Feb 10, 2026 Enterprise Brain Frontend frameworks - Transcript 00:00:00 Yeshwanth Reddy Yerraguntla: Yeah. Second goal is that. Satyasri Prabhakar Mantripragada: short uh need to have a front facing for the Yeshwanth Reddy Yerraguntla: Correct. Correct. Satyasri Prabhakar Mantripragada: application and long-term is we can discuss on what framework we wanted to Yeshwanth Reddy Yerraguntla: Yeah. Satyasri Prabhakar Mantripragada: settle on. Yeshwanth Reddy Yerraguntla: Correct. Satyasri Prabhakar Mantripragada: So let me answer your generic question. Yeshwanth Reddy Yerraguntla: Yeah. Satyasri Prabhakar Mantripragada: See design there are two aspects to design. Yeshwanth Reddy Yerraguntla: Okay. Satyasri Prabhakar Mantripragada: Now there is a third aspect coming up. In the past the two aspects to the design are okay the visual you know how does it look does it look attractive is it a nice color combination you know is it look is it pleasing is it playful is it uh very serious is it corporate is it Yeshwanth Reddy Yerraguntla: H. Satyasri Prabhakar Mantripragada: reflecting the corporate brand all of that that is the visual side of it right and um very few of us um can intuitively arrive at something that is um you know by ourselves it's very hard for many of us to um oh this is the right way to do 00:01:03 Yeshwanth Reddy Yerraguntla: Yeah. Satyasri Prabhakar Mantripragada: it I mean this is oh this looks great uh because we are very a lot of us are Yeshwanth Reddy Yerraguntla: Yeah. Satyasri Prabhakar Mantripragada: engineers and um not necessarily that that creative right right brain is not at that level some are don't get me Yeshwanth Reddy Yerraguntla: We haven't been trained. Yeah. Satyasri Prabhakar Mantripragada: wrong some engineers are extremely creative they can come up beautiful design. So, but in general, Yeshwanth Reddy Yerraguntla: H. Satyasri Prabhakar Mantripragada: uh it's okay and that is not our forte, right? Yeshwanth Reddy Yerraguntla: Yeah, Satyasri Prabhakar Mantripragada: Um in fact, if you are challenged like that, Yeshwanth Reddy Yerraguntla: true. Satyasri Prabhakar Mantripragada: you just ask Lava or Figma make and by default it'll give you something that looks halfway decent. Yeshwanth Reddy Yerraguntla: Okay, I see. Satyasri Prabhakar Mantripragada: Okay? I don't want any of us to worry about oh you know what I am generating is what I am coming up with you know is not beautiful doesn't look good because that is not our purpose for that is that you know we our design team can actually help us with establishing a style and design and it it should be done once and then that's it that's then for the entire application that's only done once 00:02:11 Prathima Inolu: Naven Navin I want to add to whatever you're saying Satyasri Prabhakar Mantripragada: Okay. Prathima Inolu: Naven so Satyasri Prabhakar Mantripragada: Yeah. Prathima Inolu: yes I completely agree with what Naven is saying u we see there are two parts to Yeshwanth Reddy Yerraguntla: Yeah. Prathima Inolu: this and uh One is while each one of us is expected to do what we want to do and what we are good at the intent is also to bring all the elements together. Right? See uh when we are calling ourselves Satyasri Prabhakar Mantripragada: Okay, Prathima Inolu: uh design plus AI uh enabled company and we know Satyasri Prabhakar Mantripragada: I don't want Prathima Inolu: how to bring both of them together in the right proportions for your platforms then that should reflect into every small little thing we do. Wherever possible, if we can automate using AI, we should. Wherever possible, if we can design and design, I re I want to reiterate the meaning the the meaning of design. Design is not aesthetics. Design is solutioning. Okay. One add-on that Dwami is extremely good at is human technology interaction. 00:03:39 Prathima Inolu: that is that is a subcomponent of design. So when we are trying to say something is not looking good, we are not trying to say uh or I want to rephrase the intent is not the intent is to uh request all the practice heads to work together. Okay. So it is not Um and somewhere I see that because we are in our cocoons uh each one of us is trying to do what we uh uh are really comfortable and good at but only when they come together is when the true effect of what Diwami can produce is going to come out. So we need to figure out how we need to figure out how all of this comes together, right? Uh in all angles. Yeshwanth Reddy Yerraguntla: Yeah. Prathima Inolu: Sorry, Satyasri Prabhakar Mantripragada: Pratima. Prathima Inolu: Naven. Yeshwanth Reddy Yerraguntla: Agreed. Satyasri Prabhakar Mantripragada: Yeah. So um just to continue on that same note again Pratima whatever Pratima said that is also true and I'm what it's not contradicting anything I said as I you know there are 00:05:10 Yeshwanth Reddy Yerraguntla: I Satyasri Prabhakar Mantripragada: three aspects is what I started with so one aspect is the visual elements and that you know best Yeshwanth Reddy Yerraguntla: dropped. Satyasri Prabhakar Mantripragada: to um so that is one but the second thing and uh and this gets lost in the translation whenever we talk about hey this is not looking good or this is not the right design is actually what is the flow does it make sense for this particular solution for this particular problem you know am I um is the user able to actually uh understand it easy use it easily does the flow make sense the best example I could give is uh you know this application called Coutillia that I you know kind of wive engineered right um you know Yeshwanth Reddy Yerraguntla: Yeah. Satyasri Prabhakar Mantripragada: um great with a lot of enthusiasm I sat down and and developed that application right um it is you know um basically because it's basically meant to replace spreadsheets and all of that and it is uh you know helps you do resource planning and all that in in almost every instance uh you know people who knew that that application was there they they looked at it said yes yes yes this is this is very useful and all of that but we're still using spreadsheets right you know Gopal by by default opens a spreadsheets 00:06:38 Satyasri Prabhakar Mantripragada: to do it you know Rakkesh also does it in spreadsheet I'm not blaming them because that application Yeshwanth Reddy Yerraguntla: We have them. Satyasri Prabhakar Mantripragada: didn't achieve what they uh want to do right all of that functionality is there just not in the way that is actually helpful to So Yeshwanth Reddy Yerraguntla: I can empathize. Satyasri Prabhakar Mantripragada: the so the goal of that application completely failed. Yeshwanth Reddy Yerraguntla: Yes, Satyasri Prabhakar Mantripragada: There's no use to that application because it is not achieving the users this thing. Yeshwanth Reddy Yerraguntla: correct. Satyasri Prabhakar Mantripragada: You you just cannot uh force people to use something that is uh you know built built that way. So that that is very f aspect is also Yeshwanth Reddy Yerraguntla: Okay. Satyasri Prabhakar Mantripragada: extremely important. I you know um I don't want to say which is number one which is number two and there's a number three also that I'll talk about. So the number two I want especially for enterprise Yeshwanth Reddy Yerraguntla: Yeah. Satyasri Prabhakar Mantripragada: brain okay number two um this this Yeshwanth Reddy Yerraguntla: H 00:07:36 Satyasri Prabhakar Mantripragada: aspect of you know how is it useful what is useful and all of that see by default enterprise grade Prathima Inolu: Namin Namin sorry to interrupt we'll bring up enterprise brain a little later if your number three is connected I want to first finish off non project uh uh uh whatever the points are then we'll get to the uh project because there are two ways that the teams are thinking whenever project is coming into picture immediately lot of things are popping up So first can you cover up all the things that are nonrelated to a project execution? Satyasri Prabhakar Mantripragada: Sure. Um yeah, permit me because I'm I'm bringing up enterprise brain as an example. Um see enterprise brain you know is chat I mean Yeshwanth Reddy Yerraguntla: Yeah. Satyasri Prabhakar Mantripragada: basically okay I asked a question that you know by default we picked the chat GPT interface. Now is that the best thing to do for enterprise brain? I I don't think we have spent enough time uh you know really thinking through and Yeshwanth Reddy Yerraguntla: probably. 