out there and how can people listening avoid them? Yeah. I think I've been in many of those conferences too, Neil.

[00:08:03] We can't get through any particular meeting without saying the word AI agent several times. And I think that's one of the pitfalls that we've observed over the last, we'll say 12 to 18 months is very much a pitfall that happened also in the early 2000s as well with some new modern web technology. Essentially, one of the pitfalls is that we see people commonly look at the solution before they understand the problem that they're trying to solve.

[00:08:32] So certainly there is a lot of excitement about the power of AI agents and absolutely that's reasonable and understandable excitement. I'm excited too. But ultimately when people start to think, I need an AI agent, I need an AI agent that kind of are fixated on the AI agent itself as opposed to deeply understanding what are the key opportunities for improvement in our business and then figuring out what are the right tools necessary to deliver on them.

[00:09:00] There was actually some interesting research done recently that identified that when you look at all kind of human tasks that are like sort of like task brokerage type websites, AI agents can only really automate end to end 2.5% of those types of tasks. And in reality, there's a whole set of other automation technologies that actually support that and connect with that, which includes everything from your traditional workflow automation.

[00:09:27] And also a huge percentage of work can get automated effectively by combining traditional workflow automation with AI that exists inside the workflow. So it might not be necessarily agentic. And then of course that it's actually deciding what steps to do, but it's a step within the workflow where you're able to generate content or summarize content or extract key pieces of information. We see that as one of the most beneficial ways. And it's not an AI agent per se, but it helps solve the key problem that people are looking to address.

[00:09:58] Yeah, 100% with you. And I think also many businesses are struggling to keep up with the pace of technological change. And yet, I think in 2026, there's an argument that it will never move this slow again. It's going to keep ramping up. There's going to be more agents out there, hundreds, thousands all acting on our behalf. And on the flip side of this, Vibe code and no code, that's lowering the barrier of entry, allowing businesses to move quicker. But the question I've got to ask you is,

[00:10:26] how do you empower teams to build at speed, but without descending into some kind of no code anarchy that increases risk further down the line? Yeah, absolutely. I mean, we learned a little bit of this when we went through other eras of digital transformation. And the first piece I would identify is that it's, in many ways, your ability to exceptionally adopt AI in your organization is not so much a technology discussion

[00:10:55] as it is a culture discussion and making sure that your team's empowered to incorporate these things within their organization. So we've actually worked closely with lots of large organizations to identify what's the kind of playbook, so to speak, to be able to be successful in empowering your team, helping them understand the technology, making sure that they have access to the right resources to be successful, and figuring out the right models for ongoing management and success.

[00:11:25] One of the things we see very often come up is sort of this distinction between, well, should we centralize these technologies and manage them within a central team of experts, or should we allow everybody to be empowered themselves and be able to take on this technology and do whatever's necessary? It might not be a shock, but I've sort of somewhere in between, which is to say, I think the most effective organizations, they operate what I think what's called a center of excellence, where they have key people that get together

[00:11:54] and they talk about best practices and they ensure sort of the things that need to be standardized are standardized, but at the same time, they're not controlling everybody, dictating what projects to work on and identifying how to work, but instead empowering lots of people to be part of an individual business function and working on their own, but also sharing best practices at the same time. So we see a couple of these approaches that are most effective in ensuring that we don't end up with chaos at the end of the day,

[00:12:22] and it's kind of this carefully controlled in the middle piece. And I think we've highlighted a few problems that will resonate with people listening all around the world. I think it's something that most people have experienced at some stage. So obviously you've released MakeGrid. I think that's a good way of introducing it now and talking about a problem or talking about the solution, sorry, and how that can help balance autonomy and oversight, particularly with AI-powered automation only on the inquiry.

