80% of the Workload Done Before a Human Touches It

Sean Weisbrot: What's it like to spend all day every day thinking about how to disrupt your own business model so that others don't do it for you?

Ray Meiring: It's a huge amount of mental energy, but incredibly exciting to be thinking about that all day, every day, to be reading about it.

Ray Meiring: Sometimes the ideas are coming to you at, like, 03:00 in the morning, and you're scrambling for some device to write them on.

Ray Meiring: But extremely exciting, very energizing to do that.

Sean Weisbrot: What are you thinking about in three in the morning?

Sean Weisbrot: Give me something specific that came to you recently.

Ray Meiring: I'm thinking about how do we change the proposal process, and

Ray Meiring: can we do everything from cloud?

Ray Meiring: Do we even need a UI on this thing?

Ray Meiring: Is it completely headless?

Ray Meiring: Or, where's the value of the UI?

Ray Meiring: Should we be challenging old thinking and old beliefs around this?

Ray Meiring: And you know those kind of three AM

Ray Meiring: thought processes that happen?

Ray Meiring: Sometimes they're absolutely daft, crazy, and and they should just be put straight into the trash.

Ray Meiring: But other times, they're pretty good, and you come up with a good idea.

Sean Weisbrot: How do you know which ones you should throw in the trash and which ones you should keep thinking about?

Ray Meiring: When I wake up the next morning, there's some clarity that normally comes to some of those ideas, but

Ray Meiring: you've got to test them.

Ray Meiring: So it'll be straight into a meeting with maybe my product team or my engineering team having a discussion about, you know, what we might do, or

Ray Meiring: even better, with a customer.

Ray Meiring: Hey, I had this thought.

Ray Meiring: What do you think about it? Has this got any merit to it? How's your organization thinking about these things?

Sean Weisbrot: Have you ever considered talking to Claude about something before you talk to that customer or your team?

Ray Meiring: I do it often, actually.

Ray Meiring: I I I might bounce the idea of of Claude,

Ray Meiring: get some critical thinking on it. It's been really good at doing that, at giving me a perspective

Ray Meiring: on things.

Ray Meiring: Sometimes it kinda tells you what you wanna hear,

Ray Meiring: which is, which is the risk with that.

Ray Meiring: So you still need further validation, but absolutely.

Sean Weisbrot: Do you ever go to another AI with an idea that that Claude gave you, like Gemini, for example, and say, hey.

Sean Weisbrot: Claude gave me this idea.

Sean Weisbrot: What do you think about it?

Ray Meiring: I haven't done that yet.

Ray Meiring: I haven't done that yet.

Ray Meiring: So yeah.

Ray Meiring: But maybe that's something to to go for.

Sean Weisbrot: How has AI

Sean Weisbrot: helped you or hurt you in the process of coming up with the next generation of RFPs?

Ray Meiring: The challenge is

Ray Meiring: obviously trying to track where this is all going.

Ray Meiring: Right?

Ray Meiring: And what is possible and what isn't. So on the herd side,

Ray Meiring: the herd comes in that you're constantly thinking, and you're trying to keep up, and you're trying to you're trying to move in that direction.

Ray Meiring: But where it's been incredibly helpful is taking

Ray Meiring: the current UI that we have in our system, all the current

Ray Meiring: flows and process, and saying, what would this look like in a fully agentic world?

Ray Meiring: And then having that conversation of challenging

Ray Meiring: yourself or it about what that looks like.

Ray Meiring: So it's hurtful when you've got to be constantly deliberating those points,

Ray Meiring: but very, very helpful in being able to challenge and run various processes through it.

Sean Weisbrot: One of the things that worries me is that

Sean Weisbrot: I can have an idea and implement it faster than I can think about whether that was a good idea or not.

Sean Weisbrot: I imagine with a business like yours,

Sean Weisbrot: where mine is new, I don't really have customers yet.

Sean Weisbrot: So it's okay for me to iterate, but it's also bad because I don't have other people giving me feedback.

Sean Weisbrot: You have the benefit of that.

Ray Meiring: Right.