00:08:43 Yeshwanth Reddy Yerraguntla: Yeah. Satyasri Prabhakar Mantripragada: understanding you know what is that so and and that should be probably generalized to a lot of the AI based projects right till now every AI based project that we had done espe except for that visual defect analysis one everything is chat based you know chatm is chat based this is chat based is chat based chatm is the optin Yeshwanth Reddy Yerraguntla: Yes. Satyasri Prabhakar Mantripragada: one IM infinitism we are by default you know is that the only way to expose AI right so Prathima Inolu: One more thing. Satyasri Prabhakar Mantripragada: uh Prathima Inolu: Uh sorry Navin I thought you were done. There was a pause. Sorry. Go ahead. Satyasri Prabhakar Mantripragada: go ahead go Prathima Inolu: So uh one another point I want to add. Satyasri Prabhakar Mantripragada: ahead Prathima Inolu: Yes, is um um every AI solution needs to be told properly to the world. What is I mean and that is your design layer. The design layer will help you your story to the world otherwise it will be all these AI solutions will be uh so many experiments that so many powerful scientists have done in the past which are lost in the dust. 00:10:09 Yeshwanth Reddy Yerraguntla: Hannah. Prathima Inolu: presenting to the world is a layer I want us to understand is a mandate not even option otherwise our story won't be sold for example off late we did so much of Yeshwanth Reddy Yerraguntla: Yes. Prathima Inolu: work presented it to consendo they are our partners but to build that credibility that we are a fantastic AI team. We know what we are doing. The presentation also has to be powerful. Yeshwanth Reddy Yerraguntla: It's 8:15. Prathima Inolu: I hope this is making sense to all of you. Satyasri Prabhakar Mantripragada: You you were a little broken up there Pratma. It was very choppy. But I think what you are trying to convey is you know uh this is in general goes after a lot of AI related projects because if it is not actually exposed well then the the value of what you did on the back end is is not really absorbed by the end user and that is true for many projects that we're seeing and especially going forward in the AI world. This is where we are staking out a claim that that AI plus you know that that AI in the AI world how do you you know design is very very critical because otherwise what you have uh in in your AI layer cannot actually be absorbed and used by the end user is the point I think you're making and so the this layer is extremely important to us and same thing the best example is the you know you can look at enterprise brain as the example right what is the best way to consume 00:12:03 Satyasri Prabhakar Mantripragada: enterprise brain is as an example so I'm not still going then the third aspect that is new that has come up and you can argue that oh it is just subset of one or subset of two but perhaps it is worth looking at it separately is this idea of okay what in the in the new world okay whether it is AI or nonI or whatever you know how users are consuming uh that uh has also changed. It is not just basically 2D screens uh keyboards uh as in the past. Now it is multimodel engagement. You know yesterday Wen that guy Wenut from SPL splashbi was making the point that you know voice based interface could be there. um uh you know but but you know uh we are also starting to call it you know experiential design you know 3Ds animations don't necessarily think of it as purely oh that is just a subset of the visual aspect number one but it is a whole new way of consuming information right you know the the 3D is not just a visual aspect because 3D because it brings another dimension there is another layer of information that you can consume. 00:13:23 Satyasri Prabhakar Mantripragada: So it is another way of delivering information. So you know with motion with uh 3D and I'm only coming up with two or three examples because that's all I know. But what I'm trying to say is because the tech is changing with AI there is a lot more opportunity to be uh um uh you know to to be able to deliver and consume information. So that we should call experiential design right and that is where we need to focus on um you know it is is it AR VR is it multimodel engagement is it 3D design is it animation I will you know I'm not the right person to say what that you know I don't even want to define it I'm saying because of the new tech the new uh generation there is a new Yeshwanth Reddy Yerraguntla: H.B. Satyasri Prabhakar Mantripragada: way of being able to deliver and consume information and knowledge and insights and all of that if we call that experiential design that is the third pillar that we should focus on as well. Right? 00:14:27 Satyasri Prabhakar Mantripragada: And we when we deliver a design we should focus on all these three aspects and see you know what is the best way to deliver that and that entire thing is design. Yeshwanth Reddy Yerraguntla: Got it. Satyasri Prabhakar Mantripragada: So uh Pratima did did you want to I mean was there anything you wanted to add? Prathima Inolu: Navin, I'm coming. Satyasri Prabhakar Mantripragada: Okay. Yeshwanth Reddy Yerraguntla: Maybe I want to hear Rakkesh on's comments on what I'm about to say. But visual aspects solutioning are straight not straightforward are not new. uh experiential design on the other hand is extremely uh thing that is possible only because of LLMs only because of the new paradigm shift of the ability to think beyond just chat interface that LLMs are able to help us generate more ideas more code in lesser time. Uh yeah essentially I feel Diwami's strength should come from experiential design itself because once you figure out that point one and two automatically will fall into place is how I feel. Satyasri Prabhakar Mantripragada: True because right now the system capabilities has been increased and how the AI is consuming the how is uh the how the users consuming the data that has generated to the AI which is more insightdriven and experienced driven right so the whatever the patterns that are exist so far are considering only the one aspect of cognitive load the user can consume so now with the the AI coming into the picture so we need to find a new patterns which really helps the user to consume the uh a lot more data and 00:16:24 Satyasri Prabhakar Mantripragada: insightful way that's where we are struggling uh to what is the right way to begin just a starting problem I once we uh have that uh how we don't I'll correct your words we're not struggling we are not spending time there's a difference right you know yesterday in 2 hours we cracked so many things so we are not struggling we don't understand the priority we have not I mean I'm not debating why you guys are not giving time I'm not not even questioning I'm bringing to the table that one we are not struggling Two, you're not giving the time that it Yeshwanth Reddy Yerraguntla: As Navinana suggested, I think we should start at enterprise brain itself to relook at it and see ask ourselves what is the best way Satyasri Prabhakar Mantripragada: deserves. Yeshwanth Reddy Yerraguntla: to envision this for ourselves. We are the end users start. I'm sure we'll have more uh definitely we'll just flow with a lot of ideas. That said, Satyasri Prabhakar Mantripragada: Yeah. Yeshwanth Reddy Yerraguntla: this is the long-term solution. Satyasri Prabhakar Mantripragada: Actually 00:17:30 Yeshwanth Reddy Yerraguntla: This meeting should also uh dedicate some time for the short-term solution. Satyasri Prabhakar Mantripragada: sorry I know Prabhakar and Yashwan you both are on short-term and long-term this is my short-term solution I have a bigger long-term solution this is something I've been asking wer Rakkesh when I u in some sense yes I've been trying to request you also to work with Rakkesh and Wut this has been going on for the last two to 3 months if I'm not wrong. We are at the verge where I'm signing a blue yonder contract today tomorrow I'm sending a proposal and that requires this capability and if I'm going to send the proposal and if it get accepted immediately they'll expect this to be done for them at that point I can't one say we don't we are not there yet two we we are still we we still have other challenges but at least by the time none sons the preigns the contract right I need people in this room to be confident about what we are proposing to them right so for me this is shortterm I have a much much much bigger long-term which which we will get there I agree we need to have that we need to deliver those excellent uh designers it's all fine I'm not contradicting Right. 