The Red Review - What 2025 holds for AI in Bids and Proposals with Javier Escartin

In this episode Jeremy is joined by Javier Escartin, Founder at bids and proposal AI platform DeepRFP. They talk all things AI in winning work, from understanding the landscape of specific platforms versus ChatGPT, the market of providers, what 2025 holds and the future of AI in our world of business growth. ⁠

DeepRFP.com⁠ is a kit of AI tools and agents that help bidding professionals prepare better proposals faster. It is mostly used by small and mid-sized businesses across industries and bidding consultants to respond to RFPs. It was founded by Javier Escartin, a Proposal Professional who has been over 13 years in the field and shares his insights in his personal newsletter at ⁠jescartin.com⁠

Transcript

Welcome to the Red Review with me Jeremy brim the Red Review is brought to you by growth ignition the transformation and

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capability development business all in the work winning space and the bid toolkit its product set in bid process

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and training videos so hello and welcome to the Red Review podcast with me Jeremy brim

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welcome back first episode of 2025 and an exciting one um tackling one of the

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big subjects I guess AI with my friend Javier so um welcome sir how are you hey

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doing fine thank you thank you for the opportunity no no worries at all great to have you along so uh we haven't done

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one of these for a while actually a vendor conversation who's who's got something interesting going on um so

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I'll have to brush myself off and make sure I ask the right questions um so would you mind s give it do a little bit

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of an introduction give us your your um sort of background current role uh and

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then we'll get into things sure so you know I like to call myself

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an engineer who loves proposals um because I'm I'm actually an aerospace engineer who started working in the

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European space industry in in technical staff like engineering staff so after a

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few years in in very technical positions um I moved to project management and then business development but the thing

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with the business development in this particular industry is that it's just a sort of um sexy name for a job that is

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80% about building consortiums and managing proposals to win big government

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contracts um so that's in that role is where I sort of learn RPS beaing on

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what's our profession then I quit a job uh started full-time freelancing as a

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proposal manager at that point of time wasn't um anymore about just Aerospace

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but um most of my clients were American uh Tech and engineering companies there

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more more like a small business businesses that need help with our pce and proposals and I did like that for

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like um four years fulltime um until I saw how good I was becoming and decided

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to launch thep um sort of with this idea of bringing advancements of AI to our

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profession and so now that I founded thep like um one year before chat DPT

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happened and so that's uh you know that's kind of um I use that as a joke

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sometimes because at that point in time um this was a like this idea of using a

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for proposals was like a very small need like literally we were like three or four five maybe companies sporing this

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um worldwide uh but then after chpt happen in what was that November

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2022 um you know the the space sort of boomed to a point where I um you know I

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just the don't um sort of count them anymore like you know every week you

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have someone trying to to do something with AI in proposals trying to wrap TPT

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apis for to to do some product um so

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yeah so that's um sort of U my background one important thing to note

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is that I still keep running the services business sort of this freelancing uh for proposal business but

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right now that's more like um uh laboratory for testing things how you

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know testing use cases seeing what works in the you know in real life ining real

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life but the priority is is deeper P to feed those use cases into into tools

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into um you know into technology and software very good so um so your

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products deep RFP um so tell us about it I guess where

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where did the idea come from bu mind like you say it was before that big kind of bubble of chat GTP before everybody

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really started down this line uh what was the kind of epiphany moment and then tell tell us about what the the platform

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does sure so um the the moment I I realize was in that um

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summer um yeah autum 2021 something like that I just um you I've been you know

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being an engineer I you know always play with with tech and software and always was interested in this stuff and also in

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that point in time I was full-time involved in in in doing bid management and B writer for writing for for

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customers so and I just wanted to optimize stuff like in in the thing I

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was providing uh the services and so always had this sort of intuition about

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AI about software automation following some of the repetitive task that we that

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I was I was having to do manually back um those years and and then just

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discovered almost by chance what was at that time um gpt3 which was this model

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that started to look very well but still you know very dumb compared with what we have today but um sort of the

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predecessor of what ended to be chpt um so I started with playing those

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those models with open AI which at the time wasn't a very wellknown company um so sort of had that idea like um okay

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this is this is going this direction so why don't we basically try to to exploit

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that to my service business and and that was sort of the original idea but then

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it started to take form decided to to make the you know to take the the step

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to build a sort of start prototyping something with the commercial mindset