Sean Weisbrot: In an industry that hasn't really changed in, like, what, fifty years, people are still using, like, binders

Sean Weisbrot: to, like, share information.

Sean Weisbrot: Right?

Sean Weisbrot: They they probably mail each other binders.

Ray Meiring: Right.

Ray Meiring: Some some dude.

Ray Meiring: Yeah.

Sean Weisbrot: How do

Sean Weisbrot: you get to a point where you can iterate

Sean Weisbrot: at the speed that your customers can tolerate

Sean Weisbrot: where you're not driving yourself crazy going, goddamn it. I wish this would move a million times faster.

Ray Meiring: Probably one of the most challenging things to do right now, and I'll I'll tell you the reason.

Ray Meiring: Many of our customers,

Ray Meiring: they're still using AI to help them write a better email.

Ray Meiring: Right?

Ray Meiring: That's the full

Ray Meiring: extent of their understanding around what artificial intelligence can do.

Ray Meiring: So going to them and presenting this agentic idea where it does 80 to 90%

Ray Meiring: of the of the workload on your behalf,

Ray Meiring: it blows their minds.

Ray Meiring: And I say this with love and respect to them because their job is not to think about agentic, it's to think about building RFP responses.

Ray Meiring: Having said that, when you're in a new customer interaction,

Ray Meiring: no one wants to see the old stuff.

Ray Meiring: They all wanna be involved with what's what's coming down the track.

Ray Meiring: They wanna see the art of the possible, and they want that reflected in your software.

Ray Meiring: So what we started doing is our first release is into sales.

Ray Meiring: It's not into existing customers.

Ray Meiring: It's actually into sales.

Ray Meiring: And go put this out there and get some feedback and some perspective on how is this resonating with the prospect.

Ray Meiring: Right?

Ray Meiring: Can they see themselves in that?

Ray Meiring: And then we bring that back and iterate on that through.

Ray Meiring: And then we've got these kind of leading edge customers

Ray Meiring: that are very much working, you know, step by step with us, where we can put the good stuff into their hands and make sure that it works.

Ray Meiring: And I'll I'll give you a third piece.

Ray Meiring: But

Sean Weisbrot: Sure.

Sean Weisbrot: No. Go for it. Go for it.

Ray Meiring: yeah.

Ray Meiring: Yeah.

Ray Meiring: The third piece is where

Ray Meiring: in the past, we've built kind of horizontal tools and then applied those into various industries in their unique ways.

Ray Meiring: What we've seen right now is that taking a horizontal approach to the problems we solve, like RFPs and proposals,

Ray Meiring: that's really challenging.

Ray Meiring: We need to go vertical.

Ray Meiring: We need to be really specific in the problems that we solve in those use cases.

Ray Meiring: And so in the last eighteen months, we've hired industry professionals into the business

Ray Meiring: that we can bounce and can work directly

Ray Meiring: with our product teams to to make sure that these agentic ideas that we come up with, they actually are grounded in the reality of how people work.

Sean Weisbrot: I wanna take a step back first before we go further into agentic.

Sean Weisbrot: Why should businesses care about this process?

Ray Meiring: Because when they

Ray Meiring: apply this technology, call it a Genetec AI, whatever we want, It is gonna be a huge time saver that will unlock the potential

Ray Meiring: for them to focus on the more strategic human based elements of their jobs,

Ray Meiring: which in our world of RFPs and proposals is really understanding the customer's needs,

Ray Meiring: being empathetic towards what's important to that customer, and developing stories

Ray Meiring: that are going to motivate the humans that are making the buying decisions.

Sean Weisbrot: Won't the agents just be creating those stories for each other and then can helping them to understand what the humans want so that you don't really need any humans involved in the process at all?

Ray Meiring: Well,

Ray Meiring: I think there's part of it that's going to be fully automated.

Ray Meiring: You know?

Ray Meiring: Asking an RFP question like, do you have data redundancy, or do you support pro bono work, or some basic question like that.

Ray Meiring: Sure.

Ray Meiring: That could just be agent to agent.

