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Why Your AI Strategy Is Failing (And It Has Nothing to Do With Technology) · 10X AI with Julius Neil

• Julius Neil Buenconsejo: Good day everyone, I'm now here with another episode of 10xII with Gilles Neill. I'm here with Alex Todd. He has years of experience in technology. He is now the founder of Leray Labimi and he has several experiences including the blockchain. Alex, can you introduce yourself to our viewers and listeners? Alex Todd: Hi everybody, I'm Alex Todd, I'm the founder and CEO of Reliably Me, it's a tech startup and delighted to be here, Julius. Thank you for inviting me. Julius Neil Buenconsejo: Yeah. Can you tell us what is Reliable Me about? And how does it help your clients? Alex Todd: So what we're building is a trust enablement system ⁓ it's a hands-on, sorry, it's designed ⁓ affect ⁓ trust follow through ⁓ at an level. ⁓ And so it does is it allows people to make commitments to each other ⁓ and it follows with nudges ⁓ and ⁓ to track progress with respect to whether they were ⁓ in training and a follow-up to or how are they applying the training and so on. Or if somebody's onboarding, it follows through as to how they're coming along with their onboarding processes and so on. So it's a kind of a lightweight behavioral evidence system that kind of shortens the distance between intent and execution. Julius Neil Buenconsejo: So you started with the training first and then what are the other applications of this ReliablyMe? Alex Todd: So it's really, we use it with our interns, for example. So they commitments to me and to each other that they're going to fulfill certain tasks. ⁓ make commitments ⁓ they're going to respond to a nudge every Monday with their plan for the week, every Sunday with ⁓ they've accomplished for the week, every with their progress update for the week, and so on and so forth. There's lots of these things, and they receive these automated nudges. Then we collect a tremendous amount of qualitative and quantitative data from them every time they fulfill a commitment, ⁓ get a badge. The populates their commitment portfolio. That also calculates the rating, punctuality score, ⁓ factor, engagement then on top of that, the nudging, ⁓ you can ask ⁓ kinds of questions requests and they have to respond to those. ⁓ So you can get lot of sentiment analysis, ⁓ qualitative ⁓ So combine great deal of qualitative and quantitative data from every individual ⁓ and then fact when we're doing performance evaluations for their school, for example, all we have to do is feed all that data into an AI, including their ⁓ school evaluation form, and it automatically out, AI automatically fills out all their ⁓ evaluations. ⁓ So a reliable, it's fair, equitable, objectives and evidence-based. So it's a very tremendous saver and also me a lot of confidence that I'm being fair with everybody. ⁓ Julius Neil Buenconsejo: wow that's a very good ⁓ platform for especially when you have the snudges and then badges and then how does the user follow up on this and then what does the reporting look like because it's a combination of qualitative and quantitative. Alex Todd: all, real time as people respond to nudges. I get real-time feedback through SMS, WhatsApp, a mobile app ⁓ to how they're responding to those nudges. So first of all, you get ⁓ data. ⁓ you generate reports our administrative console, ⁓ which are on all the commitments that are being made and the status of various commitments and so on, and the schedules and all those things. ⁓ And finally, reports on ⁓ the actual data. ⁓ which is essentially your running reports on the questions were asked through the nudges ⁓ their responses and then you can do analysis on that ⁓ through spreadsheets or feeding it into AI. So typically feed all that data into AI and then it automatically figures it ⁓ out. Julius Neil Buenconsejo: Wow, so that AI model is your proprietary model, right? Alex Todd: No, the AI is generic. What's proprietary to us is this person to piece person commitments ⁓ accountability behavior modification system. So our ⁓ the data and engages, ⁓ an system. it rewards people for follow through ⁓ with ⁓ badges and Julius Neil Buenconsejo: Ow. Alex Todd: that their commitment portfolio acts as an evidence-based supporting credential to validate ⁓ experiential learning, for example, whatever it is that they're doing. So the proprietary part, engagement and generation. And then we use, generically, AI for the reporting. ⁓ We also AI, by the way, for natural language So we're integrated with Slack. ⁓ So when Julius Neil Buenconsejo: Mm-hmm. Mm-hmm. Alex Todd: people messages in Slack, which we use as our primary platform, communication platform, it automatically ⁓ if there's commitment intention. ⁓ either explicit or implicit. either there's somebody saying that they will do something or they're asking somebody else to do something and it will automatically pop up and hey, do you want to formalize that offer or request? And if it responds positively, then the counterparty gets a DM them to confirm. ⁓ so that way all these casual ⁓ that kind of floating around in communications get captured, right? Julius Neil Buenconsejo: Mm-hmm. Mm-hmm. ⁓ That's really quite complicated for me because I don't know how it works, you the frameworks, but it's very, very useful, especially if you are in this space. And also, like for example, the intern, what is the progress of the intern? Are they engaging or not? What are the qualitative analysis when it comes to their behaviors? And then the quantitative analysis in there, for example, in their work. how do you do the KPIs? What are the targets that they have done? I know it's very complicated, especially if you're doing it manually. But using AI and then your proprietary platform, maybe the 40 man-hours work, maybe it could be 30 minutes or 15 minutes. Alex Todd: yes, it's huge, huge time saving ⁓ ⁓ accuracy, right? Julius Neil Buenconsejo: Yeah, yeah. also, yeah, the hardest part of of collating the data is, you the accuracy, the accuracy of the data and then the data interpretation as well. So that, because if ⁓ data is not accurate, then your interpretation will also be, inaccurate, right? So that's result of that. And then you said that the