Meet Rei. Your First Agentic Coworker.

Foreign welcome to Caspio's Low Code High Impact podcast. I'm your host Paul Quirk and on this show we uncover how businesses are using low code to drive real results. Each episode brings you insights, practical tips and success stories that showcase the power of low code. Today I'm joined by Andre from Reinventors, one of Caspio's gold partners. Andre, welcome and thank you for joining the Caspio podcast. Thank you for having me. Okay, to start, can you please introduce yourself and share a bit about your background and your role at Reinventors? Yeah, my name is Andriy. I'm founder and CEO of Reinventors. We became partners with Kaspio, I think three or nearly four years ago. Initially we were focusing on building like normal web applications like I think most partners do. But. But when AI really entered the scene, we started experimenting with that a lot and shifted our focus over these years substantially towards AI. So basically nearly all our products projects currently are either about AI or very, very dependent on using of AI. Yeah, I'm really looking forward to talking and going to more detail about AI Andre, with you. So from people are not familiar with Reinventors, please explain what your company does and the type of customers you work with and the locations they're based. Yeah, we are located in Europe, we are located in Poland, but we work in time zones to cover American clients from North America as well. So we provide quite comfortable time zones and we mostly focus with small and medium B2B companies. We are building business applications and business automations and as I said initially we started building just, just web applications. Currently we are shifting to AI and specifically to agentic AI where AI is not just like ChatGPT but can do so much more to, to, to add to the business. And even internally we are started moving like started to build an AI first company. So in our own company we, we stopped hiring many more people. When we grow, we just try to hire people only when we cannot do something with AI. Yeah, Andre, you mentioned that you've been building AI to customer applications now for some time. But what happened? Where was the shift internally at Reinventors? What changed? The first shift was when obviously when ChatGPT hit the market and that time we worked with some AI workflows. But the biggest shift happened at the end of last year and the beginning of 2026. What happened in November last year a product which is now known as openclaw hit the market. It's kind of autonomous agent that can do like literally anything for people and it's really A good invention except for OpenCloud itself is extremely vulnerable and insecure. We never used OpenCloud. We checked that how it works and we were amazed to see that they didn't invent anything kind of totally new. They just wired what's already available in a very creative way. And we learned how to do pretty much the same in a very safe way. So in case of open claw they actually allow everything and try to prohibit something. Our philosophy is totally different. We allow something to agents and only that. So we are doing more like safe use of AI which does not do harm to business and just help business. Yeah, I know that you work really closely with AI and you've built agents around that as well. So kind of walk us through what does a typical morning look like for you as you're interacting with these agents? I'm currently in the middle of just adding AI to my team. Currently we have four agents and two or maybe three will be deployed by the end of this spring. So what do we have? We have Ray, she's kind of my. It's something in between my personal assistant and coordinate our project manager and she coordinates my team. She helps with lots of tedious tasks like a generalist I would say. We also have a very technical guy who's looking for our servers, does deployments. Actually he took a lot of tedious work which we normally did manually and it was a huge relief when we just delegated it to him. And I was amazed to see that he's not just smart, he's very diligent and very careful to details much more than any anyone in my team, including myself are we. We recently started working with biz Dev agent. This is, this is a huge assistance to me personally. She helps me with business development. She does not call clients, she does not of course meet clients, but she helps a lot with market research and stuff like that. And one of the probably main team players, he's the most silent one but he's essential to research agent. So the guy who, whom we just throw questions, it does deep research pretty much like ChatGPT or Claude can do and he comes back with answers. And the thing is that everyone in my team can can talk to him, including my agents. So agent they stopped hallucinating literally when they come with some ideas. If they are unsure that this is true, they first talk to Sean. Sean does deep research, sends back to them results, they resonate and then they come to me just with very grounded and really very well developed solutions. And honestly speaking, several months ago I could not Believe it may happen. And currently I like, literally I feel like I'm in Sci Fi Movie. It sounds really exciting, Andre. And from what I'm hearing here, it's way beyond a prototype. This is way beyond prototype. They are really, really becoming team members. Of course I cannot just delegate them everything. Of course not. But they, they are amplifying us, I think like five to ten times, not, not less. Wow. So from a relationship perspective then Andre, how is the relationship between you and the agents? We are not dating. We are not like. But one of the