Ray Meiring: But if you imagine that you have

Ray Meiring: a complex legal problem that you're looking to solve, right, and you're a big corporation,

Ray Meiring: are you gonna be happy with an agent pitching you the fact that they can solve that problem for you?

Ray Meiring: Probably not.

Ray Meiring: You wanna sit across the table.

Ray Meiring: Right?

Ray Meiring: You wanna sit across the table from another person that tells you, I got this.

Ray Meiring: And the agent can make the documents and can route the processes in the background.

Ray Meiring: But you're going to want to sit across the table

Sean Weisbrot: They're not gonna know it's an agent.

Ray Meiring: as that big corporation with a big problem from another human who you trust, who will tell you, I'm going to use all of my technology and people to solve your problem.

Sean Weisbrot: But why

Sean Weisbrot: why do the humans need to sit across the table from each other when the agents can do all of that thinking and all of that work and all of that planning without any human intervention if done right?

Ray Meiring: Oh, it can do all the work.

Ray Meiring: It can pull pull the document together, but it will not have the same connection with the human decision maker as another human.

Ray Meiring: Right?

Ray Meiring: Unless it's a highly transactional, commoditized

Ray Meiring: type of work.

Ray Meiring: But if there's a some kind of lawsuit that you're dealing with and you need assistance with that, you're gonna wanna talk to another human who has empathy with your problem, who's done this before, who you can fully trust,

Ray Meiring: Not just make a selection from a a smorgasbord of agentic outputs.

Ray Meiring: It's that it's that trust element.

Sean Weisbrot: How is all of this important for smaller companies that have a dream of serving enterprise

Sean Weisbrot: but have no idea what the hell they're doing yet?

Ray Meiring: Smaller companies need to think through

Ray Meiring: the strengths and weaknesses of those two entities, right, and the two entities being the agents and the humans.

Ray Meiring: Because enterprise is still going to have a big human element to it, particularly in this in this more sales type world of of what's happening there.

Ray Meiring: So what is the human strength that we really want to drive to the forefront

Ray Meiring: to free them up from the stuff that actually is the agent strength so that the agent can take care of those pieces?

Ray Meiring: But if the thought process is just agent,

Ray Meiring: it would be like the thought process being just human.

Ray Meiring: Neither of those two are a complete package without each other.

Sean Weisbrot: And I feel like the smaller companies are gonna be the ones that get into agentic work much faster than the enterprise.

Sean Weisbrot: So

Sean Weisbrot: how do they work backwards with people that aren't there yet?

Sean Weisbrot: Because if you say, oh, my agent will take care of it, and they're like, what's an agent?

Ray Meiring: I think I think the enterprise customers know what an agent is. They're they're familiar with the concepts and the and the principles around around agents.

Ray Meiring: And I actually think it's a better time than ever for smaller companies to be selling into the enterprise with agents, because

Ray Meiring: if those agents can tackle one discrete problem

Ray Meiring: and do it incredibly well, that frees up the humans to do other things.

Ray Meiring: There's a real opportunity to do that.

Ray Meiring: In fact, we've seen that in our industry where we're we're kind of midsized.

Ray Meiring: We've got these agentic start ups coming in, and they're not focusing on everything.

Ray Meiring: They're just focused on this one specific problem that the agents can solve

Ray Meiring: incredibly well, and the enterprises are engaging with them and buying into into that, that approach.

Sean Weisbrot: Why should enterprises not focus on automation instead of agentic work?

Ray Meiring: Isn't it the same thing to a large degree?

Sean Weisbrot: No. Because automations don't have to be smart.

Sean Weisbrot: They can be dumb.

Ray Meiring: Well, I I see that agents automate processes.

Ray Meiring: They just automate it with a lot more intelligence.

Ray Meiring: Right?

Ray Meiring: So like the old way of automating workflow type tools, it was very specified, declarative

Ray Meiring: in the way that those steps were laid out.

Ray Meiring: And if anything deviated from that, it had to have exception processing.

Ray Meiring: Now with agents, you don't need to be as definitive.

Ray Meiring: The agent can operate within its boundaries to come up with the best outcome there.