00:18:59 Satyasri Prabhakar Mantripragada: But what I mean by short-term is that we need to have a phase for the application first. I want this to be the phase. You don't mean how long it will take. But I want I don't want an intermediate phase anymore. Understood. But um there is something called the people need to experiment and research on what fits best to accomplish those designs which technology or which frameworks implement can be implemented. It takes some time. So it may take few weeks to months. I don't know. No, I'm challenging you and saying it should not. I have talked to many people they are saying it won't take just a matter of a couple of days. So you are on the other side of the spectrum where you feel like it will take months. I'm on this side of the spectrum where I'm challenging and saying this might take just a few days. All I need is all the big brains to come to one room. 00:19:47 Satyasri Prabhakar Mantripragada: Here the problem is not probably the same conversation what we had yesterday. If we had the Friday before by now it would have been solved in my help right in in lots of ways I'm requesting all of you for this I know we all have other things but what I'm trying to say is if you don't crack this now we are already behind the scenes you I mean Rakkesh and you guys tell me we have been talking about this but yesterday when you saw flourish website is when you realized oh there are so many other people doing and I'm not pushing why didn't we do in the past I know I I and I respect all of our reasons but what I'm saying is now is the high time and I'm I I I am I I I forced and I brought all of you into the meeting yesterday because I know that it's high time if you don't do it now we will be slow I know I'm pushing all of you as well but I have to I'm sorry I just missed one context what is is what is the debate about will it take 2 days or like it will take can you open studio uh one minute I'll share the So wind powerhouse Nobel Prize whatever these right these are the examples that Max from blue water sent me and asked me your design team as well as your engineering team have the capability right. 00:21:44 Satyasri Prabhakar Mantripragada: M okay not exactly these but on these lines okay that's the reason they're asking motion graphics they're asking do you guys know the tools that I used to implement what are the things and so this is what they're expecting them in more or less not exactly this but based on the applications that they have they're expecting these kind of interactions analytics uh population pyramids. Yeah. First predictive analytics. This is a graph. Now I want to scenario creation. So you take the point and you draw something then it'll and that is the indicator of what what is the deviation interactive. So remember I've been asking I mean we have I've been continuously saying we need more interactions on the graphs we need more visual uh so these are the things population graph this is predictive analytics now as of 2025 this is where we are uh and by 2050 this is how it will be. This are predictive analytics. He gave it like a video. 00:23:21 Satyasri Prabhakar Mantripragada: Now assume it's a slider where you're changing the timeline accordingly. Whenever you change the slider value it'll reload. Now it is being animated for lack of a better word. Yeah. So these are the things that none is expecting. So we need the front end engineering teams to be able to do this. Now I don't know whether it is done in react. I don't know I don't know anything about this. Understood. So these are the things that I see this is AI first design and some of these models will be driven by AI it will pick which pattern and even to draw the line see earlier design UX then UI then front end engineering a process was in one way now with AI first in fact yesterday I was telling women you put up all the patterns patterns because these are the patterns that AI can support. Now UXU they need to probably pick one of the patterns rather than they coming up with a pattern because you don't know what whether that pattern can be supported or not. 00:24:44 Satyasri Prabhakar Mantripragada: So unless all the practices come together and discuss and brainstorm this uh we will silos. Understood. Um generally like you know businesses and what I I wonder if Mike Max and Nanu are asking you is hey you need to be able to imagine and design these kinds of things implementation you know I didn't go in those but what is harder actually is to imagine that experience and then design it especially with nuns though you won't have time to experiment that's the whole condition right I'm not questioning you who is working how they are working what they working I want outcome in the timeline I give you this is the condition that's what I have been expl explaining to all of you since Friday. Okay. Now you can debate and argue with them whether you are reasonable or not. After I can buy one day here or one day here. Now the way our first of all our mindset that it will take two months to start is my understood. 00:26:17 Satyasri Prabhakar Mantripragada: Then we will not we we won't we won't be able to do this. Yeah. We won't be competitive. Why should they pick us? So we have to basically be the boutique miracle working company, right? Because the only reason to come to us is because we we are that boutique company that can do whatever you want we can do. Just a thought can we have a separate research wing establishes for researching on these topics. So whenever a project comes immediately there is an outcome that is defined and you can just uh use that. There are two parts to technology feasibility and execution. The other part to it is you know they need to be able to imagine that interaction in the first Yeshwanth Reddy Yerraguntla: Yeah. Got Satyasri Prabhakar Mantripragada: place right they need to be able to say hey I am going there is a Yeshwanth Reddy Yerraguntla: it. Satyasri Prabhakar Mantripragada: logistical uh you know this thing how best to represent it just regular chart is tama like you know how to design an animated chart like this what would work for this use case what is the best representation for this use case Imaginement then you can come to that but I you know they also need to be uh ramped up on okay you know if how do we design 00:28:00 Satyasri Prabhakar Mantripragada: this in this motion graphics format and we don't have that what I was thinking is at the start of the year or somewhere when you the direction that this year we are going to hit these verticals. So somebody maybe for example from design team would analyze what are the problems in this industry these verticals what kind of data sets can I use so how do I represent these what are their common problems what would be the solutions so if we can so the designer also gets a dedicated time to think and digest on the problem and think about the solutions so when we are in a rush There is a trial and error that we are hitting we always bring ourselves into I'm sorry to say this okay why again I'm not questioning even jan we knew we had one week we brought ourselves into 11th hour yesterday and when we bring ourselves into career and when it comes to research and in fact AI team so far has been most of our AI is research in our head in my head they'll be only able to do the how the technology part the creative part will also have to engage in somebody that's one of the key challenges we have Right. 00:29:40 Satyasri Prabhakar Mantripragada: They don't we don't have the right um that's why he's interviewing almost two people every day these days just to hire the right people. I think once we have the right people we definitely can do that. It's a long-term date. I mean this is something I think we have been talking like even Rakkesh's time also on strategy my time we discussing all of this so it'll fall in place. It's just like now all problems seem like are together in one shot. I wouldn't say problems challenges and good challenges too. Okay. What's u what's thema what are we discussing conversation yes do you want to give some when this conversation came up or you want how do you want to take this Yeshwanth Reddy Yerraguntla: Um now I want you to connect back to the second part of the um second and third points that you talked about in when when we say design. What do we mean by design law? One was the experiential aspect and the solutioning aspect. 