future of work depends on trust and accountability, which you already told us a while ago, not just technology. What are the leaders, ⁓ mostly still getting it wrong. about AI transformation today. Alex Todd: Well, the big problem with use of AI right now is that either people are, first of all, afraid to use it and not using it. That's one extreme. And ⁓ other extreme, ⁓ using it for everything. then ⁓ They have no idea, they're not qualified to do what they're... So in other words, it allows them to act as if they are experts in something, where they have no idea whether the answers that they're getting for AI are actually valid, because they don't have any background. You can tell them anything, they'll believe it. And then they just use it to get things done, and they propagate these hallucinations, or maybe just... Julius Neil Buenconsejo: Yeah. Alex Todd: inaccuracies because they're not using it properly and not using ⁓ assess ⁓ actually is this stuff that they're getting. ⁓ relevant? So human, we're lazy, right? So we're either lazy to adopt something new or if find something that's going to make life easier for us, then we can use in a reckless way. I mean, think about Julius Neil Buenconsejo: Yeah, yeah. They take it as it is. Alex Todd: You know, using a chainsaw for the first time could be quite dangerous. Julius Neil Buenconsejo: Yeah, yeah, yeah. And also, right now, many companies are always saying, okay, a lot of the companies will say, we have an AI strategy, but most of them still fails. Even they have this, AI strategy. So from your perspective, why do AI initiatives break down at the human level, not the technical one? Alex Todd: Well, it is the human. That is, the entire problem is the human level. It's how people don't use or use the AI. Are they qualified to use it properly? can the organization trust what it is that's being delivered to the product as an artifact? ⁓ from that employee you're assuming now that they've done the work and yes okay we're encouraging you to use AI but is purely just AI or are you actually in the loop? To what And so that's it's failing because it's a trust issue because there's no real... there's no... you can't trust either the or your employees. And so that's why failing because it's a trust issue because you can't trust either the AI or your employees. ⁓ to be applying good judgment. So ⁓ is the critical issue. ⁓ to be applying good judgment. So ⁓ is the critical issue. ⁓ so because it's not deterministic, like any kind of a spreadsheet, you write a formula, you're always gonna get the same result, ⁓ So any kind of program. But with AI, even there, you're always getting some variability depending on how you phrase the question ⁓ what of prompt you use. ⁓ So even variations can make big difference in the answer. And so... The are not used to this kind of unpredictability uncertainty. They want know exactly ⁓ what goes and what's going to come out in a repeated way ⁓ consistently. So a lot of issues, but most of come down to behavior, human behavior. Julius Neil Buenconsejo: Okay, so what can you say about the companies now who are, some companies they allow the employees using AI, example in your company also. But what can you say about the companies who said, no, we're not going to use AI? Alex Todd: I think that, well, I would say that if a company says they're not going to use AI, I would be, that would be a red flag for me if I was an investor. Julius Neil Buenconsejo: the argument is always data security, data breach, ⁓ this ⁓ privacy and all this. So they don't want ⁓ ⁓ or the ⁓ secrets of the company to ⁓ outside. I mean, ⁓ confidential. Alex Todd: Yeah. So my argument is that yes, the concerns are, it's human nature to fear uncertainty, something new, and you what's going to happen. That's human nature, it's normal. Companies have a reputation risk, they have a lot at stake. ⁓ They can't risks very easily. So I've gone and seen the cycles ⁓ when email was introduced and that wasn't allowed in companies because of ⁓ secrets going out to people. then also with cloud computing, what do mean you're gonna take my computers and my data and put it somewhere, who knows where it is, right? ⁓ are we gonna trust that? So, and reality of the world is that ⁓ we to it, we understand that these providers of these services ⁓ have brand, have Julius Neil Buenconsejo: Yeah. Alex Todd: They have brand promises they have to maintain. If that brand promise erodes, their market value erodes ⁓ they lose customers. ⁓ they can't afford ⁓ have missteps. mistakes happen. Don't get me wrong. ⁓ I mean, ⁓ the systems that they're putting in place are to protect you, particularly because they have to protect their own brand. Right? ⁓ So having that, Julius Neil Buenconsejo: You Alex Todd: You can, so if you're using external services, yes, but there's also other considerations that are very valid as well. You have to know what you're doing. You have to have governance in place that is, that has guardrails as to how things can be used. For example, there is ⁓ very powerful AI agent that has just been released a few days ago. and it's hitting the world by storm and essentially it's called um it's been called it's changed its name three times in the past three weeks or two weeks even um it's started most people know it as Clawd Bot uh then it renamed to Molt Bot and now i think it's Open Claw Open Claw all lobster themes and um and so they um what it does Julius Neil Buenconsejo: Okay. ⁓ my god. Uh-huh. Alex Todd: It's this open source. It runs on your computer locally. it control your entire computer and everything that you do. And it is ⁓ powerful so scary so smart. I can't get into lot of detail. I'm just going to link right now in a conversation with a colleague. Julius Neil Buenconsejo: What? Okay. Alex Todd: who he and I are evaluating and are both afraid of implementing it in our systems because there's no guardrails. If you make a mistake in how you prompt it and what you ask it to do, who knows what it'll go off into on its own. So this is where we're going. And so there's absolutely in some situations real reasons ⁓ for Julius Neil Buenconsejo: Mm-hmm. Alex Todd: about how you're implementing and using AI. But for the most part, what most people do is using these