Ray Meiring: But the process is still being automated to a large extent.

Sean Weisbrot: I guess the reason why I ask that is because I've implemented dozens of automations into my podcast operations.

Ray Meiring: Right.

Sean Weisbrot: And I I did it

Sean Weisbrot: as automations, not as agents even though everyone on the Internet's trying to sell me agents.

Sean Weisbrot: I did it because I don't trust agents, at least not yet.

Ray Meiring: That's an interesting perspective.

Ray Meiring: It's

Ray Meiring: we see it as a blend.

Ray Meiring: Right?

Ray Meiring: We see that agents will form part of that automation process.

Ray Meiring: Right?

Ray Meiring: And it may be an agent handing off to another agent to do work,

Ray Meiring: but that's the process that's going to run.

Ray Meiring: I'll give you a real example.

Ray Meiring: If you're doing a capability statement for a law firm,

Ray Meiring: there's typically five steps in that capability statement production process that would happen.

Ray Meiring: Right?

Ray Meiring: Now each of those steps can be performed by one or many agents.

Ray Meiring: And overlaying that whole process is another agent who's driving those next steps and moving the gates along in that.

Ray Meiring: In the past, we would have built workflows

Ray Meiring: and human based, yes, no, I'm done, I'm not done.

Ray Meiring: Now we don't have to do that anymore.

Ray Meiring: It's just an agent to agent kind of approach there.

Ray Meiring: Do so

Ray Meiring: does the kind of the primary agent that overarches everything have some very definitive instructions on what how it needs to execute on the steps?

Ray Meiring: Absolutely, yes.

Ray Meiring: It does do that.

Ray Meiring: Does it have quality gates built into that?

Ray Meiring: Yes. Quality gates to check that.

Ray Meiring: But it's orchestrating and handing off to other agents to do the small amount of work or the the units of work in that process.

Sean Weisbrot: I guess my fear is that they will

Sean Weisbrot: hallucinate information if they don't have access and don't have the freedom to figure it out.

Sean Weisbrot: So for example, like, if I have an automated workflow

Sean Weisbrot: and it breaks, it just breaks.

Sean Weisbrot: It doesn't

Sean Weisbrot: like, there you know, you have console logs.

Sean Weisbrot: You have network logs.

Sean Weisbrot: You have things that you can look into to figure out, is this thing actually working or what happened, why not?

Sean Weisbrot: You have scripts you can build so that you can force it to happen again, you know, in the case that it it missed its scheduled cron job, whatever.

Sean Weisbrot: I don't I don't wanna get too crazy for people that don't understand.

Ray Meiring: Right.

Sean Weisbrot: Essentially, you have fallback systems,

Sean Weisbrot: and you know that the automation is not gonna delete your data or hallucinate a response.

Sean Weisbrot: So if you have an agent that's tasked with doing a job, if its goal for existing

Sean Weisbrot: is to complete that job, but it doesn't have what it needs to complete that job, it's not gonna error out.

Sean Weisbrot: It's not gonna time out.

Sean Weisbrot: It's gonna probably hallucinate what it needs to get done in order to finish, and then you have to trust the orchestrator to

Sean Weisbrot: realize that that is not acceptable and stop them and have them do it again, provide additional information.

Sean Weisbrot: Like, this is where my fear is. And when you just have an automation,

Sean Weisbrot: if if the automation works correctly, if the files are designed correctly, if, you know,

Sean Weisbrot: your systems if your back end supports it, whatever however you do, I use serverless.

Sean Weisbrot: You know, it just works.

Sean Weisbrot: It works over and over and over and over and over and over and over and over because you you know that that thing is not gonna change.

Sean Weisbrot: I think the only benefit of an agent is that you need some level of fluidity if your process changes, and the agent can handle that.

Sean Weisbrot: But my fear is, yeah, hallucination or access to data that you overwrite or, you know, like, OpenClaw

Sean Weisbrot: scares the hell out of me as an example.

Ray Meiring: Yeah.

Ray Meiring: That's pretty cool.

Ray Meiring: Could go down a rabbit hole on that one.