[00:12:51] So tell me a bit more about how MakeGrid addresses many of these problems that we've just talked about. Yeah. Yeah, it's an interesting piece because one of the most powerful and unique capabilities of MakeGrid that will be immediately recognizable is it's an incredibly visual approach. And of course, today we're talking on a podcast. And so your listeners are going to have to close your eyes and imagine the most beautiful interface you've ever seen. But this automatically generated interface

[00:13:18] shows you all the different automations that you have set up in your business. It shows you the relationships between these automations so I can understand which automations are relying upon other automations and how data ultimately flows. But also, and this is very important, because we understand your automation landscape, we also know key things about your technology landscape. So we know, for example, that you have a key asset inside of Airtable, basically a base inside of Airtable

[00:13:47] or Monday.com or NetSuite or Workday. We actually know a lot of information about your broader technology staff. So you can think of this as a map of your business or if you were to see your business on in the same way that you look at Google Earth and look at a particular city or a town. This is what MakeGrid represents. And on top of that grid, you have lots of different views and ways to look at data. So you not only know what are the key technology assets that I'm dependent upon

[00:14:17] and even specific cases, like bases and sheets within there that I'm dependent upon, but I can see in which direction data flows. Is it pulling from there or pushing from there? And I can identify all the different relationships. And increasingly, that becomes super important when you think about AI agents. Which systems do they have access to? Which systems do they actually call and send data to and pull data from? And be able to map that out in a visual way is a pretty innovative, unique technology on the market

[00:14:47] that's going to help people increase their level of comfort for adopting these new technologies that are doing incredible things on a regular basis. I just love this idea of an auto-generated, almost real-time visual map of a business's entire automation and AI landscape. I think for decades, I've known businesses struggle with APIs, for example, and what's talking to, where the information is going. Identifying all those different things that we take for granted has been notoriously difficult.

[00:15:15] But then throw AI into the mix. Are you speaking to a lot of businesses that are starting to feel the pain of this and knowing everything that is in their landscape? Yeah, that's definitely the case. And what's interesting to me is it's absolutely true if I go talk to an IT leader. You can imagine that they're like, man, I don't know. I'm nervous about everybody deploying AI agents and I don't know what they're doing and who they're talking to and everything else. So you can definitely imagine it from there. But even when I talk to leaders in the business, when I go talk to a marketing operations leader

[00:15:45] or somebody in a customer service team, they increasingly see the importance of being able to understand and manage this. It only takes you about to that second AI agent where you start to ask yourself these questions. You say, okay, wow, this is super cool. But what happens if... And the next layer, of course, is not just many AI agents talking to different systems and pulling data from different systems, but then you increasingly come up with this,

[00:16:12] we'll say the social network of AI agents when they begin to communicate with each other, either in pre-designed patterns or even emergent patterns where AI agents can actually discover each other and begin to communicate on subtasks for each other. A quick thank you to the sponsor that supports every podcast across the Tech Talks network and every episode. Because their help allows me to publish 60 interviews a month with founders and technologists who are keeping this industry moving. And this month,

[00:16:42] I'm partnering with Alcor. And if you've ever tried to hire engineers in another country, you probably know just how painful it can be. Different laws, patchy support, and partners who don't truly understand engineering roles. So Alcor approaches this from a different tech point of view. They specialize in Eastern Europe and Latin America, and they're able to combine EOR capabilities with recruiting. So you get one partner handling everything.

[00:17:11] And they help you choose the best location for your stack, find developers with the right depth of experience, and run proper assessments so they can onboard people quickly. And they also give you a model that respects both transparency and margin. Most of your spend goes directly to your engineers, and the fee will decrease as the team expands. And you can even transition everyone in-house at that time when you're ready without having to worry about a penalty. And that structure is why

[00:17:41] a mix of early stage and unicorn stage companies use them as they scale. So if you want to take a look, visit alcor.com slash podcast or tap on the link in the show notes. But now, on with today's show. And assuming then for the IT teams, they've got this real-time visual map of a business's entire automation and AI tech stack there, they're happy. Then for the C-suite that are listening and have got this tool, they know their IT teams have got all the information they need. How does it ultimately help