00:30:57 Satyasri Prabhakar Mantripragada: Okay, Yeshwanth Reddy Yerraguntla: If nuns and other people are asking can you generate these fancy dashboards with AI the answer should be yes because we can do it anywhere. I know we can do it. I know AI can do Satyasri Prabhakar Mantripragada: I am uh okay. Yeshwanth Reddy Yerraguntla: it. Satyasri Prabhakar Mantripragada: So, help me understand. What do we mean by can these be done by with AI? Yeshwanth Reddy Yerraguntla: What is these? Chapan let me just share my screen at a very Satyasri Prabhakar Mantripragada: Uh Yeshwanth Reddy Yerraguntla: I know what 2,000 ft view or whatever the term is the thing that is expected out of AI is when someone is giving their intent it is converting it into something called as a spec specification that needs to be consumed and uh generated on the front end in the form of a design. Okay. I can give you two examples. Okay. Um what let me hide this guy. I don't know if there is any graph in one of these things but you saw few graphs isn't it like when I ask a question it was generating a interesting 00:32:14 Satyasri Prabhakar Mantripragada: That's good. Yeah. Yeshwanth Reddy Yerraguntla: diagram optin it was generating a supply chain diagram in uh Salesforce it was generating dashboards in this example that I was working on today morning when you spoke about the widgets this is also a different kind of a specification in saying uh okay give me a complex whatever with some interactivity and it it gives something I'm not saying this is good or anything but the fact that you are constraining the chat to do a limited set of actions by saying you are you have a canvas at your disposal in the canvas you can create HTML elements you can create these diagrams these diagrams belong to so and so library you are specifying what LM can do at which point you're constraining the LLM to uh give its answer in the form of some of these standard specifications only. So this is the common pattern that I observed in all the design all the ex all the user experiences which were going beyond chat beyond text. Okay. So that is the first thing I wanted to talk about when I say something is possible with LLM. 00:33:32 Yeshwanth Reddy Yerraguntla: This is what I mean that once we Satyasri Prabhakar Mantripragada: You're you're saying um Yeshwanth Reddy Yerraguntla: have Satyasri Prabhakar Mantripragada: dynamically generating a UI um um where you know AI is uh sort of able to Yeshwanth Reddy Yerraguntla: correct Satyasri Prabhakar Mantripragada: uh dynamically generate a UI how it is generating okay I'm not we are not even saying it is based on a chat it is based it is deciding what the intent is and then therefore you know then the LLM will will generate a spec therefore it can generate uh sorry to interrupt I I have a point here um Yeshwanth Reddy Yerraguntla: Yeah. Satyasri Prabhakar Mantripragada: uh Asia and uh hear me out on this. I was mentioning this yesterday also but probably only to Rakkesh. I don't know if I was mentioning this to the entire audience. Uh I am breaking down the solutions um that are in the world right now. Digital solutions that are in the world into AI first uh for lack of a better word design first but it is end of the day user first. 00:34:45 Satyasri Prabhakar Mantripragada: Uh third one is tech first. Okay these are the three categories I'm breaking down all the digital solutions that are there in the world right now. We agree. Do you have any more categories you guys want to add? Good. Okay. So when it comes to design first n user interactions and what user intents and user wants there the intent is user knows what he wants or user has more control over the stuff when it is user first user wants more control on the product. Okay, that's the design first or user first. the AI first one of what Yeshuant is trying to say where the AI layer or the LLM whatever you're Yeshwanth Reddy Yerraguntla: sitting there. Satyasri Prabhakar Mantripragada: calling it will decide this is best for the user and gives it okay tech first will be where the technology the spend the cost all of this drives the solution more than AI or use this is how I broke down solutions here tonight. 00:36:17 Satyasri Prabhakar Mantripragada: Yes, you with me. Yeshwanth Reddy Yerraguntla: so far. Satyasri Prabhakar Mantripragada: Huh? So, Yeshwanth Reddy Yerraguntla: Yeah. Satyasri Prabhakar Mantripragada: what Yashwant is showing is AI picking up what is right for the user. Yeah. So, in there were three three conversations in the room. One is if I were to automatically pick one of the patterns, then how is that architecture done? M and in enterprise brain I felt it has to be AI first. Mhm. That is where I was asking Rakkesh, Yashwan, Prabhakar, all of them, do you believe that enterprise brain has to be AI first? Uh if it is AI first then how will you build the credibility of the user? And AI is deciding on your behalf, right? And the trust that AI has to build for the user has to be a lot more because your user is not decided. User will feel like I don't have the control but it is almost like your uh Tesla car. 00:37:25 Satyasri Prabhakar Mantripragada: People trust Tesla to the precision. Uh did I did I I don't know if I mentioned I mean this is this is a true story. I don't know who mentioned I'm forgetting the name right now. Subash. Subasha is the car crash at a the accident one. So one of his my friend's friend or m's friend's friend are subash there. Subash, Subashkar, Subash, Subash is driving FSD. Then probably that one I one girl, one lady, I forget who it is. She was driving the car. Uh there was a car coming at high speed and was almost crashing into her. If it would have been a regular car, she would have been spotted. That was the speed at which the other was car was coming. and she didn't the I don't know what inside that Tesla it is called they call it some system huh FSD uh FSD FSD took over she didn't even have the control nothing she was just sitting there FSD took over changed the direction in a precision it found some open space outside of the road went it it it ended up hitting but not at the same 00:38:45 Yeshwanth Reddy Yerraguntla: Everything has Satyasri Prabhakar Mantripragada: impact and immediately called 911 and kept her safe and Yeshwanth Reddy Yerraguntla: Was Satyasri Prabhakar Mantripragada: I exploded everything ensured she was fine and people are people trusted love because of that FSD they built that trust once people build that trust imagine you not having control on your car I could not Yeshwanth Reddy Yerraguntla: he Satyasri Prabhakar Mantripragada: imagine but if if FSD is going to save my life and it prove itself Not once but again and again. Yeshwanth Reddy Yerraguntla: not Satyasri Prabhakar Mantripragada: I'm okay to give my life I mean the controls. You guys are understand AI has to prove itself somewhere design needs to ensure that we are able to bring out the AI capability that in my head is AI first design. So far with me Yeshuan and rest of the team. Yeah. Yeshwanth Reddy Yerraguntla: Yeah. Satyasri Prabhakar Mantripragada: To do that first AI should have the capability to say I know what is right for you. Then design is a cherry on the top. It says hey trust. 00:39:59 Satyasri Prabhakar Mantripragada: It knows what it is doing for you. Just blindly trust. And these are the different ways or the different parameters where you can trust it. Right? This is one aspect. The second one in user first design user in this case user needs to have control. If I go to manufacturing and do first they will not like it. I they like to have control. Sorry. Go ahead. No no no. There in that case user should feel like he is driving everything. He is the one who is clicking. He is the one who is asking. So that design in my head will be slightly different. Technology this thing is all about okay somebody picks certain Azure AWS blah blah blah they have some limitations and we design and all yesterday in Jenna you were saying something on those go ahead sir. So if we take enterprise brain or AI first design right um I and because I'm I have the enterprise brain I would speak to enterprise brain see there is a context for each enterprise brain while we are saying enterprise brain is actually multi-source fine let me take one source at a time because there is a source there is a context to it right So because there is a context 00:41:30 Yeshwanth Reddy Yerraguntla: Internet. Hello. Satyasri Prabhakar Mantripragada: um we didn't turn on slide. Yeah. So because uh enter so because for each source there is a context while we're building enterprise brain for that context we can tell enterprise brain this is the context this is sort of the typical uh things that user care users care about now hear me out right while it is different for everybody can you come again I think see enterprise brain is multissource if I take enterprise brain as a context enterprise brain is multissource but when we are building enterprise brand for each source we know what the context is for that source right we know that you know if I'm going after salesforce the context is sales revenue pro you know projects you know what what is the pipeline you know what how much progress am I making what is my expected revenue all of this is the context of enterprise brain you can always teach enterprise brain for salesforce this context if it is enterprise brain for email the context is different. 