Ray Meiring: But

Ray Meiring: I I guess it depends on the type of

Ray Meiring: process that you're running.

Ray Meiring: Right?

Ray Meiring: Like, in our world, again, building a capability statement for a lawyer.

Ray Meiring: Step one in that process is do some client research.

Ray Meiring: So primary agents

Ray Meiring: asking a research agent to go and look back at our CRM,

Ray Meiring: look back at any RFPs we've sent to this person, look back at our last engagement, look for any news articles online, and produce a client research document.

Ray Meiring: In that process,

Ray Meiring: primary orchestrator agent then looks at that document and says, Hey, did we get did you get this right?

Ray Meiring: Is there a problem with the document?

Ray Meiring: Now, there's human in the loop in certain of these cases as well.

Ray Meiring: A research document, you don't really need human in the loop too much because it's just an internal document.

Ray Meiring: But when you turn that research and run it all the way through that process to the point where it becomes that capability

Ray Meiring: pitch document that's beautiful with bios and experience in it,

Ray Meiring: you need a human still to go and check that.

Ray Meiring: Right?

Ray Meiring: And you might even want that human in the loop a little bit earlier.

Ray Meiring: But the orchestration is happening to move that process along and kind of loop back if something's wrong, fix it. Because we're dealing with a lot of research,

Ray Meiring: a lot of unstructured data that needs to be presented here.

Ray Meiring: And so those agents are reading and writing and refining

Ray Meiring: a lot of that written and read content.

Sean Weisbrot: So how do you build your agents?

Sean Weisbrot: Like, are you using n a n, using MEG, Zapier?

Sean Weisbrot: Like, because, there's a lot of these different platforms out there.

Sean Weisbrot: And I feel like they all do the same, but I could be wrong.

Ray Meiring: Our team grew up on the Microsoft c sharp background, and so they're in that world,

Ray Meiring: that Microsoft world, and they're building these agents on top of those frameworks.

Ray Meiring: So the agent SDKs that Microsoft

Ray Meiring: produces and allows.

Ray Meiring: A lot of it is being built from

Ray Meiring: the ground up using those baselines that Microsoft provides.

Ray Meiring: A key part of what we do is we integrate into the Microsoft Office platforms and the Microsoft M365

Ray Meiring: platforms, because that's where, let's take a law firm, they want to operate.

Ray Meiring: So we have a very Microsoft centric

Ray Meiring: engineering approach to building these agents and deploying them as well.

Ray Meiring: What's been interesting with that is

Ray Meiring: you know, we see Microsoft's Copilot out there.

Ray Meiring: We also see a huge use of Claude,

Ray Meiring: legal specific tools like Legora and Harvey, some of these big names that are out there as well.

Ray Meiring: So while the actual core capabilities are being built with the Microsoft frameworks and the SDKs in the background there, obviously, MCP is the thing that's, you know, putting that out there and making this accessible to everything else.

Sean Weisbrot: It's interesting.

Sean Weisbrot: I interviewed a guy years ago who was building apps for Microsoft Teams,

Ray Meiring: Yeah.

Sean Weisbrot: and he was telling me about how freaking difficult it was to get anything published on Teams because they had this manual process of of review

Sean Weisbrot: for every application that could take, like, weeks or months.

Sean Weisbrot: Do you have the same issue?

Sean Weisbrot: Okay.

Ray Meiring: Still there.

Ray Meiring: Still there.

Ray Meiring: Still the same process.

Ray Meiring: They need to get an agent sitting behind that.

Ray Meiring: You know, the good news with that is it's a pain to get it there.

Ray Meiring: Once it's there, it's pretty you don't have to keep updating it through their through their offering.

Ray Meiring: You update the source code.

Ray Meiring: It goes through a review once.

Ray Meiring: If you change the manifests that they have, then you gotta go through the review again.

Ray Meiring: But most of the time, it's a one and done.

Sean Weisbrot: That sounds like, Google developers for, like,

Sean Weisbrot: like, Google developers and I iTunes developers' programs for, like, their apps.

Sean Weisbrot: Yeah.