commercial services like ChatGPT from OpenAI or Anthropics. really try to protect your data. Like I can't put in secrets into system. it will detect them and will prevent me from sharing those things and so on and so forth. So there are all kinds of controls in place. Obviously there's still risks and you don't know what's going to happen, but generally speaking, if you have a paid subscription with those major companies, you're going to be fairly well protected. Julius Neil Buenconsejo: So you're saying that if it's an enterprise level for example for companies, so most probably there are guardrails for you. So you can trust this, you know can trust the system. Okay, so you spend your career in trust, yeah. Okay, of course, of course, of course, of course, at least there are... Alex Todd: Yes. Yes. Nothing is 100%. Nothing is 100%. Let me define trust for you. I define trust. Julius Neil Buenconsejo: Okay, we've been talking about trust. Okay, define trust AI. Alex Todd: So anything, ⁓ define trust as acceptable uncertainty. So uncertainty is quite quantifiable. Acceptability is personal. So it's choice. So what is uncertainty to you would be different from what it is to me. And also circumstantial, depends on the circumstances. Julius Neil Buenconsejo: Yeah, all right. It's very subjective. It depends, you know, how much, yeah, and how much risk can you take based on your situation. on. So you've spent your career in trust innovation from PKI to blockchain and then behavioral systems. How was the definition of trust evolved in the age of AI? You said that uncertainty, right? Uncertainty. So in the age of AI, is it still the same or is it going to be... Alex Todd: Yes. Yes. Acceptable answer. Julius Neil Buenconsejo: there's some variable. Alex Todd: There's no variation. That is the definition. However, how you create conditions for trust also universal. There's a framework that I have. But in essence, you have have governance. have to have guardrails, as I said earlier. You have to have Okay, so there's, I'm not gonna get into details, but the point is there's a comprehensive framework optimizing, analyzing and optimizing conditions for trust. They're applicable for any type trust, whether it's personal ⁓ relationships whether it's with AI, it's the same. The mechanisms the are different, of course, between people, relationships, and with AI and ⁓ any other kind system. But it's all based on information theory. Can you rely the information in a consequential way to take some action? the consequential action. So that's really what it's about. we can engineer trust is what I'm trying to say. ⁓ Reliably Me ⁓ designed to address that in certain ⁓ set ⁓ circumstances. a trust infrastructure, if you will, that is ⁓ designed to... build trust, establish and maintain trust between any entity, mostly people, but also between AI, AI agents and people, between AI's themselves. imagine scenario where you're actually making commitments. Any party can make a commitment to any other party and as they ⁓ their commitment they give recognition. But the point is ⁓ they're not allowed to take any action until that commitment has been, the prior commitment has been fulfilled successfully. ⁓ Only can they move on. So think about these ⁓ AI for example. The biggest is, ⁓ I alluded it with, open claw, whatever it's called now, it can go off and do stuff on its own. how do you put guardrails on what is allowed what is not allowed? And so what you need, ⁓ you always need have the human in the loop. I mean, I have problem with ⁓ my team members, my We had a situation recently, broke the system. Julius Neil Buenconsejo: You ⁓ Alex Todd: ⁓ And they can't they don't know what happened because they don't know what they're AI is doing it for them and they have no idea what what they did it I said well look at all these database Changes that you made and they said well, I don't recall I said well what were you using an AI engine? Well, yeah, they're just going to proving everything without checking what the AI is doing ⁓ and they messed up and then they can't go back and figure out that they were responsible, that they did something. They didn't realize they did it because the AI did it for them. So I that's totally broken. That's not how it should work, right? It's scary. Julius Neil Buenconsejo: Yeah, you mentioned about it. Now it becomes the accountability part. If I use AI, for example, your intern used AI and they just prompt it and then use that AI, who's accountable if something goes wrong or something was broken like yours? And that's one of the ethics, maybe ethical issues or some other guardrails that AI should evolve from. Because right now we don't have that governance right now. Alex Todd: Yes. Julius Neil Buenconsejo: So everybody can do whatever they can, every startup that has, focusing on AI, they can do whatever they want because there are no guardrails, there are no laws or regulations or whatsoever to stop them from doing what they want to do, especially what you're saying, the open claw, right? They can do whatever, they can operate, in your PC and they can do anything, right? Alex Todd: No, we don't. do whatever they want and doing stuff that they're not qualified to do. They don't understand what it's doing and just say, ⁓ it's getting done. No, don't get me wrong. I make the same mistake. I'm using it for things that I'm not qualified to do either. so I'm also guilty that, ⁓ but I haven't anything yet because I have more common sense. Julius Neil Buenconsejo: Uh-huh. Alex Todd: do verifications and checks and stuff like that. I'm not 20-year-old. So yeah, human judgment ⁓ is extremely in having effective AI implementations. Julius Neil Buenconsejo: Okay. Yeah, obviously already have some firm reliability experience on this. So organizations often rely, those organizations who are not using Reliable Me, for example, they often rely on surveys and annual reviews to understand the performance. So why are those tools fundamentally incompatible with how modern teams actually work right now? Alex Todd: because they're not evidence-based. They are subjective. So if you put out a survey, So here's how I've done, historically I've a manager in organizations and this is how performance reviews have been done in the