00:42:36 Satyasri Prabhakar Mantripragada: So then you can teach if the enterprise brain for something else is some different you teach. What is the context for that? Because the context is this you know AI because it has that general knowledge because of LLM it can also say oh typically in this context what do people care about but you can also train that hey this is what typically people care about. Fine stay with that. So if we are saying enterprise brain for Salesforce. Now imagine enterprise brain for Salesforce combined with email and chat. Let us just take that as an use case. Right? You have already taught enterprise brain what is the context for enterprise brain with email. Enterprise brain with chat and salesforce. So the moment you come on to enterprise brain enterprise brain knows that the context is sales. So typically people care about what are the the latest uh projects, what are the latest uh this thing, what are the latest things in the pipeline etc etc. So imagine that it's it it automatically says uh you know here is what happened in in the latest information you know latest in Salesforce you know there are two leads recorded and by the way there is a chatter in the email and uh your chat groups already about this particular account or it knows that by the way this 00:43:59 Satyasri Prabhakar Mantripragada: particular company that is contacting you this person was at earlier at this uh company and had contacted you two years ago and you tried to do a project with them and because that all of that context is in the email it knows right and so that is the that is the power of enterprise right because it is able to cross connect and say this is what you want to know trust me you want to know this okay now let's say in my operational role I say look I generally am not interested in sales information even though in working with sales. The only interest I have in Salesforce is um I just need to uh track which verticals we work with. That's the only thing I care about. I can tell enterprise brain that I generally am not interested in this. Don't show me this information. Now it has learned and then it it adapts because now it is personalized to you because you have already told it. It is kind of coming into the userentric design where we don't decide what is for us. 00:45:06 Satyasri Prabhakar Mantripragada: User first case shift shift but it is still AI first because you have told it it has learned and it is still AI is deciding then what is right for you because you have told it. So it mixes the information that what you have told with what it is thinking that oh this is how to connect because it knows the connection. So in my in my head right now this is wrong. Okay, when Praaka is asking this is long term what okay that's that's debatable between all of us but in my head at least the reason is I want to tell the world that design plus AI we mastered it the only way is by ensuring is representing enterprise brain is first dealt with and done then I go because each person's requirements are very very different. NSAP something something so Oh, I thought you were canceling it. But I could I couldn't cancel it. Okay. Can you move into that room? We are moving. 00:46:35 Satyasri Prabhakar Mantripragada: Give give us five minutes. We moving into another room. of course. Hello there. This goes to get started. Now what are your concerns? Where? Where? What? What are your concerns? What are your challenges? You can hear us now. I think now we can. Yeshwanth Reddy Yerraguntla: I was talking about mute concerns challenges as I showed the diagram doing something is not a difficult but what is that we need to do is the difficult Satyasri Prabhakar Mantripragada: Okay. Yeshwanth Reddy Yerraguntla: part this this once I know this I can reverse engineer and say okay this is what I have to instruct the LLM and uh hence we can prove uh the world that we can create complex designs But what is that complex design that we want to demonstrate or set of complex designs? Satyasri Prabhakar Mantripragada: Yeah. You're saying Yeshwanth Reddy Yerraguntla: If the the requirement is vaguely saying I want everything that is in flourish.studio to be possible, 00:49:51 Satyasri Prabhakar Mantripragada: do Yeshwanth Reddy Yerraguntla: I can take that also as one input. But exactly what is expected on the screen to be visualized when you're talking with AI is not clear. That's what I Satyasri Prabhakar Mantripragada: I think yeah I think all of us are together figuring it out correct. Yeshwanth Reddy Yerraguntla: want. Satyasri Prabhakar Mantripragada: And yesterday was the first meeting in that direction. Yeshwanth Reddy Yerraguntla: Yes. And so that is what I that is my challenge like technically there's nothing challenging from my side. Okay. Once I get the specifications I'll do everything possible to get it Satyasri Prabhakar Mantripragada: Cadence one Yeshwanth Reddy Yerraguntla: done Satyasri Prabhakar Mantripragada: second on this sort Yeshwanth Reddy Yerraguntla: please. Please. Satyasri Prabhakar Mantripragada: Can Yeshwanth Reddy Yerraguntla: Yeah. Satyasri Prabhakar Mantripragada: you make sure they're getting to all right so what is the ne what is the next step I mean are we how close are we to defining like a enterprise brain AI first enterprise brain UI so there are three practices heads and one delivery head, right? 00:51:47 Satyasri Prabhakar Mantripragada: No, no. Three practice heads and one delivery head. One, two, three. Four. Uh, he's also a practice head. Well, for this in the a delivery manager and a delivery manager and a delivery manager and a delivery manager. Whatever number of four delivery managers and four practice. You're making my point even much stronger. Yes. With so many digal in the team, why the hell are we even having this discussions? Because we need one second. My request yesterday was Rakkesh looks at it from the design lens. Ashwan looks at it from an AI lens. Winkut looks at it from front and engineering lens. We all brainstorm together. If you have to half an hours, we need individual time. We do that individually. Together we come and say this is what I discovered. This is what I discovered. This is what I discovered. 00:52:37 Satyasri Prabhakar Mantripragada: Now how do we stitch all of them together? things will move faster is what I have been trying to say. Yeshwanth Reddy Yerraguntla: Okay. Satyasri Prabhakar Mantripragada: This is what I mean and this guy is good at tools. He's the one who discovered whatever that is what I want. I discovered this exciting news. You gave life back to me because now stress level two weeks put up an extremely I put up a face and I have to that's my job as a CG but then I don't know and then on top of and bomb will blast in the morning right and then the sense of urgency my only request to all of you is please understand the sense of urgency we are in and I feel I have given all of you enough time I don't want you guys to fail let me put it this way I know this contract with nuns is going to get signed. I know that. Okay. The minute it comes, you don't deliver. 00:54:16 Satyasri Prabhakar Mantripragada: You lose your face value. I don't want anyone of us to fail. We work extremely hard and I don't want us to fail. So problem not that all of you are not experts or you guys don't realize a problem prioritization sense of urgency on certain things don't apply your regular processes to things that are that sense of urgency canva flourish see I needed a way to show there are other ways possible because this is especially I got excited about that predictive thing. That is what I was asking. That is exactly graph local is what I was expecting. Right? But he brought it to a next level where selection I'm happy with that not but that was something I was envisioning and see my vision come there was nice in one way but I also felt slightly be feel bad that it wasn't Dwami who did it. Okay. So again I'm asking how far away are we come coming up with the enterprise brains UI you know then enterprise brain clear. 