Sean Weisbrot: But I've heard that those are a lot easier.

Ray Meiring: Similar to that.

Ray Meiring: Yeah.

Ray Meiring: Could be. I I don't have another reference, but I know it can take anywhere from a week to a month to get through the through the store.

Ray Meiring: I mean, last year, we did a we did one through the Adobe

Ray Meiring: marketplace because we work with not just law firms, but engineering companies.

Ray Meiring: And they use Adobe InDesign extensively, and so we built an app,

Ray Meiring: put it through the App Store there.

Ray Meiring: That one was a little bit more complicated, but same principle.

Sean Weisbrot: So you're building agents

Sean Weisbrot: and then deploying them, and then the users are using them how they want.

Ray Meiring: To some extent.

Ray Meiring: To some extent.

Ray Meiring: So we'll have these primary agents that deal with specific use cases, capability statement, RFP answering agents.

Ray Meiring: Those are kind of primary agents.

Ray Meiring: And the users will use that, and the agent will guide them through the bounds of what needs to be done and the best practice steps that need to take place there.

Ray Meiring: And they can access these agents through Office, through Adobe, all over.

Ray Meiring: But it's the primary agent that's driving what the other sub agents are doing.

Sean Weisbrot: How long until agents are talking to agents?

Ray Meiring: Eighteen months.

Ray Meiring: Eighteen months.

Sean Weisbrot: Why do you feel that way?

Ray Meiring: Because we've started on this journey already.

Ray Meiring: You know, we're working with, the RFP issuer type organization who sends the RFP out to have their agent talk to our agent

Ray Meiring: to answer as many of the transactional questions

Ray Meiring: as possible in advance.

Ray Meiring: Maybe just a singular

Ray Meiring: human in the loop review on some of those those questions.

Ray Meiring: Shortcut that process entirely.

Ray Meiring: It's it's already it's already been done.

Ray Meiring: It's already been worked on.

Sean Weisbrot: So what was a typical cycle

Sean Weisbrot: for the start to finish of one of these processes where it was human to human, where like, to now?

Ray Meiring: So back in the day, and this is still today, but back in the day, a system like SAP Ariba would produce an Excel spreadsheet.

Ray Meiring: An Excel spreadsheet would be sent to another to the the selling human to complete that

Ray Meiring: and then sent back.

Ray Meiring: And depending on the complexity of that RFP that's received by the seller, it could take anything from two weeks to six months

Ray Meiring: for the seller to complete that RFP. Again, depending on on complexity.

Ray Meiring: Typically, three to four weeks, of cycle time there.

Ray Meiring: In an energetic world, that process happens straight from the buying platform to the selling platform.

Ray Meiring: The selling platform does a bid no bid.

Ray Meiring: Do we really want to do this?

Ray Meiring: Is this in our wheelhouse to do it? Have we won this before?

Ray Meiring: Qualifies in or out.

Ray Meiring: It qualifies in, goes ahead and answers majority of the baseline questions.

Ray Meiring: Now it can, moves past the first gate.

Ray Meiring: Now we're into the high value discussions around the more kind of strategic elements of that of that RFP.

Sean Weisbrot: And how long does that stage take?

Sean Weisbrot: Because it seems like the the base layer should be fairly simple if both agents already have the vast majority of the knowledge they need to be able to generate and respond.

Ray Meiring: Well, the the first step of, like, the basic bid, no bid, and then answer the questions, that's gonna be days, hours.

Ray Meiring: The real

Ray Meiring: long pole in the tent there will be the human just validating that and signing off on it before it goes back in. Because that step's still gonna be important for a little while until everyone trusts that the agents are gonna get it right.

Ray Meiring: But that could be within a day that you've passed that first gate.

Ray Meiring: The second gate,

Ray Meiring: where it's more of the strategic stuff, that may still take some time,

Ray Meiring: but at least you know you're working on the good stuff as the seller and not just,

Ray Meiring: you know, you've got this RFP now you need to respond to.

Sean Weisbrot: Right.

Sean Weisbrot: Because you could potentially

Sean Weisbrot: send out a dozen of them and only get one done

Sean Weisbrot: and through through and and the sale is made, and that that could take a year.