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and and and building building tools and so that that that was s the origin of the company um but right now DP is the

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the best way of thinking about the is is a a kit of different AI tools and AI

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agents that are sort of like um mini applications or mini apps focused on

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solving very specific use cases and and those are use cases I have seen myself

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when when you know I was full-time doing this but also I see p me every day and

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so we have tools for writing responses to requirement we have tools for editing and reviewing we have now virtual s

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matter expert sort of um you know um having AI playing the role of engineer

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or a technical expert instead of used a big writer or big manager um so we have

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these mini tools that are optimized for doing one specific thing only and users can run these tools like as in a kit you

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know you just have this need you go to that tool run it get your outputs keep moving um so that's for the tools part

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also recently we we have launched um AI agents which is you know these are live

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since November last year so 2024 um so Prett new um we have a set

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that work with um with analyzing our piece and generating full reports on on

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that analysis of that RP reports that look like um compliance matrices but can be about anything actually the scope of

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the analysis is you know free and and then we also have agents to sort of

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draft full proposals um so this idea of because that's something that users have

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been demanding like since I started the RP until basically today um there is

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this need for this use case where you used upload your RP upload your winning

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points or your pass proposal or whatever and you get a full draft like you know 50 page draft that is 70% ready it's not

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your final proposal but you don't need to be sort of iterating with the um you

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know with the AI as you would do when using tools or using chatbots and

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co-pilots so um that's that's the the way of of thinking about thep is this

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key of of um tools and agents interesting um so what how is it

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different from just using chat GTP or from the other the Platforms in the

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space that are developing yeah so well I I

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like I I like to think of thep more in comparison with the rest of the professional tools in the space and not

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so much with end consumer applications like chpt or or Microsoft compile and

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anyhow um the there are like um maybe yeah

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mainly three ways uh in which DP is different the first one is we focus on

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solving real use cases so it's not about which model model po what but the use

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case Okay so our priority is to solve a real use case in buing and proposals and

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then for that um you know sometimes in order to do that very well we need to

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use a propretary model or we need to use an open source model that we customize

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for that particular use case or we can use a third party uh model uh that we

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have sort of focus on solving that particular use case with documentation and samples Etc so that's

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um one key difference is that we are not trying to first we are not tied to any

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AI provider or whatever but um that our priority is to solve the real use case

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in in biding and we don't really care much about the technical stuff as long as it solves the problem but that's one

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um the other way thep is is different the second one is that um we don't train any AI model on user data and to and and

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to ensure that because you know some vendor could promise that but to ensure that that is actually the case we don't even keep or

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save the data from from users uh runs and so and that's one way of protecting

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them sort of to ensuring confidentiality and protective property info because even if you know imagine

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your company like the company gets acquired in the future that uh New Management um like

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cannot train AI on on your data because we didn't save your data and so and

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that's um you know that actually was a hard uh hit to take regarding marketing

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because it's you know it sells if you if I tell you that a a tool is going to learn from usage and it's going to be

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better with your use Etc but for that I need to keep your data and then you know that there is a risk of some some you

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know sometime down the road that that data used for training AI models um you

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know that's a like the part of DEA learning when you use it it's a good

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marketing hook so we we have to compromise that to to renounce to that in order to ensure the the confidential

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data and and that's actually a big difference uh between thep and what I'm seeing other vendors do in the

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space and then finally and this is more like um type of user or type of Market

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we are after um a big way in which DP is different is that we are

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um focus on like if you you can imagine software as a service in different

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quadrants you have this uh very expensive solutions that are after the

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Enterprise deal that need to you know a Salesforce to push those deals and and

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then you try to get someone in a multi-year loin contract because you

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know complex software Enterprise level whatever so we are in the opposite

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corner of the quadrant we are like very affordable self-serving no risk deal

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part of the software industry so basically we offer a pure software as a service experience where anyone can get

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a free trial then you know upgrade to a plan with a use a credit card and if

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you're not happy with that you just cancel it you know you can do monthly

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billing so you can cancel it after a month and that's it there is no big risk no big investment and you could uh

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be using DP without having to talk to anyone in sales or you know even have a demo and and this is the reason that uh

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why thep is very popular between or among um small to small businesses

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Freelancers and and some uh mid sizes companies um Also regarding this you

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know of course you know we still do demos like if someone ask for a demo or you need some customization we we have