00:56:05 Satyasri Prabhakar Mantripragada: Okay. Okay. Because enterprise brain project plan or timelines. This is war zone for me. Okay. War zone of the the heads of practices. Okay. Coming together and saying for AI first kind of platforms this is how the process will be. Okay. For a user first platforms this is how the process will be. For tech first this is how the process will be. This is verticalized right horizontally what is experiential design and AI AI first design what is innovative design from an AI perspective what what I don't know what that I don't know then from a tech perspective what is it that you require for this model let me rephrase short term you have a critical you have promised to show enterprise brain to some number of people you know either it is NSL, it is somebody else, it is Sam, you know you have promised to show enterprise brain right and there is no good we feel that there is you know the it is not impressive it can it has to be better because it is I understand from because otherwise they're not even they're not even appreciating the question and answer because question and answer is There is no they're not seeing the value in question and answer 00:57:40 Satyasri Prabhakar Mantripragada: right reaction was also but our people don't know what questions to ask so how do they derive value from it right so that is so how do we deliver value in an AI first solution because if you always say oh you ask questions it'll answer anything I don't know what to ask so if I don't ask any questions it won't deliver any value to me then what value are you delivering So we have come from that aspect right. So and then so there is a short-term immediate need of hey we have to deliver an AI first design for enterprise rate. It may not be the long-term end state of what an AI first product uh UI user experience will be like but keep that aside. What is it for enterprise man? That's an immediate task. We need to deliver that within a week, right? So I need that now. Within a week you can do it. I I believe anything can be done within a week. 00:58:42 Satyasri Prabhakar Mantripragada: We need to actually start believing that, right? Because with all of that AI generation, yes, of course, if you have so much, you know, interactivity and all that, maybe we just do it with an SDK. I'm not saying you have to write every line of code from scratch, but you got to be able to demonstrate. How do we do that? Right? So for demonstration purposes for this thing, we should be able to build something within a week. But if it is defined first, so where are we with that or enterprise way? We're not there. We're not closed yet. So when can we close it? When can we target to close it and and you know spend I don't want to spend more than two hours. So you you can extend it to okay what is the future direction for AI first user experiences. Please solve my short-term problem first. If you focus on the long-term problem and the short-term problem we will never be able to deliver it within the next week. 00:59:49 Satyasri Prabhakar Mantripragada: and you have commitments that you have made to say that I need to show them the value of this. So let's work the short term first and then extend it to the long term. Okay. So short term when can we sit down? What did how far what did you do yesterday? Yesterday you predominantly talked about the long term. We discussed about the design pattern patterns. Oh, what do you mean by short-term and long-term? For me, because what I know they have a short term. What? For me, my short-term goal is what is a great demonstrable user experience for enterprise brand. I don't want to constrain it by saying, "Oh, this can't be done. I I want you to define what is the ideal most ideal, you know, user experience for enterprise brain." I am challenging ward to see how we will be able to deliver it and if we find exceptional challenge yeah because that is the tech right in eventually we have to deliver so okay between yes and wenut we have to see what part of it we absolutely cannot deliver because that is a much longer term then we'll come back and say hey can we adjust this piece but don't mix the two let us first say what shortterm what is the best user experience for Enter President Yashwan 01:01:15 Yeshwanth Reddy Yerraguntla: I am agreeing with you. Satyasri Prabhakar Mantripragada: Go. When can we do that? We can do right now. Anyway, we already started learning on it. We can do right away. Okay. here. We need your guidance and direction. What is it that really the enterprise brain because I you know I you just heard what I said earlier. Yeah. Which point of what you said uh there I was saying this is what I have in my mind enterprise brain there is a context with which we train. So in that context we we tell the enterprise brain that hey generally because this is the context this is all you need to work with. If I don't like that then I will add on or I will start asking oh show me this show me that based on that it will learn my pattern and then adjust what it shows me tech I'm not the right person no I I freed you up from tech. 01:02:29 Satyasri Prabhakar Mantripragada: Okay, two things. One, there I need us to take first of all, I'm not aware what is a complexity, what is required and all of it. But from a design perspective, can I set up again? Don't start with because see I am not you I'm bringing it back. Can I finish my k I don't because I I set it up first. Don't even bother what is possible what is not that is wards and no for this week I'm saying even for this week even though I'll drive and then all of us have to agree to it if we find an exceptional challenge that we can't deliver one piece we'll come back because we don't even know what we can deliver what we absolutely that I'm okay but starting mindset whether and like I'm really telling my challenge with Yeshwanth Reddy Yerraguntla: Yeah. Satyasri Prabhakar Mantripragada: people in this room is to convince that this is important no are we all convinced Absolutely. Because I am saying you No. Yeshwanth Reddy Yerraguntla: Aka I'm desperate to hear from you what we can do in the next one week. 01:03:28 Satyasri Prabhakar Mantripragada: I no no no no no no no no no no no Yeshwanth Reddy Yerraguntla: Not one week, forget one week. I want to see what is that best thing we can deliver. Satyasri Prabhakar Mantripragada: no per enterprise brain in me enterprise brain then you know I will challenge yeswant and wat and Yeshwanth Reddy Yerraguntla: Yeah. Satyasri Prabhakar Mantripragada: myself to see what how can we deliver that in one week if we can't absolutely deliver it in one week okay eight days then we'll come back and ask you so here is how I will break the teammate bin and me will be our side which is the front facing we will break it into two parts we will only be working on AI first and user first and we have to go back and forth otherwise we won't be able to do the right things Yeshwanth Reddy Yerraguntla: Yeah. Satyasri Prabhakar Mantripragada: Navin Ward and yes you guys be on the tech side of it where you're Yeshwanth Reddy Yerraguntla: Yes. Satyasri Prabhakar Mantripragada: building okay Prabhakar you need another person or or you're a single army force I need you to be the one who is saying um AIQA AIQA whatever that is because one of the key things I'm observing is same problem is creeping into AI right now like whatever our reasons are but I'm seeing that when we are delivering it has to have a certain quality so AI to 01:04:50 Satyasri Prabhakar Mantripragada: the okay so that is where I need you and the delivery part of it Yes. Okay. Done. So when are we getting the user experience? We need see we three will discuss we come up with something. We need another meeting in the evening where we are Yeshwanth Reddy Yerraguntla: Oh my Satyasri Prabhakar Mantripragada: presenting. Yeshwanth Reddy Yerraguntla: god. Satyasri Prabhakar Mantripragada: This is what we we came up with. Now in AI first AI has to drive it kada. So we will come up with patterns or what what are you expecting from us? Do you have some expectations? Because you asked me to drive. I'm driving it. But if you have any expectations, you tell and I'll follow. See, Yeshwanth Reddy Yerraguntla: Was it on me or like I was I'm listening aa Satyasri Prabhakar Mantripragada: no, no, no, not you. Sorry. I don't know what is expecting. I'm asking Navin what are you expecting? 