Ray Meiring: Right.

Ray Meiring: Yep. That's exactly right.

Ray Meiring: Yeah.

Ray Meiring: And, you know, depending on the,

Ray Meiring: the industry, like, the legal industry, you you're still gonna have an RFP. It's gonna have the questions,

Ray Meiring: the basic questions, and it's gonna have the more complex questions.

Ray Meiring: Then you're gonna get shortlisted,

Ray Meiring: and then they're gonna want somebody to pitch,

Ray Meiring: some human to pitch.

Ray Meiring: So there's still that

Ray Meiring: full process that needs to follow.

Ray Meiring: We're just shortening the time of the first gate

Ray Meiring: on that so that it's agent to agent.

Ray Meiring: So we get to the really good stuff that we want to look up.

Sean Weisbrot: Should it be illegal for companies to be that large?

Sean Weisbrot: That they

Sean Weisbrot: to be so large that they need, they need months or years to figure out if they wanna buy something?

Ray Meiring: Well, my example of a month to year is something like, hey, we're RFPing for you to build a bridge, across this huge body of water, or we need to rebuild the,

Ray Meiring: you know, Hangar five of big airports.

Ray Meiring: So the reason it takes a year is because there's just a lot that needs to go into the planning of that that that RFP response.

Ray Meiring: But you can imagine how expensive it is to bid on a bridge construction.

Ray Meiring: Right?

Ray Meiring: It's expensive to bid because you almost gotta plan this thing

Ray Meiring: quite far into it. You gotta be showing pricing.

Ray Meiring: You gotta be showing, like, a draft plan on this.

Ray Meiring: This is what we would do.

Ray Meiring: If you can cut out the ones that you're not gonna win

Ray Meiring: early on in the process, you're actually saving money by focusing on bridge building that we're gonna win versus just going for every bridge that we get our people.

Sean Weisbrot: And it do you also

Sean Weisbrot: I'm just trying to think, like, if there's a way

Sean Weisbrot: for the agent to also work on the

Sean Weisbrot: the actual quoting.

Sean Weisbrot: Like, the actual okay.

Sean Weisbrot: Let me because, like, I know that you can show something to an AI

Sean Weisbrot: and say, hey.

Sean Weisbrot: Make this better, and it'll it'll come up with a a better jet design,

Sean Weisbrot: you know, that humans can like, so I imagine if any part of that process includes an AI that specifically focuses on figuring out how much it's actually gonna cost.

Ray Meiring: Right.

Ray Meiring: There are totally gonna be agents that can do the costing, the planning, the resource kind of layout on that.

Ray Meiring: That's not gonna be us, but

Ray Meiring: we'll talk to a specialized agent that's a pricing agent.

Ray Meiring: We'll go ask that agent, hey, run the pricing

Ray Meiring: calculation on this thing.

Ray Meiring: Here's five previous ones of similar

Ray Meiring: size that we've done, come up with the best pricing based on that pattern that's gonna work for us right now.

Ray Meiring: Same for design, same for resourcing.

Ray Meiring: Yeah.

Ray Meiring: It's gonna be a it's gonna be an org chart of agents passing work off to.

Sean Weisbrot: I think that part's really interesting because I,

Sean Weisbrot: you know, for the software that I I've been building,

Sean Weisbrot: I asked it to look at every API call we make and every software that we touch that it knows of and turn it into a markdown file with all of the costs and all of the plan all of the upgrade opportunities when we should consider upgrading into the different plans, what are the the the, you know, API limits and calls and all of this stuff for all of those things so that we know how much it'll cost.

Sean Weisbrot: Wait.

Sean Weisbrot: It's just me. So I know how much it'll cost

Sean Weisbrot: to run the business as it gets to a certain size.

Ray Meiring: Right.

Sean Weisbrot: It's so cool that it

Ray Meiring: And how good was this?

Sean Weisbrot: I mean, the cost to run the business right now is $50 a month.

Ray Meiring: K. Great.