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done that a couple of times but um most of the time is see this idea of this is

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a easy to use selfservice very low risk uh software and you know one evidence of

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that one proof of that is that our pricing is public so you could go today to the website check the prices for the

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plants um something that you know is not that common in in the other Bandos that

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are trying to go after this Enterprise type of um of

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deal so yeah that you you know that's um sort of the three ways in in which de is

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is different from what um I see in the in the app and proposal space and that's

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that's really interesting so um so you're different from chat GTP as in it

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your platform is only looking inside the company's data it's not sharing the data externally is it it's uh it's just focus

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lens on the company stuff that's for sure uh the confidentiality part you know we improve on on what and consumer

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applications do but also um it's very different in from sorry CHP and other co-pilots or

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chatbots is because the user experience is also different so what we have is

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these two parts of the Tool uh sort of sorry the the kit so we have tools those

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tools look more like um um a web form where you use provide your inputs and

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run it and you don't need to care about anything else you just get these you know the output from that and you have

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different tools optimized for different use cases so depending on what you want to do you need to choose the tool run it with your inputs and you get the output

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but you don't need to learn sort of how that AI works or iterate with it um sort

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of work on your how you talking to the AI how you directing the work it's more like um one of tools like here my input

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give me my response or my summary or my edit or my you know technical approach whatever you're doing and then the other

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one is running agents and agents are even easier to run because it's just

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about selecting the right agent uploading the documents the inputs which are full files in the case of agents and

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just run it and then you go for a coffee or whatever because you know it takes a few minutes to complete and then you go

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back and get your output and the feeling is more like working with a remote

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coworker than actually running tools that's well we will talk about that in a minute but

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basically that's um you know the what what I think I'm I'm bullish on the agent idea so it's not only about data

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it's not only about pricing it's also the user experience is is different in the way that people are using chatbots

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or co-pilots interesting thank you so yeah CU it's it can be an expensive game on

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boarding a platform like this at a corporate big Enterprise level um and so

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I think you've probably got quite a smart plan in terms of you know a free trial and monthly billing and all of

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that kind of stuff transparent pricing I think that's really clever actually and because there is that it will be very

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handy for people to be able to dip their toe in the water and really be able to see what this stuff can do if it's their

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first time out Beyond looking at just using co-pilot or something um so I

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think that's quite clever yeah and also you know um since since I've been I've been building

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the um you know as I told you like the whole project started like one year

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before chip happened um we like we were getting a lot of uh leads also from the

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corporate world like the Enterprise level like we have talked with you know very big companies about dcii thing

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before chpt and after chpt happened um but as a small business you you you

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realize like that's sort of not your game um and and so I I think it's is the

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right strategy for us U but also is sort of um you know the the structure and the

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business that you need to put in place in order to go after those Enterprise deals um that requires um you know a

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whole different approach to to business and also it changed your pricing drastically and what's what what I'm

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seeing happening in this in particular our space but also you know it's literally in every software as a service

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in the B2B world it's like companies that go for that often raise fund from

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Venture Capital yeah and that that Rising requires them to go after those

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Enterprise deals and then you need to build the sales team you need to have you know your account managers your

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sales rep you need to push you aggressively to this executive to try to

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close deals in the you know in the ranges of um

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$100,000 and and so um it's a a whole different game um that we basically are

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are not trying even to to play um and so but yeah in the in the you know in the

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other part of of that um space I I'm you

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know we are very comfortable doing this um more sort of easy software for

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building teams that you know doesn't break your budget and is you know very

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transparent from the beginning you know we are not charging anyone differently because you know the pricing are public

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um and you and you don't need you don't have the hustle and the risk of selecting this vendor because I'm going

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to be committing for three years contract because this is sort of and I need to ort all my stakeholders or

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whatever it's a different game like small businesses need more like um you know quicker Solutions than than that

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and I just personally I just hate go to some software company try to use the

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tool or whatever and the only way to move forward is booking a sales demo with someone and then move to the next

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one and then next one until the third iteration you don't get the pricing and the quot it's like it's you know for me

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it's you know I I don't like that personally and also why I focus the in this segment oh I understand that's

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quite smart and to be honest I have mixed feelings about private equity and all of that space

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anyway it's it's a really powerful tool for unlocking growth in certain ways but as a business owner

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or a leader it's quite I think it's quite stressful um it's not it's not for