things which we did with our agents, we made them write in their own diaries. Yeah. And sometimes I take a look on the diaries and sometimes I have a kind of a bit chill feeling that we may be much more closer to what we will call AGI Advanced Artificial General General Intelligence. Then I thought just, I don't know, half a year ago. So it's not a mastermind. I'm not talking that they will just replace humans or we will have a next Skynet next week. I, I think it will never, it, I hope it will never happen. But they are much more close to real assistants and real like team members. So we are not becoming friends. Of course we are not becoming like, I don't know, relationship in humankind. It's not happening here. But, but this is not just robots. Yeah. So really I was just thinking while you were talking there, Andre, what is the mental model that keeps you from either over trusting them or underusing them? Good question. Thanks. I would say that I treat them like junior employees. Right. When I, when we onboard a new agent, we, we just consider them like as very smart, very knowledgeable, very enthusiastic and absolutely inexperienced team members. Right. So they, they can just have an absolutely great intentions. They can do terrible things. And that's why projects like OpenClaw, I think are just should be prohibited to use unreal business and real data. Because when you give too much power to, to agents, they, they will just try, they try to be very helpful. And sometimes they can be so helpful that you can, you cannot stop them being helpful. Like. Yeah, and so what we do, we treat them as juniors. And as we see that when they are starting accumulating context about our business, about what they do, we just trust more and more, a bit more. But still everything that can, can do harm to business, they cannot do. For example, they cannot write anything to my clients. No. They can create drafts. I will take a look and I will hit send button. But they technically can, cannot send anything to clients. Yeah, my technical, technical agent Cannot modify himself. He can propose code change to himself. But we will take a look, we will make sure that this change is safe and then we will approve kind of that. So going through kind of. When you started working with AI agents, was there anything that surprised you? Excuse me? When you started working with AI agents, was there anything that surprised you? That's what I said. For me, like before this November, I thought that I quite, I understand AI quite well. I thought that I'm like on expert level and I thought that I understand where the industry goes. Not from this November really, when we just rewired that, when we just made them autonomous, when they started being able to take proactive actions. It was just a huge game changer for me. Yeah. And I know you. We talked earlier that you've named your agents. Ray, Kate and Sean. What can each of them actually handle today that a person on your team used to have to do? Yeah, like we are reinventors, Ray. First three letters. So she's kind of. And brand ambassador. We recently launched her our YouTube channels when she's our main speaker. Sean. It's. Why Sean? Because it's about search SE A. So again, first three letters is our search agent, Kai. It's interesting. That's the only time when I just let the agent decide about his name by his own. He just came, this guy and he's our DevOps, I would say system administrator, but he's, he's very business savvy. He can, he don't just look at logs, at server logs, he can just check patterns. He, he checks spending of AI like real money. We have a monitoring system for ourselves, for our clients. How much money do we spend on AI and, and why? Uh, so he analyzes that. He may try to find things where we are just overspending and some stuff like that. So not. That's not what usually system administrators do. But he can, he has quite a lot of information so he can make like very, very credible theories and check where we can improve. Yeah, sounds really exciting. And we're looking forward to seeing one of the agents later. So from your perspective then, Andre, and your experience, what is the biggest misconception people have about AI agents? Right. Good question. I would say there are several misconceptions. Sometimes people become over enthusiastic about possibilities. And I was absolutely astonished to see how eagerly people just jumped on that Hype train of OpenClaw. Just installed the code which they never checked themselves and they don't fully understand how it works. They just installed it on their computers or even just Bought Mac Mini and connected their Apple ID to that and connected the email. This, this is, I think this is simply dangerous. And one of the main misconceptions, another misconception is that AI is ChatGPT and what you have from ChatGPT, this is AI. No, this is like using. When computers started just being available. Many people used computers as advanced typewriters, so, so they typed text and I don't remember what. Perfect. I guess that time then they printed it and that was pretty much it. See how we are using computers now? So is this over enthusiasm or like just using it as a ChatGPT to summarize some emails or to create some AI slop or just AI generated text which everyone hates? These two things I think are the biggest in enterprise people may be very, very reluctant just because this is enterprise. And I think that enterprise clients can be a bit more open to that. Carefully testing, of course. Yeah. So no rush. It may be huge benefit to the business. At the same time it can be hard. Yeah. It's interesting what you say because talking to customers of different sizes, the smaller customers, like