[00:18:11] fast-scaling businesses stay agile whilst also maintaining full control and visibility over workflows and start demonstrating that ROI that has been difficult to prove over the last 12 months? Yeah. I love that you used the word agile. I think that's exactly the word that I talk to customers about all the time. Yeah. And the reason I emphasize that is because often there's this kind of mental model that when I automate a process

[00:18:40] or even if I take an AI agent and apply it to a process, at that point in time, often people think, well, that's going to be a set it and forget it moment. Like as soon as I automate it, now I can move on and do other things. And what we see among some of the most successful companies in the world is they don't think of it as set it and forget it. They think of it as business agility and their ability to respond very quickly to competitive pressure changes, to changes in their supply chain,

[00:19:10] which certainly happened over the last year, and changes to what their customers demand and expect. And so increasingly, they think about automation, not as set it and forget it, but as the ability to fine tune a process in order to continually improve the kind of top level results of a company. And for those executives out there, regardless of the size of organization, what was really interesting to me is I've actually seen within several of our customers

[00:19:37] is that they use a very visual tool like Make and MakeGrid in order to help an executive understand how their business really works and operates. You think about what a typical executive is thinking about at the very highest level. They spend a lot of time thinking about, you know, what's my core product and are we investing in the right things in R&D. They spend a lot of time thinking about people. Do I have the right people on the team and are we investing in the right skills?

[00:20:06] And most executives don't get enough time spent on thinking about how their business actually runs on a day-to-day basis. How are these systems connected and how does a process of a customer onboarding actually work? And something like MakeGrid enables them to actually tap into that type of information and begin to understand it so that they can do what's most important for executives is ask the right questions. Love that. And as 2025 slowly fades away

[00:20:36] in the distance of our rear view mirror, we're looking at all things 2026. Is there any tech trends that excite you? Anything that you're going to be keeping a close eye on or anything that you're going to be doing there at Make that you can leave us on a few teasers with? What's next year mean to you? Yeah, I'd be happy to. As we look at sort of the, I'll start with the tech side and wrap up with what we have coming from Make and some kind of the broader trends. But one of the things

[00:21:05] I'm most excited about, if you follow sort of the AI agent world and those types of landscapes, in 2025, there was introduced a new concept called MCP or the Model Context Protocol. There's three little letters got lots of people very excited. And in truth, this protocol, which helps make it easier for AI to talk to different systems and interact with those different systems. In 2025, it's pretty immature or early technology in terms of its real capability

[00:21:35] and being secure and managed and accessible. So I'm very much looking forward to 2026 as the year in which MCP becomes a much more mature technology, broadly adopted and accepted among vendors as a good way of interacting with different systems. But being able to be able to manage and control and provide precision to how different AI agents interact with different MCP applications. That will be something that I'll be looking for as well. I also hinted towards

[00:22:04] my excitement about the future and we'll see to what extent it becomes a reality in 2026 is when we really start to see actual multi-agent patterns emerge. So certainly people have experimented with this now where you have an AI agent that has a broad goal and it can work with what you might think of as like sub-agents to break down tasks into smaller things. But I think we're about to see over the next couple of years emerging patterns of AI agents being organized in much the same way

[00:22:34] you might organize your employee org chart. So how do you think about agents that are able to self-organize and self-communicate in order to accomplish a broader task for your company? Those are big technology trends and certainly some excitement around them. At Make, I'm specifically very interested in a couple of key things. Number one is that we expect to continue to invest in AI agents to make them

[00:23:04] as transparent and observable as possible. And it sounds a little bit crazy but to actually be able to see an AI agent think and reason through different options. That not only helps me build and test out agents more effectively but when I'm looking back towards what happened in the past I can understand what decisions an AI agent made, what tools it called and do this in an incredible visual way. So I'm looking forward to the next iteration of AI agents in Make. I'm also looking forward