01:06:01 Satyasri Prabhakar Mantripragada: See again you coming up with oh this is a pattern to show graph this is a pattern that's not pattern and you're looking again at visual pattern there are there are you in the context of a problem what could be the right solution is what I'm calling as a pattern okay please extend that for a step and say what is the for the problem of enterprise how do you do that is an implementation detail. So you guys tell we have to have the discussion right. Okay. Yeah. I I I am agreeing that I thought you would involve us even earlier but he has to go to sleep. Okay. Sure. Sure. I am more than happy to involve you in Prabakar may not be available until evening. Okay. That's why I said evening. Sorry. Evening. Evening we'll sit again. You you'll come with patterns and evening we'll sit again and then nail down the the user experience for enterprise break. 01:07:18 Satyasri Prabhakar Mantripragada: That's how you're seeing it. There are three parts to this one. There are three parts to this. One is recognition of the patterns, identification of the patterns. pattern not these are complex patterns that we talking about like query while you're going inside a query like Okay. So the way we will approach Naven is there are same designs we will be approaching and there is uh uh description layer, diagnostic layer, insights layer, prediction layer and prescriptive layer right follow. How do I take it all the way to prescriptive? This is one one way one approach patterns because it's a it's a loop within a loop and saying I have to come back to you guys was telling me query the query it it becomes expensive so we need to understand patterns what is the expense I don't know and I'm just I don't know the technicalities agnostic of AI agnostic of whether front end can do it We will do those patterns. Sure. 01:09:03 Satyasri Prabhakar Mantripragada: We will include Wat because he's here only and we'll ask him front end can do it or not. No no no because that again will be based on what we know today. Hey based on hey this is the challenge. Can you do it I want then we will go and spend that you know few hours to determine what is possible in a week what is possible in a month. Unders. So this is one approach I have in my because if you ask up front then we will only be able to tell you what we know today and then that you know with just this amount of research we may be able to do more we don't know. Yeah. So this is one one approach to the design workshop that we are going to the other approach is uh UXUI experience and then innovation. This is another framework I'm going to use for our patterns in UXUI. They'll be like basic experiential design. 01:09:58 Satyasri Prabhakar Mantripragada: The lowest layer is uh transitions, animations. Like if you look at this one, uh just transitions. These are just nothing but transitions. These are transitions or animations. then micro interactions. So the lowest of the experiential design the highest of the experiential design will be that uh graph predictive analytics graph which is like interactive then immersive we have to come up that is another one. So innovation experential layer pnovation what is innovation none of us have an answer to. So that is another uh pattern that we what is expected of us when we meet today evening we will we what our thing is enterprise brain on salesforce this we'll do this as research then we will take enterprise brain as sales on sales force yeah consider that the power of enterprise brain is most when you have multiple Yeah. So if you don't include that as part of the thought process then we'll be limited by a single source. Can you then in that case you give us between prabaka give us about 30 uh questions that because we are going to do this research asking us to come up with that questions also. 01:11:43 Satyasri Prabhakar Mantripragada: If you give us the questions then we can map to it and we will that will be our base. I'm not saying we'll limit ourselves to those questions. That will be our base based on which we'll build the solution. Whatever solution you can if you give me those 30 questions or 50 questions, 100 questions I I don't know. questions. Uh okay. Okay. I mean I'll give you five. I can't give you 30 also. Uh don't give like and I cannot give you please. I'm not I'm not asking you alone right because you said it is powerful with multi-ing I am not at least thinking in that direction right now and nor I have the bandwidth in my brain to think like that because I'm on the creative front right now I need somebody on the logical front I am I'm saying okay I I'll honestly ask you guys if you can think of that complex scenario that makes sense please give as many questions as you have. 01:12:58 Satyasri Prabhakar Mantripragada: Okay. Uh Yeshuant Rabhakar wanker can I request you this now is there for half an hour. Can all four of you we three will sit here four of you move into a different room and come up with those complex questions right and then it's not complex question there's a scenario because it's not a question and answer session right it's a scenario that whatever use cases or usage scenarios give me those 30 us scenarios okay let's Okay, this is while you're doing that one right another thing is especially nuns requirement it may not necessarily be driven by AI all the time what kind of examples he sentes question started with one thing yeah I mean see these are the examples that uh this guy sent I don't know see that is my challenge that I don't know that we know that what is the in what is valuable in that enterprise right okay so I have I always end up with a couple of only you know minor questions same but it's but you know let's see if we can do that we can connect also but I can connect a link same link We eating the wizard dog and 01:15:25 Prathima Inolu: So wait and can you guys get started and start discussing? See think of what is valable. commitments 10 minutes assume that this team this meeting extended just going to that immediately come I don't have time so you learn I'm logging of you are Yeshwanth Reddy Yerraguntla: Yeah. Prathima Inolu: going Yeshwanth Reddy Yerraguntla: Yeah. Yeah. We'll come back Satyasri Prabhakar Mantripragada: Yes. Yeshwanth Reddy Yerraguntla: with Satyasri Prabhakar Mantripragada: So see enterprise brain so enterprise brain by definition is sit sit sit I'm not sitting is is valuable in a multi-source setting right because single source questions you know even multource everybody's thinking of enterprise multource also okay how do you extend it from a chatbased interface how do to deliver that user experience because enterprise brain products everybody is on the same bandwagon. It's not that we are oh uh we are pioneers in this space kadu everybody is on that same thing that oh I I will integrate all of your sources so all of your knowledge is but how do you actually expose that that is really please do not think that 01:17:06 Yeshwanth Reddy Yerraguntla: Honest. Satyasri Prabhakar Mantripragada: enterprise brain is unique and we are the only ones coming up I I I you know I mean I I hope you're also seeing that right and everybody Yeshwanth Reddy Yerraguntla: Yeah. Satyasri Prabhakar Mantripragada: like wisdom.ai AI is all about enterprise brain for you know they're going after custom databases but what is the immediate next step they'll start integrating other sources multiple sources together so the power is in combining Yeshwanth Reddy Yerraguntla: Yeah. Satyasri Prabhakar Mantripragada: sources right and that also how best are we able to deliver it right you know that orchestration layer that uh orchestration layer and there being able to understand the question or the problem and then saying okay what part of information should come from what source and combine then presentation is the final because then the user experience or that is the those are where the differentiators come but everybody is sort of doing on the same bandwagon of enterprise they're calling it things are different but enterprise so what you know what are the things like you know from a example questions let us say I am watching enterprise brain for um Salesforce and we have um uh uh Jira and we have uh let's say cautilia uh um email and a chat okay let us say these are our sources okay now can we compl come come up with complex scenarios that only enterprise brain will be able to answer yesterday I gave one example Example too when he was asking the same question there are several agents buy every 01:18:58 Satyasri Prabhakar Mantripragada: product so why should we use enterprise one example could be that uh recently a customer escalation mail has come now the CEO or somebody wants to see wants to find out what are the connecting dots for this and how is it going to affect my forecasting revenue so it would ask okay why has this email come in the first place what was the pre-context to it and what has been the progress on this so far So then how is it going to affect my current incoming revenue and the future sales? Correct. Fantastic. So let's take that example right. So uh the context is um so how are we going to write it right? Somebody take you will you will present it right? So the context is okay um because there is a some mail that that from a customer has come um that is either different in tone or it's actually an escalation escalation didn't even have to come to the CEO somebody it came to the project manager of that corresponding project but that you know enterprise brain should say hey this looks like based on all the prior context. 