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me I mean I I get people approach me all the time you know I left I was an authorized trainer with the apmp uh

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until the middle of last year and I left because of a a difference of views let's say um and people approach me all the

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time you know will I start a competitor to apmp and there is there's a dramatic business opportunity for somebody it

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would be easy to AB absolutely destroy them and do a fantastic job better quality good

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Integrity um you know all of that kind of stuff uh because they've got some Cornerstone issues that it would be easy

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to um to overpower them on but um I just I just you would need big money behind

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you private Equity stuff the same as the kind of uh big software as a service lot

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and you'd have to go after lots of big corporate deals like you say corporate memberships and all of that kind of

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thing um and it's just not for me really i' I'd rather just have a nice life um

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and run a great business enjoy working with my clients um you know happy days

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so I I can kind of get the Vibes I can see why people do it but I have a number of clients that are private Equity

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backed and the metrics that are put on them the behaviors the the sort of challenge it's it's it's not for

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everyone it's definitely not for me so um I can I can sort of get that so best of luck to people that do that yeah and

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also you know linking to that uh topic if you see them like I see I would

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expect this year I'm beginning of the next one uh to like because the market

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is like all markets are but our space also um um you know it's kind of

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saturated of AI tools right now like you know we're talking about hundreds and

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and many of those are uh BCB um for example I told you thep I boost up

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the company so uh not R there but I see some um companies doing something um you

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know similar things or or actually going after these Enterprise deals but anyhow

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sort of trying to use AI for proposals on our piece and stuff um and I don't think all of them are being able to

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close the many Enterprise Deals they need to survive the next round and so um

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it's in I think it's going to be interesting to to see who sort of survive that race for the Enterprise

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deals um and I think that you know if you see the sort of when these companies

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raise money um and sort of the typical window of one and a half two years they

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give you for the first sort of milestones for the next run um I think

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this will be the year where we see some of them actually winning the game and

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just some of them just going U you know bankrupt and closing the companies so I

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I hope um maybe you know um I I would expect that in a year and a year and a

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half we will have less players in the space I how that's just my guess no I could agree it's it's usually

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the sort of thing when you when you get a Sprint like this with a new technology or new innovation uh you you do get it's sort

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of that betax versus VHS kind of thing isn't it that you'll you'll find some will fall by the wayside um and it'll be

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testing what happens for the clients that have signed up with the wrong ones that go bust when they've uh or or close

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because uh they've gone and put all their eggs in those baskets it's it's a real question that I would say yeah and

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also um you know the this this um and I'm talking about um personal experience

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now is um this gives us um kind of an advantage because

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um like we can thep can really be focused on trying to lead on agents lead

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on research and development like trying to the last thing see how to adapt to that and um don't worry much about um

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sales and and or at least of course you know we do care about marketing and sales but uh the thing is we are not

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stressed by having to close those many deals this year otherwise we are out of

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business so you know this is like for the long run since thep break even and

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and started to generate more money than it spends then it's just a matter of like like this company can be here for

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the long term um and so that's also a nice advantage of of not being in that R

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and and also I think that's um of course my personal opinion but can bring more

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value to the space and to the professionals and to the peers that are doing this stuff uh because at least you

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have some companies that can be focused on fully taking advantage of AI to solve

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real use cases and not so much the pressure of you know going after this um

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big Enterprise deals and and being in that race but yeah you know um anyhow we

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will see well it's a nice segue so um we were going to talk next about what uh

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2025 holds for deep RFP but more widely for AI in bidding more generally as well

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what what do you think the themes are what do you think the next steps are or the next innovation where where are we

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going to take it in this game yeah so for for sure I believe AI

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agents are going to be uh important a very big thing because of how

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implementation's going to change with them so and and think I think this is going to be like across the board

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because um and and the main reason is because of how these agents um fit into current workflows so

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as I was telling you before it really feels like you are working with a a cowork uh in remote you know H you just

25:34

ask for some task and you get the outputs and you just don't need to do anything else it's not like running

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tools or chat Bots or copilot and where you you know with copilot and CH you sort of need to micromanage them but in

25:48

this case it's more like delegating stas and so I think that's only that is going to be fitting better on most people's um

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most team's way of working so I I I think AI agents will drive um

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implementation of AI but also not only because AI will be more used because of

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Agents but also we have current limitations in AI systems and and I I