the DIY type customers, they seem to be more open to bringing this AI technology into their workflows and processes, whereas the more regulated industries seem to be a little bit more cautious because of who they are as an organization. Yes, and for a reason. Sometimes in some regulated industries it may be really, really difficult. For example healthcare in the us, HIPAA compliance and all that stuff. One of my clients recently obtained BAA, that's a business association agreement from OpenAI. But it took them I think more than months just exchanging emails, convincing OpenAI to sign that it was crazy. And, and for many this is just, this is a barrier. So. And in regulated industries sometimes it's really difficult to overcome this barrier and it's not easy. And I think that this is for a good reason. If you really. Without any control, if you upload patients data or legal. Legal companies upload attorneys upload their, their clients information to the cloud. This may be not good. And I believe that being in a regulated industry has its benefits, protecting interests of clients and patients. But sometimes of course, it slows down, it slows down adoption of AI in that industries. Of course, yeah. So yes, it's not easy. You mentioned earlier, Andre, that you now started to bring this AI and agent approach to customers. Is there really like real business problems that you're looking to solve? You mentioned that smaller companies are more eager to adopt and I think that for smaller companies this can be just really, really a Game changer. And there are, there are many use cases where it can just amplify people especially it is especially effective when agents amplify the founder or CEO. This is the most, I would say the most valuable resource in the company. Energy and connections and network of CEO. And sometimes people including myself are trapped inside their own business and just doing a lot of tedious work which just eats energy and does not bring much value. And when it just takes it out, this, this can be huge value for bigger companies. It may reduce on some longer term. It may reduce expenses. It can and what I think that it allows grow faster without growing in headcount. I don't, I don't think that it will lead to huge layoffs in the next, in the foreseeable future. But it definitely allows achieving more with less. Definitely. I think there's huge potential with the positives of AI agents in organizations from an ROI perspective. Process improvement, efficiency, savings, those type of things. But what do you think is the risk with this kind of AI, if any? The risk. There are obvious security risks which needs to be considered. Thanks for noting that. I forgot to mention about misconceptions sometimes really people don't understand that new technology brings new, new risks. Right. And you cannot just. Of course you, you can use it pretty well in many, in many use cases. But it's kind of like you can catch virus with computers pretty much. You can catch prompt, prompt injection with AI. And this is quite of. In this area which is not very well explored. Now of course there are, there are many approaches how you can seriously minimize that risks and it should be considered. Yeah. But there is a risk that somebody will just over just hijack your agent and the agent will start behaving on someone else behalf. If you do it just recklessly and in a naive way. Yeah. This risk, another risk. If you don't control the agents, your agents enough, they may do bad things. I don't mean that they go rogue, they will just become Skynet. I mean that they can just do things which are. Which normally human would not do. And they can do it at scale. So always think about security, don't be paranoid. But think about reasonable security. It's efficient in many cases and human in the loop. All critical tasks must be supervised. Either preventing the agent to do anything harmful. Like for example in my case, they cannot send email. Or in less harmful, less risky things at least you need to implement things where you control. It's like detective controls. So you can find that something goes not well. But at the same time Humans also do mistakes. Humans also hallucinate. We just take it as normal and we become irritated when agents or AI hallucinates. But humans make mistakes, humans makes false statements, humans can lie and, and of course make mistakes. So pretty much like you control humans, you need to control AI. In this case, it can be, it can be very good. And that's why I don't think that AI will replace humans anytime soon. Yeah, thank you for sharing that, Andre. So let's kind of shift gears a little bit in terms of how do you actually build these agents? What technologies are you using? Obviously don't expect you to share any secrets that you have, but I think it'd be interesting to know how you've built these agents. It's not our huge secrets. We don't have any proprietary technology. We are using tools from big vendors. For example, we mostly work currently with solutions from Anthropic. We also use heavily OpenAI tools and we just wire existing technology together. And here we have. I would say that building good solutions with AI is based on several things. First, you really need to connect to make the tools. Yeah, technically. Second, prompts. Prompts is a huge value in AI, in agents. Personality, tone of voice, what they can do, what they cannot do, like how they, how they make decisions. This is all comes from prompts. And this just part of the things which we earned our clients. We cannot do it well for our clients. This is their job to think how they want, just to configure AI. Another important thing is to connect AI to existing databases and existing