01:20:14 Satyasri Prabhakar Mantripragada: Okay. Um uh there is an escalation that uh you know and and because from this customer you have two other um u pipeline. Yeah. In in the pipeline there are there is an extension project that is there that would they're currently going through review and it is at a particular sales stage. Right. uh and now that is potentially at risk or it it it'll at least get extended. It will not close this quarter. It'll close next quarter. Um and um so because based on the context context is um yeah yeah okay because it it you know because there is of that escalation currently there is something on uh you know in this thing and that is at risk. Okay, now you can dive into what happened and you can go into Jira and say you know the velocity has slowed down and you know why did it happen it needs that context of going into Jira why that attack got escalated something got escalated got delayed etc and then therefore you um you know the but to fix it what is needed because the complaint is about something getting delayed perhaps you could do additional resources For that you go into cautilia look at your resource allocation and see if there are 01:21:55 Satyasri Prabhakar Mantripragada: resources that are available. somebody is on the bench, they can immediately be pulled for two weeks and to accelerate something so that you could get it back on track and then therefore you can still u you know uh perhaps not allow the sale to uh and you could actually use that to uh prove that hey you you know you immediately respond to it and then uh do that. The thing is that escalation mail only went to the project manager and the person responding to it is the co the delivery manager calling the project head on the customer side and correspondingly the CEO calling the uh their CEO or their CIO saying that we'll take care of it don't worry that CIO doesn't even know that but they're reviewing but they you will know that that escalation will go so by the time the CIO reaches the escalation itself the CEO is calling and saying look we know there is a challenge but you know it's very simple we're going to you know because some resource suddenly went on uh leave and so therefore we got delayed and therefore you need to fix this. 01:23:10 Satyasri Prabhakar Mantripragada: So that is one example like that. What else can be this thing right or a new lead has come in? The new lead has come in and you are basically saying who is the one on the customer side and you are able to recognize that this particular person actually approached us uh one year ago uh with another project perhaps even with another company and then it only progressed this far and then these were the reasons why it got uh why it didn't get this thing and therefore it actually researches uh researches uh uh that company and that corresponding thing and says hey here are some of the uh things that you could do differently this time because last time this is what were the concerns and you were not able to address it and therefore this is what you need to do around this time right last time it was a different salesperson so you don't even have the context right this time um because that lead came and you are the salesperson person assigned to it. 01:24:20 Satyasri Prabhakar Mantripragada: Both the salesperson and the uh VP of sales is getting copied on that. So both of them will get that notification from enterprise brain. They'll get a notification when they log into enterprise brain. It's going to give them the full picture because it's not possible to give you an email with all of that interactive information. Right? So now think of scenarios where I can further drill down and ask questions where it will then say oh or even it lets me interactively explore what are the possible things that I would have you know I could go into different directions. I could go into the research into that company and understand or I could go into this person and understand the behavior of the person. I could go into the lead requirements and and then understand that etc etc. Right? Often times this happens right the other great example could be you know somebody has uh entered a new lead. Okay. Now you can immediately u go I mean um perhaps there is a companywide contact database or something that a lot of times see you know Danish sometimes connects with my you know people that I know without even realizing and and works works work it is it could be so much simpler if the person wants to come then immediately they can do I or or the moment that he's working on that potential person as a possible lead immediately enterprise 01:25:59 Satyasri Prabhakar Mantripragada: brain tells that tells him that look actually this person is in this person's contact database that is something that they do standard but not everybody is on my LinkedIn they're part of my email and my contact phone database so it it actually looks up my email and because it knows that I'm interacting it tells that person that you know talk to that person um that person may know more information or then it it gives them history about that person with this company you know have they ever worked with Dwami a lot of times people don't know like the new salesperson doesn't know and they go after somebody who is on our blacklist or somebody who we have done business with so you have to approach them like that otherwise they get pissed off right that we you know we are not doing the right thing so things like that so the moment some new lead is entered it automatically discovers and says. So these are proactive things then there are reactive things right and so then we can start with okay this is like triggered things some event happened in the company and automatically enterprise brain starts react other thing is okay today I logged in so what what are you going to show me because the context can be okay it is enterprise brain for salesforce you start with okay hey this is what happened over last week this is the change from last week these are the new leads 01:27:24 Satyasri Prabhakar Mantripragada: These are the new um uh these things. Now um think about those lines on what you could trigger from that aspect. So you don't have to um you can consider Salesforce use cases. You can consider Jira use cases also like something happening in the project and then you're able to recognize it and then go after email and then go summarize it and and do something things like that. One thing that we are thinking yesterday is um because it is enter brain enterprise brain it has connection to all that. Now it monitors my calendar and prepares me well ahead by scanning through the documents and yes perfect. I have a meeting set up now. Um you know um yes you know how can it give me more information about uh that meeting uh you know what would what could likely be the topics that would come up because it can look through my email. A lot of times we go unprepared because we ourselves don't see everything that needs to be done. 01:28:33 Satyasri Prabhakar Mantripragada: It can it knows the agenda. It knows the email threads. It knows the history. So it can give me this is what you need to know before you go into that meeting. Right? That typically when you have executive assistants and founders office people, CXOs get that. But not every CXO has that. So to before going into the meeting, it can give you these are the likely questions that will come up, right? Um one other thing that uh suggested but Rak said it may not be worth the but is that one I wanted to define my personality based on my role that my Tuesdays are occupied for say finance meetings my Mondays are for prospective calls like that okay so I I give a notes as simple text file or MD file to enterprise brain so accordingly it updates my the landing page I don't want to call it as a dashboard So it say it will say on Mondays my landing page will only be related to finance. Yeah. Could be. So sounds good. So please work on those. Sure. Sure. Transcription ended after 01:29:54 This editable transcript was computer generated and might contain errors. People can also change the text after it was created.