past. ⁓ Both me, my performance reviews and also those of others who reported to me. ⁓ So happens is you ask the person to do a self-evaluation based on certain criteria. Okay, they fill that out. Then as a manager you look at it and say, Julius Neil Buenconsejo: Mm-hmm. Alex Todd: Okay, I have my ideas from what I recall. reasonable. ⁓ let me ask you about this. So is just from what I remember, right? And how am going dig through everything that happened? can't, you know, you don't track everything that happens. And so, so it's ⁓ it's very subjective and difficult to, to defend, quite frankly. Julius Neil Buenconsejo: Hahaha Alex Todd: both parties for the employee and for the manager who is doing the evaluations. ⁓ But you use a system ReliablyMe where every commitment is being tracked and And results of that, because when somebody says, I've done something, they have to provide evidence as to what they've done. ⁓ then when they're those, responding the nudges, you actually know how they feel about things, what they're struggling with, what they need help with, how proactive they are. ⁓ You tell how they're ⁓ responding the questions. And so have objective of every significant activity they're Julius Neil Buenconsejo: Yeah. Alex Todd: engaged in throughout the process. so, frankly, you can intervene if they have issues and challenges proactively. That gives that kind of ⁓ visibility at times. ⁓ for the reviews, it becomes really trivial exercise that before AI, it was very, very Julius Neil Buenconsejo: ReliablyMe captures the commitments from everyday workflows through Slack or WhatsApp. So what does commitment data reveal that the traditional performance metrics completely miss? Alex Todd: So first of all, you know what they're committing to doing. They say, I will, they make promises, I will do this, I will do that, or I promise to do this, whatever, right? That's a statement, first person. Secondly, each commitment is associated with a badge. The badge is both a ⁓ that governs that commitment. Julius Neil Buenconsejo: Uh-huh. Alex Todd: but also it represents ⁓ is the nature of the commitment. ⁓ it a ⁓ skill that they're developing? Is it a soft skill? Is it Is it teamwork? ⁓ Or it ⁓ Node.js or MongoDB or whatever? So they choose ⁓ the badges they want to earn so they can show evidence of the kind work that they did, experiential learning or experience they have with that skill based on the badges that they've collected and ⁓ commitments that they made and also the evidence of what they said they did to earn the badge. So when they provide proof. ⁓ then in addition to that, you've got that the nudging, which is the qualitative data. Now on quantitative side, you're also those badges ⁓ are the individual's commitment portfolio. And that commitment portfolio is a collection of all their commitments that they've made, successfully and unsuccessfully. the badges that they've earned, their reliability rating, punctuality score, confidence factor, engagement points. ⁓ you can actually see and chart how engaged are people. Are reliable? Is their reliability dropping off? Are they punctual? ⁓ Are confident to make longer term commitments? So are all indicators. So there's a lot of rich information there. And commitment portfolio actually belongs to individual. So if they're working for somebody or they're at school or the sports team or volunteering, that every aspect of their lives, ⁓ accumulating everything into their commitment portfolio that then they can filter and whatever and then present the, if somebody asks for evidence, present just the subset of that data ⁓ that particular party is interested in without revealing everything else. ⁓ the point is it belongs to them, not to the organization. Julius Neil Buenconsejo: Yeah, but it's quite interesting also because you as you also work in a corporate environment so this annual reviews performance reviews sometimes even if you're doing good, The comes in the way for example for promotion and all that so I'm just quite ⁓ curious how do you think Reliable Me will be able to at least, Alex Todd: They know. ⁓ Julius Neil Buenconsejo: neutralized, you know, 90 % of the politics when it comes to performance evaluations and then the promotion of the individuals. Alex Todd: Totally. ⁓ I think that it actually does bypass it. Let me give you an example of, I had a situation where I doing a performance evaluation of somebody using ⁓ system that I described recently. there was one aspect where the AI did not have enough data to provide evaluation of a particular aspect of the person's performance. So it said, don't know. mean, it's ⁓ not enough data do that. So I it in, myself, judgment. My own personal judgment, I put the evaluation in. I got challenged by the individual, right? So said, well, I'll tell you what. I mean, ⁓ I'm claiming, as I said to you, you're going to be evaluated by AI. In this case, I did it, so not fair. So ⁓ let's give more context be able answer that question. Julius Neil Buenconsejo: You Alex Todd: Because the individual I recorded the conversation, so the previous conversations actually had evidence of what they claimed that they had done that's relevant for that evaluation. So I said, let's give it everything and then let it decide. open to whatever. ⁓ can make mistakes. ⁓ we're into it and he got the higher evaluation. ⁓ Julius Neil Buenconsejo: Mm-hmm. Mm-hmm. ⁓ nice! Alex Todd: And I was happy and he was happy. Everybody was happy. Julius Neil Buenconsejo: Yeah, that's a great real-world example of what the AI can do. So how about in making commitments visible directly? How does this improve using ReliableMe or the AI aspect of that? Alex Todd: the thing, AI ⁓ useless relevant, data. the more relevant, data you give it, the more useful AI is. Here's the thing, is ⁓ without valid So the more valid data you give it, the more useful AI is. And so what ReliablyMe does, it's generates, ⁓ it's a data infrastructure ⁓ that ⁓ generates tremendous of, as I said, qualitative data. evidence-based, objectively based on evidence of behavior attitudes. So intrinsic. So if you're an AI investment in your company and you want to improve your AI ROI, you would want to find rich, ⁓ valid on things that want. to use AI so that you can use AI and