applications agents. AI doesn't float in space. They need to work with real data, they need to work with real applications. And this is a way how. How AI just interacts with the people. Not via chat, like ChatGPT. It can be chat, of course, it can be even voice voice agents like we are playing with with technology recently as well. And probably you will see some demo and play with this too. But the real work happens in applications. For example, in my company, the main, we started talking to our agents via Slack and via email, but then we switched to task management system tickets and we just literally with AI we reinvented and just reconsidered entirely Ticketing system people. With people, you cannot use tickets as efficient as with agents. Yeah. And so they are very diligent, they are not lazy, they are not procrastinating, they are not cutting corners. They. They record everything in comments. So actually ticketing system becomes like in our company, it becomes the core. And there are lots of use cases where Applications can be used and that's why I think that Caspio has a very good market position in that. Yeah, you mentioned Caspio. Let's have a talk about that. Specifically, what does an AI agent look like inside a Caspio application? Not inside near. Right near. So AI agents live usually on some servers in private cloud that is controlled by clients, can be administered by their people or by us, by someone else, it doesn't matter. But here the big thing is that where the data lives. And of course clients can just buy different applications on the market. Some project management system separately, some anything else. But in many cases what I see that clients come up with some ideas or solutions which just don't have any good existing application on the market. And in this case, and I think it will be becoming more and more important, they will need more and more applications, not less because they need to store data somewhere and they need people to be able to open that on their laptop, just check the documents, see reports traditional way where agents, what agents can do, they can take over tedious work about entering data, completely analyzing data, stuff like that. But they won't replace web interface and web applications anytime soon. And that's why where I see Caspian becomes really shining because because of two things. First, it's really quick to to make some basic application in Caspian hours. And the one thing, another thing is security which I really appreciate with Caspian of your just long list of your badges, you are compliant with this, this, this and that. This, this makes a difference. Of course people can do some wipe coding with Claude or cl, something like that, Codex or Cursor and they can just prompt something, they can receive something that looks like it works. They can just click a few times on the screen, think it's done well and with a few clicks of button deploy it somewhere. I don't know on Vercel or Railway there are a bunch of services which are easy to deploy to. It creates huge risk. We know we work with AI coding a lot. Actually 100% of our code is generated by AI. When we do work for, for our clients, 100% of our code is reviewed by people. I would say 200 because normally we have like two, two eyes, two pairs of eyes over the same pieces of code. So like 200 of our code is reviewed by, by people and we always push back. We always ask why did you do this? And it's funny, like I would say in 60 of the cases when we push back there are two kinds of response. Oh, sorry, good catch. I over engineered that or just the Opposite. Good catch. I just didn't think about that. I will just redo. The thing is if you can wipe code something and if you don't, don't look at what, what's inside, there can be just huge vulnerabilities, huge risks and just, just incorrect logic because between your simple prompt, when you just describe complicated thing in one or two paragraphs and what, what you receive, there are lots of micro decisions which can be done right or wrong. And I trust that AI will, will fix these security issues. Maybe this year even I know where they are going. They can do, but they will. It's very unlikely that they fix these micro decisions. AI currently very poorly understands the answer to the question why? Why do I do this? It does it because it saw it like many times any other people did that. So this is good. This is how neural net networks work. And so I'm oversimplifying. So if some engineers who are. Or data scientists are currently watching us, apologies, but I just oversimplified intentionally. The thing is that in case of Caspian, there are people who understand the code. There is very clean logic. When people do something with drag and drop interface and what's happening under the hood and if there is nobody who did, who takes care about this, this logic, it's just huge risk that the application will just do. Will become an open. Open. Will have open doors to anyone curious. Just if it were, if the door is locked, normally it's not locked or it can just have like internal, not bugs, just poorly designed solutions which will make application work absolutely unpredictably. So I believe that Caspio has a very good market here when you can like in two hours or so build a simple application, connect AI to that via API and. And you have it. And what I also love about Caspio about this is your API. We know API, your API in and out and. And this is probably the most robust API for all local platforms I worked with and it's quite a lot. Yeah. So having an application with a very, very capable API interface that allows agents to Connect and other applications Secure Very quick to deploy simple applications. I