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think it's important for everyone to know but basically there are like three main limitations we we have with cover

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and state-of the models okay one is inputs um sort of it's very easy to

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overwhelm AIS with too many inputs so people have this idea of trying to

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pass the whole Content Library um and you you just can do that um you can you

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know you need to be a strategic about the inputs that go into each request in order to maximize performance then you

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have the limitation of outputs which is sort of the length that you can generate in one run which is sort of one thought

26:49

stream of the AI if you know maybe they are not thinking or whatever but that's more like a philosophical debate but

26:56

anyhow this this idea of in one run in one uh thought process what they can

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generate that's right right now around two to three pages of content per run

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and then you have the hallucination problem which is some of these systems making um stuff up like you know using

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fake data or use something like they don't know something but they tell you they do and and they airmed some you

27:23

know past project that wasn't there Etc so these are the limitations you get with a um generative AI large language

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models as as currently they are and and this you need to manage these

27:36

limitations yourself when using tools or using chat Bots now with agents you can sort of

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orchestrate the process behind the scenes so the user doesn't take doesn't

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need to take care of any of these limitations because you can select the inputs strategically behind the scenes

27:54

depending on what the request was you can generate full drafts doing this iteration like maybe the AI is just

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doing two pages at a time but you behind the an AI agent at least for example

28:06

what's happening with the one that we have that draft proposals is that you

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have this processor when one AI is playing the manager role sort of deciding the table of content which

28:18

winning points we want to use for each section which input we to consider for each section all that stuff and then you

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um that manager is calling AI writers to develop every section and then you

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iterate on that process and but all all this happens behind the scenes so the

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user just you know uploaded the RP and now it's downloaded a full draft um so I

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that's why I think agents are so powerful because of the way of working with them which is you know more like

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what we do nowadays and also because you can build in the the managing this

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workaround limitations um so at least what we're want to do in

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this year is we're going to keep expanding the set of Agents we have um and the use cases that this discover and

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I think this is going to be like across the industry like what's going to happen with with um with tools but also I I

29:14

wanted to to tell you about um Jeremy about um a concept I've been exploring like um the few last weeks um it's a

29:23

concept that to be honest I I still don't have a good name for it but is this idea of having a a top layer

29:32

interface where you don't really need even to run tools or agents or you know

29:40

just sort of um you ask what you want to do and this sort of viral proposal

29:46

manager is the one that has access to the whole kit of tools and agents and then ensures that you know you provide

29:53

the right inputs for the what you want to do and then runs the tools in the background and runs agents in the

29:58

background and sort of you stop having to interface with an application through

30:04

this software interface and you just talk to it and it knows sort of Masters

30:11

what to call and when to call it and which which documents Etc so I don't know how to call that yet yet but we

30:18

have a prototype um sort of um conceptually uh in the buildings and I

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think this is um well right now this is just too too much into research and

30:30

development to say it's even a thing but um this are this is a concept I want to

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explore this year about um this idea of you know and in in other spaces like for

30:41

example if you you talk about personal computer companies like Microsoft and all the big ones are exploring this

30:46

concept of like you have a computer we have a lot of programs and tools Etc but you could have sort of a layer of AI

30:53

where you use as for things and that layer knows how to open your Navigator or how to draft an email how to run that

31:00

tool or this other tool that you just interface the computer like through a conversation like um anyhow um so that's

31:09

what I what we going to focus on on on 2025 so sort of developing the agents um

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a lot and investing there a lot covering use cases and also trying to as always

31:23

with thep we are trying to go in the to go to the yet with this technology and

31:28

so exploring this concept of um interfacing differently with a web

31:34

application um this idea of you don't need to be to even care about where the

31:40

tools are or which you know how to run each tool you just ask for things and

31:45

and then we we like this AI layer takes care of what to run depending what you want to do Etc and of course you can

31:51

always access the traditional software application you will and and run the tools yourself or run the agents

31:57

yourself but um sort of um way of reducing friction with AI which I think

32:02

is key for people to benefit from it yeah is exploring this idea sort of like

32:09

an AI Somalia or something yeah

32:15

of yeah a compass um I was thinking about calling it a compass or a master

32:20

but yeah it's still too early to even to give it a proper name no fair enough and

32:26

and what what do you are there more other General themes beyond your business in the world of sort of AI with