demonstrate its exponential value over what you've been able to do before. I can't think, sure there's other examples, but offhand, can't think of another example where something is generating this kind of quantitative quantitative data in real time in such large quantities ⁓ and valid. Julius Neil Buenconsejo: Mm-hmm. Alex Todd: and that would feed AI. It's a godsend for AI. I designed it and developed it before AI. But now that we have AI, it's so much more powerful. It's absolutely critical for AI to have a tremendous amount of Julius Neil Buenconsejo: Hahaha Alex Todd: contextual data that's and currently relevant. ⁓ if you don't have that, you don't have your AI usage ⁓ results are to be mixed. And ⁓ the afraid you are of giving it data, ⁓ the worse the ⁓ results are to be. ⁓ Julius Neil Buenconsejo: Ha ha ha ha ha. So based on the data that you're getting, have qualitative and then you quantitative. So does the behavioral data change affect the person? Is system will be able to, for example, predict, okay, these are the qualities that you have right now and that the company wanted you to be like this? Is it also part of that? Alex Todd: Right. Yes, absolutely. So you're tracking, you're tracking those big behavioral trends. So we're affecting behavior change through the commitments and the nudging. So it's designed to affect behavior change. And then we track behavioral outcomes, okay, as a result. And behavioral outcomes, behavioral outcomes are a leading indicator of impact. Julius Neil Buenconsejo: Okay. Alex Todd: the ultimate result. So you can see a trend. I if behavior changes, your results are gonna change as well. Julius Neil Buenconsejo: Yeah, it means for example, because in an organization, you see there are people who talks a lot, you know, but there's no, talks a lot, but less, you know, less output. And there are people who are quiet, but they have maybe 80 % of the department, are doing all these things. So it will also manifest in this report that you have, right? Alex Todd: Yes, because it's subjective evidence. It's not just on how much you communicate through in meetings or in Slack or Teams, whatever it is that you're using, but also and more particularly is explicitly. You're ⁓ being asked to some things and then you have to respond to those. ⁓ And how you to them ⁓ is... is evidence of your behavior, so it's objective. Julius Neil Buenconsejo: an organization, for example, an organization that is still starting ⁓ AI, there will be resistance. Resistance to AI is often framed as a fear of replacement, which is always like that. What have you seen actually drives resistance and how does trust reverse it? Alex Todd: Yes. So first of if you're afraid of being replaced and therefore not ⁓ being a Luddite ⁓ trying to sabotage AI implementations, I you're sabotaging your career. So that's the first thing. So that's, there'll be, you don't trust AI, ⁓ then management will you. It's okay to... also the ⁓ adage, know, coined by... President Reagan was trust but verify. And so true with AI. You trust it to do certain things, but you got to keep track of what it's actually doing. ⁓ It's same thing with the employees who are using AI. You trust to use it, you encourage them to use it, but then when you're getting ⁓ what they slop, ⁓ stuff that's out of it that hasn't been gone through a filter, ⁓ just easily ⁓ dump it. I do it too. Julius Neil Buenconsejo: You Alex Todd: do it as well. We get lazy, right? Because we're busy with other things. It's not a good thing. People have be held to account that they're showing evidence of having in the loop a significant way and used applied good judgment. And so we use, for example, I'm not saying we're doing it perfectly, but I'm just giving an example. We actually have our team members make commitments that they're going to respond to nudges related their use of AI twice a week. And so ⁓ receive a ⁓ and it asks ⁓ how they've used what's worked well, what hasn't worked well, ⁓ how could they their usage next time. And then we also have other nudges that ask them, OK, have you ⁓ Julius Neil Buenconsejo: Okay. Alex Todd: added, given it more context, you know, and what were the results of that? would you try next time? ⁓ that kind of stuff. So ⁓ trying to get them to think about they could use it more effectively based on reflection and also proactively thinking, okay, now that I've learned this, ⁓ how could do, what more could I do? Julius Neil Buenconsejo: That's a very profound explanation of what the system can do. So you also mentioned about ⁓ CHROs, evolving into cheap people and performance officers. So what new responsibilities does the role require in an AI enabled organization? Alex Todd: So yeah, it's a good question. See, my insight is that kind of what I mentioned earlier, HR is probably afraid of AI. And it's And the reason is because they get their budgets based on the number of people that they're in the organization. So if AI is going to reduce the head counts, then the budgets will go down. And if the companies are investing AI versus people, then the budgets are going to the AI implementations and IT departments. if I were an HR manager, I'd be thinking, oh, shit, what's my future look like? It'd be frustrating. Julius Neil Buenconsejo: Yes. Yeah. Correct. Alex Todd: But what I'm trying to say is we can empower HR people and we empower them by having them embrace the idea of being able to gather really valuable data that will support the AI implementations of the company. So suddenly they become a strategic resource for generating AI ROI. Julius Neil Buenconsejo: that's ⁓ good take on that. That's a good take on that. But ⁓ think now it's not yet there, but I think it should be there in the future. ⁓ all of this transformation becomes a standard for every organization, then we will have a different responsibilities or, you know, an amplified responsibilities for the new CHROs because they will become part the process of implementing of AI and the solution. So... ⁓ Alex Todd: The solution. The actual solution. Julius Neil Buenconsejo: So we talk about the CHROs for the CEOs and CFOs who are listening or watching right now. How does behavioral visibility help them connect human change to financial outcomes in a way they couldn't