[00:23:34] to a fantastic release we talked about a little bit at our last customer event and this release will be coming to fruition in the next few months which is a product and capability called Maya by Make. Maya is essentially a built-in assistant that enables you to create and manage and interact with all of your automations and of course eventually your automation landscape using natural text. So you mentioned Neil

[00:24:04] Vibe coding earlier. Yeah. To what extent you spend your weekends on Vibe coding. But the magic of Vibe coding is that it moves away from this one-shot prompt kind of perspective that a lot of people experimented with where you might, for example, describe a business problem and it spits out an automation. But what we're looking for here and very excited about Maya is it's interactivity where it's going to ask you clarifying questions as opposed to making assumptions.

[00:24:34] It'll help step you through the process of setting up connections and different resources and continually iterate with you on building out your automation landscape as an assistant. This is something we've been invested in for a long time and we want to get it right. And so we're very excited to bring that to our customers. That does two things. Number one, it lowers the bar for people and their technical experience necessary to be successful. But number two, even for very technically talented individuals, it makes them faster, more

[00:25:04] effective, and feel even more powerful than they did before. Wow, there was more than a few teasers there. I think we're going to have to get you back on later next year. And I completely agree with you about MCP as well, especially because it's joined the Linux Foundation recently. A lot of question marks over what that is going to mean for developers and businesses building the next era of AI tools and agents, etc. So there's going to be lots to talk about in 2026. There's an open invite for you to come and join me again. But before I do

[00:25:34] let you go, where's the best place for people to connect with you, your team, or keep up to speed with some of those announcements that are going to be coming out next year? Amazing. I'll definitely take you up on that offer to join you again. But certainly the primary place where you can go and learn more about Make would be simply at make.com. So that should be pretty easy to remember. But I'll also identify a couple other resources. One, if you're thinking about, particularly at an executive level, if you're thinking about how to

[00:26:03] transform your organization to be an AI-first organization, I would direct you to playbook.make.com where we've really invested heavily in helping put together the right assessment to help you understand your current AI maturity level, as well as the right steps in the very specific playbook to become more mature. That's a fantastic resource I definitely recommend people taking a look at. And last but not least, myself personally, again, Darren Patterson. I'd love to connect

[00:26:32] with people on LinkedIn. The closer I can stay to people that are tackling real world problems, the better off I can be in helping understand what the future holds and certainly maybe even providing advice from time to time that people might find insightful. Love that. I'll have links to absolutely everything. If I can find a video that can show people what this real-time visual map of a business's entire automation and AI landscape looks like, I will post that as well because, as you said, this is an audio

[00:27:02] podcast but it is something to see. So I'll add links to everything there and I do invite everyone listening, share your experiences and we'll get you on here too. But more than anything, thank you for starting this conversation today and I look forward to speaking with you again in a few months. Likewise. It was a pleasure. Thank you so much, Neil. I really enjoyed that conversation with Darren today because I think it tackled the tension that many leaders are wrestling with right now. How do you empower

[00:27:31] teams to move faster with automation and AI without creating risk, chaos or blind spots that will come back to bite you later? And what particularly stood out to me was this idea that automation is not something that you just set and forget and the most effective organisations will treat it as a living system. One that needs visibility, iteration and shared understanding across technical teams, business leaders and of course the C-suite. So if you want to

[00:28:00] learn more about Make, MakeGrid or anything we talked about today you'll find links in the show note at the blog post over at Tech Talks Network and Tech Blog Writer. I will also add a video so you can see exactly what this looks like. And as always I'd love to hear your perspective. Are you feeling confident about what is running inside your automation and your AI stack today? Or if you're completely honest are there still parts of your business you cannot quite see or know what it does? Well let me know

[00:28:30] your thoughts as always and I will speak with you all again on the next episode of Tech Talks Daily. Speak with you then. Bye for now.