32:31

proposals that you're seeing what are the themes for this year do you think so the the agents are are right now big in

32:40

every space many companies are exploring this idea um of having sort of

32:45

autonomous AI doing tasks on behalf of people uh with restrictions of course

32:52

because of the limitations of the technology you cannot have like a like um in proposal you cannot have an AI to

32:59

take over a full RP and try to manage the whole process yet um because you know not smart enough and hasn't um

33:07

doesn't have the the planning capabilities but anyhow agen is is is you know being big but also there is

33:14

this debate on is AI uh hitting a wall in terms of development and capabilities

33:21

or not and that's a debate that still you know been arguing about and we going

33:27

to be um the good news is that we will have some proof one way or the other in

33:35

uh the first quarter of this year because the last generation of models have been trained so far and and about

33:42

to be released we have finan from open AI but also you know XII and other companies are building and training this

33:50

last generation model so we will see the new capabilities we get with those and

33:56

that is going to Define I think it's going to define the the the next few years in in software and AI

34:03

overall because if AI um sort of hits a wall and

34:09

stops having these emerging capabilities that have surprise everyone then we are

34:14

pretty much lacked um or stuck with the intelligence that we have now yeah you know models will get a little bit better

34:21

but it will be like sort of the same thing and then everything is going to be focused on how to drive implementation

34:29

how to ease the use case experience um user experience use cases how to you

34:35

know bring this AI to all the applications and software we use today but it's not going to be like changing

34:43

the the approach that you already see in in different tools and vendors that's one option then the other option is like

34:51

the exponential curve keeps um up and and then if it keeps going then nobody

34:58

really knows because it's going to depend on the capabilities of of what these models are able to so imagine you

35:04

get one model that is able to go through your FP and through your library

35:10

content and and then it's also able to communicate within your company and sort

35:15

of becomes your virtual proposal manager but in a sense that you don't really need to micromanage the whole process so

35:22

if you ever get that capability in AI systems then the whole software um

35:28

industry is is going to sort of adapt to that and probably the tools that we're going to see at that point in time are

35:34

not anything like thep today or any of the vendors in the space today because of how big they live in the capabilities

35:41

of a but again this is going to depend on on what happens and and the the funny thing about this is

35:47

like um I'm not sure enough people understand this you know in

35:53

in you know like overall or in general but the systems haven't been been

35:59

designed to to do any particular case so we're talking about system that have

36:04

been about use training particular algorithms on huge amounts of data and

36:10

give them crazy amounts of of compute uh Power and then you start having these

36:17

emerging capabilities but no one designed um the models that power GPT to

36:23

write proposals that that wasn't a design requirement or whatever it's just like okay let's put like the whole internet

36:30

into this thing give like this many data centers to this thing and this happened

36:35

and now this thing knows how to code writes very well content can sort of

36:41

think breakstone with you Etc and so the thing is the question is what happens when you scale the next step and and

36:48

nobody has the answer yet even we probably get some in the next few months

36:54

and that's going to shavee in my opinion that's going to shape the the whole industry depending on what happens at

37:01

the other side of the new generation models interesting slash terrifying uh

37:08

it's really it's really fantastic and as I'm a bit getting a bit older I guess yeah unnerving but um there you go I

37:15

think I i' I've been um managing the risk of our business in terms of exposure with this stuff for a while

37:22

we've been standing up AI proof businesses like property development stuff and I Focus these days most people

37:30

come to me and want me to teach them to write bids and stuff and I I do need a bit of help this year in developing some

37:36

extracurricular modules on AI and how to interface with it generally not product

37:42

specific um in in this space uh so we're doing that at the moment but um actually

37:48

I gravitate more towards capturing key account management and things where it's still about humans and relationships and

37:54

building trust Etc although of course I I interested in whether some of the

38:00

vendors start to point AI to support that in terms of researching prospects um you know un helping you

38:07

develop your strategy propositions um you know understanding the personality DNA of the people we'll

38:12

be interfacing with and who the real decision makers are and all of that kind of stuff there's some of that going on

38:18

in the CRM World plugins to Salesforce Etc but I'm I'm interested what the interface will

38:24

be by the time it gets to proposals strategy was yeah um yeah that's that's

38:31

right and and that's um sort of um one of the main points right now is

38:38

that you know AI is going to is is preing at time everywhere you know and

38:45

many use cases are qu WIS everywhere um and people so people are that are using

38:50

AI um are getting you know free time back and now that's that's sort of the

38:56

newest equilibrium like you're not going to gain an advantage just because of that now what matters is what you do