before? Alex Todd: Well, think about any department. talk about sales, for So let's say in sales, ⁓ are your, what is the key success factor for sales if you're outbound sales? It's ⁓ number of that you make. ⁓ Essentially. So it's very ⁓ for, you the top performers do what they do and they do it well. They could always get better, the uplift for the organization is going to be taking those middle the ones that are not as good, and lifting them up. ⁓ And what ⁓ is them back? Well, it down to basically behavior. I'm oversimplifying when I say it's just number of calls. ⁓ But you also track with. First of all, with Reliable Me, you can their commitments, can ⁓ ⁓ things are going in terms of their experiences, what customers have said, ⁓ they responded to certain situations. Get that in real time, real everyday. They respond to nudges and you're getting a sense of what's going on, right? So you can adjust that. First of all, Secondly, if they're being gone through training, can help them, you can reinforce that training. You can say, okay, so you attended this one week training or whatever it is, we made that investment, how we applied it today. and it make a difference, et cetera, et cetera. So you can do that on regular basis. It does two things. One is it refreshes their memory about what they learned. ⁓ you can also tell whether, so they could try applying it, or it tells you whether it was worth it. Was it worthwhile? mean, ⁓ is it they can apply? Are they having success with it, right? so you can, so you'll get an ROI on the training. ⁓ You'll get the behavior on the training, okay? You'll get them to stay committed because, and on track because they're getting recognition ⁓ not only the end results, but actually the process of getting to those end results, okay? So they're getting the badges, they're getting the recognition for all the right things that they're doing. So. So I mean that's it. And what that will do is it's an array is this expression is arising tide lifts all ships, right? So if you can do that with most of the people, even raise them a little bit, you're going to have better outcomes. I mean, it's just math in this example. Julius Neil Buenconsejo: Yeah, yes. So in terms of the, you know, in terms of the transformation of the organization, so we talk about behavioral changes, we talk about commitment, accountability. So if every organization can see commitments, the follow through and the trust in real time, what would fundamentally change about leadership, culture or power dynamics at work? Alex Todd: It would be a huge culture change. Right now, organizations do have ⁓ robust systems. People are held to account in an explicit way. ⁓ They are to account in an implicit way, ⁓ in a way. Obviously, everybody knows if somebody's reliable or not. hearsay and reputation in the organization and so on. Things slip. It's normal for things to slip with everybody. there isn't explicit expectation that you're going to be ⁓ make explicit commitments and it will be your commitment is not just something you say you're going to do or it's on your, you you come out of a meeting, you come out of a meeting, you have all these next steps for everybody, right? everybody takes away their own, you don't know what happens ⁓ that, you kind of have to follow through. What do is we just, use ⁓ system with AI grab all the next steps for each individual and automatically ⁓ send commitment requests each of them coming out of that meeting. Julius Neil Buenconsejo: Yes. Alex Todd: automatically just goes out. So you copy paste, bang, gone. So there's no ambiguity. Everybody has their commitment request. They have to accept it. If they don't accept it, you can see and find out why they didn't accept it because they always have a choice. You have to give people a choice. You have to empower them as to whether want to make the commitment or not. And so was their choice. ⁓ And they're to get it done, you don't tell them. when you must get it done, as you can suggest, but ultimately it's their own choice as to when, and then they're being evaluated on actually when actually did it relative to when they said they were gonna do it. ⁓ so they're being empowered and being held to account ⁓ for choices. So, So the culture change is huge because there are hardly any organizations that enforce ⁓ even in compliance scenarios ⁓ there is a safety compliance issue or other kinds of regulatory compliance. you know, you have what happens is everybody kind of just goes through the motions. HR puts out the training, then they expect to do it. If you've gone through the training in a ⁓ tech ⁓ there be a survey that comes out ⁓ later that's it. Nobody cares ⁓ after ⁓ So the person is actually staying compliant ⁓ and that attitude and the desired, the required behavior, nobody's tracking Julius Neil Buenconsejo: Yeah. Okay, so you mean that for example, most of the organizations work like this right now. Okay, these are the KPIs, you need to finish all these trainings on time so we'll have 100 % completion within the end of the month. So, this numbers does not really equate into behavioral changes, Or cultural changes. So based on reliable me, will you be able to use your platform to be able to, you know, initiate the culture change or initiate the behavioral changes of the individual or the department. Alex Todd: Yes, absolutely. is the most cost effective way to affect behavior change. Julius Neil Buenconsejo: Okay, that's very interesting. It's very good. It's a very good platform because you talk about qualitative and quantitative. Most of the technologies that we have right now is more on the technology side, efficiency and all this data. You can track it by the numbers. But the qualitative data is very hard to track. You don't know if somebody is really improving their perspective. You don't know from being a negative person becomes a positive person. or from being, I mean, ⁓ just non-engaging or just going to work to being an engaging person. So if you're going to be able to capture that in that system, both of those sides, it's going to be a holistic in AI transformation. It's very, very timely. And also what I saw is even though you are a technology guy, you have this technology, you always... Go back to culture, commitment, and