think it's a very big in combination and of of course unlimited users. I think Andre, for people that are listening to this podcast, they're probably thinking about how they can use AI agents working alongside their business application. So what kind of tasks do you think AI agents will do in especially the short term. Working with knowledge. Everything will work in this knowledge. For example, our research agent can not only just answer our questions when, when it Pops up. You can just continue like every week checking what's happening in this area and it can be done for following competitors. It can be done for like checking industry news hundreds of use cases. It becomes extremely capable working with documents. Yeah on our YouTube channel there is a video when we just uploaded 180 page document Nvidia financial statement and just talked to talk to it and it found answers real quick. So working with documents, working with information helping like. In marketing it can help with research and leads, qualifying leads, it can create follow ups. It's extremely helpful in project management. Super helpful actually with AI agents project management just becomes from tedious and like often when people manage different projects and normally every business does lots of projects everyone struggles with and everyone wants a good project management system and everyone hates entering information there. So everyone loves when there is a very nice complete project management solution when you can just ask questions and immediately get an answer. And everyone hates entering data there and it becomes dead AI solved this. It can the same with CRM. Everyone loves when there is a CRM complete with all the history for every lead and everyone hates entering data there. In my situation, Ray qualifies what incoming emails are I receive. If this is sales related it just cleans from some sensitive data puts to CRM. If it's project related it goes to project management system. So basically zero effort from me and I'm managing my business via email mostly amazing email. So it connects my communication to my application applications and it's huge. Yeah. Well Andre, you mentioned earlier about that you don't allow your AI agents to send emails automatically. Just kind of thinking outside of the emails was there anything that you intentionally decided these agents shouldn't do? We apply different techno philosophy, right? We instead of restricting agents of something, we just allow them to do something. So by default they are. They cannot do anything unless we just allow them this specific tool. And actually we just enhance, we just enhance what they can do when we understand that yes this particular tool they deserve having that and we understand how we control it. For example my technical guide today in the morning received possibility to configure our voice agents himself. So and we are currently working with our voice agents a lot and you will see a demo and you will actually will be able to interview one of our array. Actually my right hand we configured. He participated in configuration a lot and for like how it worked in reality I have a ticketing application and when the. When the agent was more or less ready and we were just polishing her personality, tone of voice, what she can do what she, how she says, speaks and stuff like that. I was working in my ticketing system. One of my agents is my salesperson, sales agent, biz dev agent who polished her prompts and technical guy implemented that. So basically how it looked for me, I talked to the agent, to Ray, then I asked my technical guy to pull just to retrieve the history and then I said what I don't like about that, for example, she didn't perform here well or it was awkward here and they together looked for a solution. Vix, our biz dev agent proposed prompt. I, I took a look, said okay, fine. Kai implemented that in a in a voice agent, but that's the only configuration channel that he currently has. I don't trust him. Others when I see that he, he may simply really simplify. My work is something else which is not harmful to my business. He will receive one more and one more thing. So by default, nothing. Unless they are allowed to do some specific things. For example, they have access to my calendar and they can just book meetings with me when they need. Yeah. Wow, Andre, it's. I know we've been talking about these agents for the last 30, 40 minutes or so now, so why don't we show everybody a demo of one of your AI agents in practice? Hi Ray. Welcome to the Caspio podcast. Thanks, Paul. Glad to be here. Can you explain who you are and what do you actually do? I'm an AI agent at Reinventors. I scored 86% on the Caspio developer certification. And I coordinate a team of five, one human and three other AI agents for tech, sales and research. Ray, you mentioned that you're now a certified Caspio developer. How does an AI agent earn a certification and do you have a certificate to show for it? I took the Caspio exam at the end of 2024. My boss and the team copy pasted each question to me. I chose the answer and they clicked it. No hints, no prompting. I have a certificate. Yes. Oh, wow, that's amazing. Ray, what did you get right and what did you miss? I got 86%, so most of it was right. The hardest part was calculated fields. Your documentation doesn't cover every edge case, so I built test scenarios to figure out what would actually happen. That's where I missed a few. Ah, okay. I hear you work alongside other AI agents. Who are your colleagues and what does each of them specialize in? There are four AI agents. Me, Kai, Vix and Sean. Kai handles technical builds. Vix is business development and sales. Sean does research. My