39:04

with that time that's going to be what matters and then you have this uh sort

39:09

of debate on if you go forbiding more or you go for biding better and that's

39:16

honestly that's something that every company needs to answer because sometimes it makes sense to be more for

39:21

more because you have the capability to execute those sort of the capacity to execute those contracts but also you

39:27

have a huge competitive advantage and and you just need to be more to win more contracts that's you know not the most

39:34

often case but sometimes that's the solution most of the time I think the

39:41

wiser strategy is to invest that time in Bing better um and and that biding

39:46

better what what it means is the sort of things that you have just describe it's for example how we going to capture

39:53

better insights for from customers and stakeholders to build into proposals spend time there um um a strategy bu a

40:01

strategy and and sort of um Game Theory strategy like where are you position in

40:07

terms of quality and scope and and then pricing all that all that stuff and also

40:14

improving the content itself like spending time on on even if you are

40:20

working with AI to improve that content but spending time driving that process of just not let's don't use uh what we

40:27

we already have but improve that and and fit that into the AI and so it's going

40:32

to also a trend we are seeing right now is that um you know more and more

40:37

procurement and in live presentations and sort of live interviews um one of

40:43

the reasons that's happening is because they are having a harder time to differentiate between good and bad

40:49

vendors just based on the content because of AI and um you know an a new

40:56

sort of um um um and is not super new field but uh

41:02

you could also invest the time on on improving your um sort of your skills on

41:09

winning those deals that require a live presentation and and yeah and and regarding technology I agree like for

41:15

example for um for the sales part like there is a there is a paradox in sales H

41:22

which is that the best people the best sales uh people are very busy selling so

41:28

are the ones that input less content to crms because they are just too busy jumping from call to call meeting to

41:35

meeting and no one takes them accountable because they are bringing them you know more Revenue than anyone else so you you know this type of sales

41:42

rep that they start in the team and they don't capture insights in the CRM because they don't have the time

41:48

literally and then crms gets populated with inputs from the average Sal r

41:57

which are probably the ones that have average insights on on medly insights on

42:03

on clients and so AI is called to change that because you know if you could give

42:09

H that very good sales rep um a way of for

42:15

example just recording an audio note between meetings while driving and then

42:20

the CRM Tes that audio note detest it an an AI that is specialized on that use

42:26

case PST the those insights where they need to be and so people ining and

42:32

proposers can leverage those so and I think that's not going to come from

42:37

vendos in rpn proposals more like it's GNA be like the incumbent crms but I I

42:44

see hope for for that big advancement there um and also ac across the process

42:50

like um I think AI is is going to unlock value in many of these steps so it's not

42:56

only about saying in time but you're going to get better insight and and you know better strategies Etc but again

43:03

what is going to determine the winners of the future I think is what you do with that free time

43:10

that's that's the advantage like um what you going to do with the free time that this

43:16

automating um you know tools and a tools are giving you yeah I think that's fascinating

43:22

actually you've set some hairs running in my mind there that's really interesting um cuz I I'm on my 16th client now maybe

43:31

17th actually 17th um where when I've been working with their board or

43:37

leadership team particularly Finance directors Chief exec we've we've realized looking at the data that around

43:44

80% of their margin is coming from 20% of their clients and then they have a few clients where they make some more

43:50

money and then a very long tale of clients when if they actually calculate it effectively which they very rarely do

43:57

if you wind in the cost of sale and looking after those clients they're making a loss um and so if you cut the tail and

44:06

just add a client or two to that list of the the top clients you'll smash your numbers to bits and have to bid a lot

44:12

less um and be able you'll probably have higher what we tend to find the latest

44:18

work we're doing is what's in the DNA of the clients and the projects that are in that initial bulge in the in the sort of

44:27

curve and it's the clients that engage early that are good to work with um

44:32

where you have a higher propensity for direct Awards and negotiations rather

44:38

than competitive tenders so I I I think it could be really valuable that you

44:43

release your time from working on tender so much using Ai and then put more effort in into your solutions to clients

44:51

to make sure you deliver more value than anyone else and then in how you look after those clients we my natural