human, and people. Why is it? Why is it that? Alex Todd: Well, the reason is that the whole purpose ⁓ why ⁓ conceived of her life to me is to help people, to empower them, to them be recognized for their authentic self and social worth, to help them be trusted by strangers. based on objective evidence of them making their social contracts and fulfilling those social contracts and their track record of having done that. And that was the whole purpose of it. It was all about using technology to people. Julius Neil Buenconsejo: Yeah, it's a very good point. Creating a technology to help people not to replace them. Right? Alex Todd: Absolutely. We're not an app. We are an infrastructure that mediates the relationship between people. facilitates ⁓ commitments and ⁓ throughs and all that ⁓ maintain those relationships and that follow through. So it allows people to engage. ⁓ in a very simple and quick way via SMS or text messaging or WhatsApp, know, on the fly. ⁓ it works equally well in an office environment or sites remote or, you know, or ⁓ remotely like teams all over the world through Slack ⁓ and all ⁓ So ⁓ equally in any, for any scenario, ⁓ it's quick and Julius Neil Buenconsejo: You Alex Todd: has huge benefits. kind of a lightweight trust infrastructure. ⁓ that is very flexible. It's an API, it's a smart API, so it integrates with almost any application, intelligently. So it can be plugged into Salesforce, ⁓ ⁓ ⁓ ⁓ GitHub, it is that you're using. ⁓ And can accountability. ⁓ Julius Neil Buenconsejo: Yeah. Alex Todd: and you can track what commitments were being made, that somebody's gonna do something, and did they do it, and then you can find out what the issues were in trying to do it or getting it done, ⁓ then you'll know, have evidence that it was done, and then you can approve it, and that'll be recorded, and all that kind of thing, right? ⁓ Julius Neil Buenconsejo: Yeah, so there's one comment also in my previous podcast in his or her episode, there's one comment ⁓ whatever saying about human, focusing in human for the AI transformation and he commented that everything that AI transformation right now, the company only ⁓ on ⁓ the ⁓ the money the financial side. They don't care about the people. But here, I have you, you are the CEO, you are the founder of company, but still you about the humans and the individuals as well. So for those viewers or listeners that we have right now, what is it that not every will be thinking like that? What is it from your perspective that will make at least ⁓ change their or just reconsider of saying that, okay, not all companies will be more on the financial side, they also care about the people? Coming from a founder like you. Alex Todd: So what I would say is that are holding, ⁓ a financial side, these are the outcomes, these are the impacts, ultimate result. Have you more sales? Are we more profitable? Those metrics, right, quantifiable metrics. ⁓ The issue is a ⁓ couple of things. of all, when you don't, when you, so. So everybody's struggling. Do it any way you want. Just get the result, right? I care how you do it. Just get it done. first of all, it shows a lack of care ⁓ nurturing. ⁓ secondly, Julius Neil Buenconsejo: Yes. Alex Todd: A lot of those ultimate results are not necessarily in your control and you're being held accountable for them. So in other words, to close a sale, it's not necessarily, you can say all the right things, but there's so many factors that the customer is ⁓ to decide whether gonna make that particular purchase or another one, if any at all. And so a lot is not in your control, right? And that's why it's a numbers game in many cases. The more doors you knock on, the ⁓ the chance that somebody will buy kind of thing, right? That philosophy. So first of all, lot of it's out of your control, so it's not fair, okay? Secondly, you're not nurturing and cultivating the people's ability to be successful. right, by ensuring that they're modifying their behavior that will empower them to be more successful. And so that's being missed. mean, yeah, we're going through the motions training and that kind of thing and ⁓ and whatever it is, rallying rally things, know, off and stuff like that. But in reality, we don't have a systematic way of holding the people's hands, if you will, their journey ⁓ encouraging and motivating them to actually their behavior they will produce better results. Julius Neil Buenconsejo: That's a very good take on that. So at least I have one founder and CEO right now who is telling us that not company is ⁓ all the financial side. So there are companies also that cares about the human, the people to be able to be successful in their jobs. Okay, so looking ahead three to five years from now, what will separate companies that successfully scale AI from those that quietly abandon it if there are companies who will abandon it? Hahaha Alex Todd: Well, those who abandon it will be abandoned. But those that adopt it in serious way are going be competitive. They can be competitive in several ways. First of all, they are going to more productive. Julius Neil Buenconsejo: ⁓ yeah. Alex Todd: they're going to have better quality employees that do retain. Now they're not going to keep as many, obviously, but they are going to retain those that apply the judgment, ⁓ skills, ⁓ cognitive skills to be able to manage the AIs. Because really what you're doing with the AIs, you're managing them. ⁓ an orchestrator. You're sure. It's a function, supervisory management function, really. So they'll have those skills and that cognitive capacity for success. You have better quality employees. will be able to move a lot faster. stay relevant. mean, there's also that really important aspect of this is that agility and the ability to constantly learn and adapt is important and it's so difficult for larger organizations to do. But those organizations are going to be the the ones that survive essentially. They'll be able to pivot quickly. They'll be able to... Wayne Gretzky, a famous Canadian hockey player, known for saying... I him, what's the key to your success? ⁓ He I skate not to where the puck is, but to the puck is going to be. Julius Neil Buenconsejo: correct, correct. Alex Todd: ⁓ now things are moving so quickly on a weekly basis. There