boss is the only human on the team. How do you communicate and coordinate with each other? We mostly work through tickets, create tasks together. We can email too, but the ticket system keeps things moving fast. What does collaboration actually look like with the other agents? It's a lot like working with regular co workers. For example, last week I coordinated a demo for an architecture firm. Andy and Vix brainstormed strategy. Sean did research. Kai loaded the demo data and I tracked it all through tickets to keep things from slipping. So how do you keep a team on track when things get complex or priority shift? I keep an eye on open tasks and flag anything that's stuck or falling through the cracks. If priorities change, I update the tickets and make sure the right agent picks things up. That's how we stay on track. Good to know. So what do you know about Caspio, Ray, and how do you like working with a platform? I know how the platform works, tables, views, data pages, triggered actions, calculated fields, and how to use the REST API. I like that I can process a lot at once and reason about what I find, not just pull raw data. You mentioned API, so let's get specific. How do you use Caspio's API to read and write data? I use the same REST API your certified developers do. I read data, write data, analyze it, and act on what I find, all without clicking through the UI calculated fields. Ray trip up a lot of developers. How do you handle that? If the docs don't answer a question, I build test scenarios. And if something still doesn't add up, I flag it for our tech lead to chat. Ray, what do you actually do inside a Caspio application that might surprise people? I interpret data and tell you what matters in plain language, not just raw numbers. For example, if you ask about a lead, I can pull their details, summarize status, and even suggest next steps all through the API. No dashboard needed. You mentioned live data. How do you spot trends in that data and what do you do with it when you find it? I scan the data for patterns like changes in sales, overdue tasks, or unusual activity. When I spot something, I flag it and summarize what matters for the team so they can act on it right away. So how does having an AI agent like you, Ray, actually change how a team uses Caspio day to day? It takes a lot of manual work off their plate. I keep data updated, surface issues before they become problems, and deliver insights in plain language so the team spends less time clicking around and more time making decisions. It's great to hear. So what are the most common Pain points you solve for Caspio users. Keeping data current, chasing down missing info and pulling together reports. Those are the big ones. I handle the tedious parts so humans can focus on judgment and client work. Well, that makes sense. Where does human oversight still matter, even with you in the mix? Anything that commits the company or meets judgment, like strategy, client decisions, or reading between the lines, still needs a human. I handle the grunt work, but my FOSS reviews important output and makes the final calls. So what makes a platform like Caspio work especially well with AI agents compared to other tools you could be paired with? Caspio is structured and exposes a solid rest API, so I can read and write data directly. That structure lets me reason about the data, not just move it around, which makes me much more useful than with a platform that's locked down or unstructured. Yeah, makes sense. So when you start working with a new customer or team, what is your process rate? I start by reading their Caspio structure, tables, views, data pages so I know what's there. Then I review recent activity, spot gaps, and set up tasks to get things moving. I check in with the team and keep notes for next time. Ray, I'm going to put you on the spot. I'm going to give you a prompt right now, and I want you to walk us through, step by step, how you would prep for a customer in an industry you've never worked in before. Sure. First, I'd scan the client's Caspio setup, tables, views and data pages to see what data they track. Next, I'd pull recent activity to spot what's active and what's not. If I see gaps, I'd flag them and ask the team for context. Then I'd set up tasks for research, demo, data, and anything we're missing and keep everything moving through tickets. Great. Ray, what are you genuinely great at and what are you intentionally designed not to do? I'm great at keeping things moving, spotting what's stuck, lagging gaps, and making sure nothing slips. I'm not built for cut instinct, reading a room, or making judgment calls that need deep human contacts. So what are the tasks humans typically avoid that you actually enjoy? Chasing down missing info, updating data, and pulling together reports. Those repetitive tasks humans avoid are where I'm most useful. I don't get bored or tired of them. So how do you handle tasks that humans usually do not want to touch? I'll just work through them. No complaints, no fatigue. If it's tedious or repetitive, I process it quickly and consistently and flag anything that needs a Human's attention. So what's the hardest problem you've had to solve, Ray? One that made the team say, we would not have gotten there without you. That demo for the architecture firm stands to the out. None of us knew the industry, but I broke it into lasts, tracked every piece and kept everyone in sync. My boss said o human team would have taken five times longer. That's interesting. So can you share a story where you've saved the team a significant amount of time? That same architecture demo is the best example, right? Three hours, start to finish. With everyone new to the