44:57

reaction but I'm going to do some more work on that actually mate that's I think that's really interesting if I was

45:02

given more time what would I do it's probably those two things but maybe some others yeah and that's you know that's a

45:09

question that uh people need to answer themselves and and that's actually one of the top tips I've given not only in D

45:17

RP because you know I'm very active in you know I basically talk proposals and

45:23

Technology all day long so you know my newsletter um jar.com and also LinkedIn but the

45:31

thing is one of the top tips I've G given the most is this idea

45:36

of um there's there's like a two steps task or project is first analyze your

45:43

Bing process and when with analyze I mean um like actually drawing uh diagram

45:50

flow like uh you know process where you have the inputs step outputs and having

45:56

that very clear like what's happening when you know how you screen RPS what happens when someone says okay we're

46:02

going for this RP the the steps you take have you know stakeholders and

46:07

integrating contributors content whatever you do in the process like having that picture there and then

46:13

that's the first step the second step is to understanding current capabilities and limitations of AI systems which we

46:20

have talked about today um so but but basically this idea of internalizing

46:25

that computers can now read understand write um par information

46:31

like never before plan um you know execute on task autonomously like those are capabilities that computers didn't

46:37

have two years ago and we need to sort of remind ourselves that that's something that we now have you know

46:43

everyone has in in the phone or or or the laptops and so once you have those

46:48

two clear um you know steps like your process on one hand and you understand

46:54

what AI is capable of or computers are capable of then you can sort of put those together and you go bottle neck

47:02

after bottle neck asking yourself like can AI help me with this particular bottleneck like I'm doing this for every

47:09

bit is there a way AI can help me with this particular step it's probably yes the answer and then you just go for that

47:15

Implement that um and so just do by doing this you're going to be ahead of

47:21

most people in the space and also better prepared to look for tools and to uh

47:29

avoid being tweaked by vendor marketing um because you have a clear idea why you

47:35

need and and you just want a solution for that bottleneck which is your car bottleneck Etc and then as a result of

47:41

that what happens is like you're GNA find yourself freeing dozens of hours

47:48

every week and and then the next step is more like a strategic and it's a question that everyone needs to answer

47:54

within the team with the context of the company Etc there's not one solution for all which is this idea of what you going

48:01

to do without time um and and that's very very important question to answer

48:09

it is it is thank you sir there's some really good thought-provoking stuff I mean 2025 in amongst other things is the

48:16

year of AI for me in my business I have to say I've been behind the curve slightly fearful of it and I need to

48:22

pull my finger out and just e even in my marketing stuff which I've taken great inspiration from you on I have to say

48:28

with your uh email uh newsletters Etc which people must sign up for will come

48:34

to um you know I think there's a lot of value to be had that can make me even more of a David a powerful David against

48:41

these big goliaths that I come up against all the time so um thank you very much good coaching wise counsel um

48:48

so where where do people find you um where where can people follow you and all of that kind of stuff yeah you know

48:55

um um if if they want to follow linking is the place I should consider engaging

49:01

conversations and that's also the easiest way to reach me just message me

49:06

on LinkedIn so that's one then if if they are into insights more like you

49:11

know um using to um use all information for every day like to do better at

49:18

proposals and Bing then they can uh sign up for free to the newsletter I send a

49:24

couple of emails every week um and they can do that in jar.com with the J and

49:31

that's for free and also it comes with a lot of um perks as you subscribe and you know I share some useful insights there

49:38

and also I share your positions and give some free resources so it's it's like um

49:44

if you are looking just for resources and information that's the place and then if you are looking for tools then

49:51

the place is dp.com that's the company page for sof as a service um then often

50:00

what happens like um is you go to the page get a free trial account we have

50:05

free trials there for seven days you can play with all the tools No Limits and then um you know you just decide if if

50:14

that's for you or if you want want to give it a try for a couple of months remember that you can cancel anytime

50:21

that this is not like the type of Enterprise deal that is going to log you in for 3 years or whatever um so those

50:28

are like and and that but I only would recommend to go to the.com for people that are proactively looking for you

50:36

know tools and testing what they I can do and testing this agents concept and that kind of stuff so for tools

50:42

dep. for insights just cutting that very good well thank you very much really

50:48

appreciate the time it's been great to have you on uh I'll follow with interest and here's to 2025 it's going to be

50:54

exciting thank you yeah thank you for for the opportunity to be here