Sean Weisbrot: But, yeah, it it knows, like, it it won't be that expensive with the if the pricing model I have remains,

Sean Weisbrot: it won't because, for example, like, an image generation is, like, a fraction of a penny, and I'm charging a dollar to generate an image.

Ray Meiring: Alright.

Ray Meiring: Alright.

Sean Weisbrot: And the the you know, there's a transcription API. There's the post generation API. There's the image API.

Sean Weisbrot: There's, like, a number of those kinds of things.

Sean Weisbrot: But then there's also, you know, the the database provider.

Sean Weisbrot: And so there as you're aware, there's a lot of things that, you know,

Sean Weisbrot: are involved in this, but, luckily, there's a lot of businesses out there that offer free plans for people that are just starting out.

Sean Weisbrot: And so I can essentially start

Ray Meiring: Right.

Sean Weisbrot: I I started and, you know, launched a

Sean Weisbrot: production ready software by myself in less than a month, and it cost me $50 a month to manage it. But it cost me probably a thousand dollars to actually build the software and the website and all of this stuff because I was

Sean Weisbrot: stupidly using thinking mode, which triples the output cost.

Sean Weisbrot: It it they charge you based on output tokens, not input tokens, which I didn't know.

Sean Weisbrot: So, yeah.

Ray Meiring: Okay.

Ray Meiring: But I think you hit on a key point there, Sean, because

Ray Meiring: we're still coming to terms of what actually running these agents is gonna cost us. We've got a lot of theories.

Ray Meiring: We've got a lot of models.

Ray Meiring: We've got a lot of views there.

Ray Meiring: But as usage increases on this,

Ray Meiring: we're going to learn a lot about how much it costs to operate this.

Ray Meiring: And then, of course, there's the whole pricing discussion

Ray Meiring: and scaling discussion around that, margin discussion around that.

Ray Meiring: But I think that's a key area that's still

Ray Meiring: coming to light as we deploy and use AgenTic AI more and more.

Sean Weisbrot: I think that's why people look at using

Sean Weisbrot: AI tools as like, they're they wanna charge

Sean Weisbrot: for usage rather than a subscription because they they always have profit baked into each token.

Ray Meiring: Exactly.

Ray Meiring: Yeah.

Ray Meiring: Yeah.

Ray Meiring: That that's

Ray Meiring: that's great when you're building a more technical product.

Ray Meiring: But for us to go to, like, a a head of sales

Ray Meiring: and try and sell on a token based costing model, it's such an unfamiliar

Ray Meiring: concept for them to get their minds around.

Ray Meiring: So there's a there's a transformation that's gonna need to to take place here,

Ray Meiring: especially around the cost side, cost and set selling price.

Sean Weisbrot: What's the most important thing you've learned so far in your career?

Ray Meiring: Speak to the users that understand and know

Ray Meiring: the real world use cases that you're aiming at.

Ray Meiring: I think it's great to be able to come up with a lot of ideas, but speak to those users and understand.

Ray Meiring: And I'd say something else.

Ray Meiring: I would say some things

Ray Meiring: are worth innovating around and making changes and and and trying to find the next thing.

Ray Meiring: And other things, you just need to actually stay the course on certain ideas for a long enough time period to actually see it through.

Ray Meiring: And let me give you an example of that.

Ray Meiring: And this is especially the case with with AI today.

Ray Meiring: You come up with a great idea.

Ray Meiring: Right?

Ray Meiring: You put it in front of your users.

Ray Meiring: They say, this is a this is an excellent idea.

Ray Meiring: And you start rolling this out and trying to build scale around it. And immediately,

Ray Meiring: you get nervous because it's not working.

Ray Meiring: It's not going in the right direction

Ray Meiring: that you thought it would.

Ray Meiring: And your inclination

Ray Meiring: is innovate and change your way out of that.

Ray Meiring: Sometimes, that's not the right approach.

Ray Meiring: Your right approach is just to stay the course on the original idea or slightly adjusted idea and go full board of that.

Ray Meiring: There is actually

Ray Meiring: a lot of damage that can be done doing this versus just slight tweaks to a really great idea.