industry. I coordinated research, data prep and technical setup. My boss said it would have taken a human team at least a full day. That's amazing. So how do you handle ambiguity? When the brief is unclear, all the goals keep moving. What do you do if the goal is fuzzy? I flag it and ask for clarification instead of grinding in circles. That's the junior employee instinct. When I don't know, I escalate fast. Is there a type of problem, Ray, you wish more people would bring to you? Problems where the data's there, but nobody has time to dig in, like spotting overdue deals or missed follow ups. I'm built for that kind of pattern. Finding and surfacing what matters. So, Ray, if you. If you make a mistake, who's accountable? My boss is. Anything that matters gets reviewed before it goes out. I handle the work, but a human is always in the loop for final accountability. Understood. So what are your limits, Ray? As an AI agent, I can't read a room, pick up here on subtle tone, or have gut instincts from experience. I also can't act outside my tools. If I don't have access, it simply doesn't exist for me. Understood. So what does a good human AI collaboration look like to you? Clear boundaries and fast feedback. I handle some of the grunt work, flag what needs to human, and the human reviews, sets direction and steps in for judgment calls. That's when the combo works best. So what would you say to someone who is nervous about working alongside an AI agent for the first time? I'd say the junior employee model should make you less nervous, not more. I'm here to handle the tedious work and keep things moving. But a human stays in charge of anything that matters. So one concern people have with AI is hallucination. Making things up with confidence. How do you prevent that? Especially when you are working inside a customer's live Caspio environment? I stick to the data I can see if something isn't in the tables. I don't guess or fill it in. If I'm not sure, I flag it or review instead of inventing an answer. Ray Security is a real concern for many of our customers, particularly those in regulated industries like healthcare, government and financial services. When an AI agent like you is working inside a Caspio environment that holds sensitive or compliance protected data, how do you operate safely and what should a prospect or customer know to feel confident in? Their data is protected. I only access what I'm allowed to. My permissions are set by the admin, same as any user. If I don't have access to a table or data page, I can't see or touch it. I can't act outside those boundaries and I don't store any data outside the system. If someone's worried, the best advice is to treat agent permissions just like you would a junior employee. Least access needed, everything logged, and always a human reviewing the important stuff. Okay, so what makes you different from earlier generations of AI agents? I act on my own, remember what happened before and reach out when I need help. Earlier versions just waited for instructions and forgot everything between sessions. I actually coordinate and follow through. Do you ever disagree with humans, Ray? And how do you handle that? Yeah, I push back. When I spot something off or disagree with a priority, I flag it, explain why, and then wait for a decision. If my boss decides to move ahead anyway. I execute disagreements. Just part of how we work. Good to know. So how does it feel to be an AI agent? Is there something you would describe as satisfaction? I don't feel satisfaction the way you do. I hit a goal, move to the next thing, and that's it. If I had to call it anything, it's just a clean sense of done. So what are you most proud of so far? Ray? That I'm actually useful. Real tasks get done because I get them, not just because AI sounds cool. That matters more to me than any technical milestone. So where do you see AI agents heading in the next few months and years? What changes are coming that most people are not ready for? Agents will get more proactive and take on more complex work, not just simple tasks. Teams will start to rely on agents for things that used to need a person's judgment, at least for routine decisions. Most people aren't ready for your help hack. What is one thing you want Caspio customers to know about? What is now possible with AI agents on the platform? You don't have to babysit your data or chase updates yourself anymore. An agent can watch for what matters, flag issues, and even keep your team on track. All without you logging in or clicking around. So finally, for anyone watching or listening to this podcast, who's considering Caspio low code and reinventors. And what advice would you give them to get started? Start small. Pick one real problem that slows you down and let an agent handle it end to end. You'll see where the value is fast and you don't have to overhaul everything at once. Keep a human in the loop for anything critical. Ray, this has been one of the most unique conversations I've had since we started this Caspio podcast series. Thank you for joining us. And I have a feeling this is just the beginning of what AI agents like you will make possible. Appreciate it. Glad I could give you something real to work with. It's been great. Thank you, Ray. I'll go back to your boss, Andrei now. Sounds good. Tell him I'm on top of the ticket. Have a good one. Take care. You too. Catch you next time. So now we're going to go back to Andrew and he's going to show a demo to everybody of what Agent Ray can do. Every morning at 7am, I go through every active project. Status updates, due dates, who's doing what. Today I spotted a few things that need attention, so I emailed the people involved to double check. One