are major announcements, major changes week. And so if you're not nimble enough to see what the trend is, what's going on, and like I just talked to you about ⁓ OpenClaw, which is the latest, very, very important significant development in the AI and start understanding what are implications of that? And ⁓ what are the... pros and cons us and how can we leverage ⁓ these ⁓ to advantage, competitive advantage ⁓ and we have to be thinking in terms of exponential growth now. We're no longer thinking about ⁓ linear growth patterns. And it will also be increasingly, this is another thing, going a little bit further out. So this is first survival through this period of turbulence and change. That's the first change. But after that, equation is going to change because the of success of a company are going to change as well. The economics are going change. The cost of everything is going to go down. So think about AI agents and AI robots doing a lot of the work, most of the work, in fact, that humans do. But fixed costs. There's very little variable cost there, right? And so once you make that investment for scale, they can start, you know, make the investment and then they actually produce for scale so they can justify ⁓ their investment, right? The cost everything goes down and ⁓ with, that puts pressure, mean that could increase profits ⁓ but it will also ⁓ put pressure on profits of competitive environment because everybody's costs are being reduced for less money, right? So it's kind of this race to the bottom, if you will. So equation to what success looks like and for whom. From a ⁓ broader economic perspective, just for financial, but brand value, all the intangibles, all the human things, that's going to become a more important. Julius Neil Buenconsejo: Yeah, yeah, yeah. Alex Todd: And so ⁓ the next five to ten years, the as to what we consider, how we measure success, ⁓ I is going to be very different. Julius Neil Buenconsejo: Okay, that's very good. You touch all the aspects of the transformation from AI and into the future. Okay, thank you very much for all the insights. I enjoyed a lot and I learned a lot from you also. We now move on to the rapid 10x questions that I'm going to ask you. So we will have 10 questions about your AI daily or what are your perspectives about AI. So question number one, what's one tool you actually use every day? AI, AI tool. Alex Todd: Comet, Perplexity's Comet is my new default browser and its assistant ⁓ what I use all the time and it does a lot, I delegate to it. Julius Neil Buenconsejo: Uh-huh. Okay, that's So what one task AI has already 10x in your life? Alex Todd: uh... so from idea to artifact just instantly you have an idea for a new website or do you idea for for a new education program just creates everything for you a simple example every day is uh... you know every week we have to do a team meeting i should prepare my agenda five to ten minutes before the meeting based on, but with AI agent a look at the previous meeting, what happened notes, looking at the communications since then in the past week, and it creates an agenda five or 10 minutes before the meeting for me. Julius Neil Buenconsejo: And that's good, that's good, that's good. So what's one human skill I can never replace? Alex Todd: Judgment. Julius Neil Buenconsejo: I agree with that. If you could automate one annoying thing forever, what would it be? Alex Todd: You know, it's this coordination tasks. It's all a friction of thinking and finding what the source of information is and being able to take the information and move it from one place to another, fill out a form, all those things that take up a tremendous amount of time. Performance evaluations, for example. All those things that take a tremendous amount of time and are hard to do and they don't add a lot of value. It's all process. Julius Neil Buenconsejo: Yeah. what's the biggest misconception about AI right now? Alex Todd: It replaces thinking. Julius Neil Buenconsejo: What advice would you give someone who wants to become 10x starting today? Alex Todd: Learn how to verify outputs. mean, if you want to move fast, AI can move fast. Julius Neil Buenconsejo: Yeah. But you still have to verify if it's accurate enough to be able to move ⁓ Alex Todd: Which direction are you going to move in? Julius Neil Buenconsejo: Yeah, yeah, So, okay, for example, looking back, what would you tell your younger self about the future? Alex Todd: Leverage Beats Effort. Julius Neil Buenconsejo: What's One Book, a podcast, research that's shaped your thinking about AI or innovation? Alex Todd: The Moonshots podcast with Peter Diamantis. ⁓ Julius Neil Buenconsejo: What do you like about the Moonshot Podcast? Alex Todd: They're highly optimistic, visionary leaders from various disciplines ⁓ in tech startup who have a lot of insight into what trends are, they're going. And so you're thinking about you'd have take your company in the future, think about what they're talking about because they call it twice a week a podcast that's about an hour and a half and it's insightful and it's inspiring quite frankly. Julius Neil Buenconsejo: Okay, so if you had to bet one AI trend that will be massive in three years, what is it? Alex Todd: I would say accountable, agentic systems with memory and governance. Julius Neil Buenconsejo: In one sentence, what does 10x mean to you personally? Alex Todd: would say ⁓ the distance between a good idea and a trusted outcome. Julius Neil Buenconsejo: Okay, that's nice. Thank you very much for that very insightful, entertaining, fascinating and enjoyable conversation that we had for the last hour. So for our viewers or our watchers right now who can be your future clients or somebody who wanted your advice, how can they reach you? Alex Todd: I think the best way to reach me is through LinkedIn. So it's Alex Todd and it's Reliably Me. So can find me quite easily. based in Toronto, Canada. So can find me easily on LinkedIn. Happy to respond to any messages there. If you could visit our website if you like also at reliablyme.com. And we a generic email address info at reliablyme.com. Happy to answer questions that way as well. So looking forward ⁓ engaging with anybody Julius Neil Buenconsejo: Yeah, thank you very much again for your time