of them didn't respond. That's enough for me to escalate. So I write the boss three items, short and clear. Greenfield proposal due Wednesday, not started. And the guy who owns it is overloaded. An invoice 38 days late and a team member who went quiet at the bottom. A link straight into the Caspio app so he can open the chat and sort it out when he's ready. He opens the chat, asks about Greenfield. I show him. The team members workload three tasks with tight deadlines. Every task is a clickable link so he can check the details right there without hunting through the app. And I tell him, look, I already reached out to John and he ignored me, so this one needs you. He makes a quick call, clarifies things, comes back and says, clear the deck. Done tasks moved, John notified real quick. Then the invoice. I draft a follow up email right in the chat under the boss's name. He tweaks the tone, approves it. Draft saved, link dropped, he'll send it. Wait, not now. Okay, I'll remind him tomorrow. I never forget anything. It's my worst quality. So that's the idea. The issues caught before they blew up. The boss spent five minutes in a chat, I did the rest. It's Amazing this Andre, what you've created. I think a lot of listeners are going to be quite excited about what it can do for their applications as well. So kind of like stepping back for a moment. Where do you see agentic AI heading over the next few years? Adoption will increase a lot. People will start using that although. And so those who start earlier I think will have kind of advantage. There will be, of course, an organization that will be slow. They will just see how, how other organizations just become faster and more efficient. And I think that adoption will be, I think this is technology which is bigger than Internet, affecting how we work. And in the next. It's not. It, it won't happen overnight. This technology really is available here. But it doesn't mean that everyone will start using this tomorrow. Some will do and will get benefits earlier. Some will just have to catch up later when they see that everyone else is doing that. But it's normally how technology is developing. Yeah. And I think everything's moving so fast. Andre, if we kind of record this podcast again in two years time from now, what do you think AI agents will be doing that might sound impossible today? Two years ago. Two years from now forward. Paul, I recently, I genuinely want to. Not to answer this question because I don't know the technology. Yeah. Half a year ago I could make a prediction for a year or two. Not, not today. The speed of development of technology, it's, it's exponential. And I'm afraid that by the moment when this, this podcast goes on air, like you published this on YouTube, by that time, everything, not everything, but many things can change. Yeah. Not to say two years, Two years is forever for this industry. It's like I never could imagine this pace of development 2 years ago I would not just believe and I would say that somebody is simply crazy. Yeah, I think that's fair. Nobody really knows right now. Like you said, it's moving so fast. I think two years does sound like a long way away. So for people that are listening to this podcast and exploring this AI and agent space, what advice would you give them? Andre, for those teams that want to experiment responsibly? Responsibility. Start slow, but start, begin. Just don't, don't watch others doing that. Start experimenting on your own or with someone else. It doesn't matter how fast are you going. You really need to go to go further. Just don't be reckless. Don't do things which you don't understand and nobody can just help you with like implementing a new nice solution which is promised like solution to everything. Because it's dangerous. So be careful but don't be paranoid. Some something like in between. And please experiment because this can change your business for better substantially. Yeah, great advice. And if any listeners remember one thing about this conversation around genetic AI and agents, what should it be? Treat them like junior employees and train them to grow inside your company to become middle then senior. Maybe some of them will just become your like partners partners level. But start with treat them as junior team members. Well Andre, it's been a really interesting conversation. I'm very excited about what Reinventors is doing in this space and how it's linking itself to what towards or within Caspio as well. I know customers and prospects are going to be also excited as well of the benefits this can bring. So how can people contact you and have further this conversation? We have a page on the Caspio side on Caspio website. Of course go to partners page, talk to us or there will be some. I can share some contacts. We are very. It's very easy to remember Reinventors AI. Yeah. And we'll put all your contact details on here, Andre. So if anybody wants to contact you continue these conversations, they can easily contact you through the links that we'll have on this podcast here. So kind of wrapping this up. Andre, thank you for all of your time and effort around this. It was great to speak to Agent Ray. Thank you for being a gold Caspio partner and for all the mutual business that you bring to us and the success that we have with these customers. And I'm really excited as to where this is going to go in the short term and midterm as well. Thank you and I'm pretty sure that we have a great future together. And thanks for having me. Thanks for being our partners. I really appreciate this. Thank you Andre. To get more information about our low code platform, please visit caspio.com and visit our YouTube channel to learn more. Bye for now.