Turboconsultant: Running a Solo Practice on AI Agents, end-to-end

 

Jean-Christophe Lanoix

SPEAKERS

Jean-Christophe Lanoix, Will Bachman

 

Will Bachman  00:02

Hello and welcome to Unleashed. I’m your host Will Bachman, and I’m delighted to be here today with Jean-Christophe Lanoix, who was a consultant for 17 years. He was the second employee, well, the first employee, along with the founder of a firm called Hinicio, starting with an H H I N I C I O, he was the first employee, and they grew it to 70 employees. That firm, and it was sold to an engineering firm. It’s a firm in in Belgium and France, and then he’s currently the founder of Turboconsultant, which is builds AI systems purpose built for independent strategy and management consultants. So, Jean-Christophe, welcome to the show.

 

Jean-Christophe Lanoix  00:54

Thank you, Will. Thanks for having me.

 

Will Bachman  00:57

And maybe just right at the beginning here, and I know you. We can repeat it at the end, but to catch listeners that you know just right at the beginning, I think that you have a discount code for listeners of this show for Turboconsultant. We’re going to be spending most of the show today diving into Turboconsultant, but maybe you just share that right up at the front as well to to catch listeners as as they’re joining here.

 

Jean-Christophe Lanoix  01:20

Yes, indeed. Thanks for the introduction. I do have I do propose a promo code for your listeners, which is unleashed underscore TC like Turboconsultant, and it gives 100 euro discount on the price of Turboconsultant, which is normally 499 euros per month, so it comes down to 399 euro per month for life for your listeners with this promo code. But we’ll come back to that later.

 

Will Bachman  01:58

Very cool. All right, and Umbrex and Unleashed. We do not receive a referral fee, but we’re happy to make people aware of that, and we’ll include that discount in in the show notes. So thank you for that. Let’s um. I know you have a couple slides, and you’re going to actually do a bit of a demo of the tool. So lead off, Jean Christophe. Tell us about this tool that you have built.

 

Jean-Christophe Lanoix  02:21

Sure. Let’s go ahead. So I’m going to share my screen right now. Please, we’ll confirm if it works.

 

Will Bachman  02:28

And I’ll mention the listeners who are getting this on audio. We’re going to put this out on iTunes and Spotify and all the great places you listen to podcasts as an audio version. But we will have screenshots on the Umbrex website, and we’re also going to publish the video version of this as a permalink on the Umbrex website. We have some profiles of different AI tools for consultants. So this video, if you do want to watch and have all the visuals, you can go to the Umbrex website, and we’ll include a link in the show notes for people to find that.

 

Jean-Christophe Lanoix  03:02

Okay, I’ll do my best to make it understandable for those who will listen only without the the image. But we’re going to have a lot of slides and a lot of images, so I’ll do my best. So, what what is Turboconsultant? Can you see my screen?

 

Will Bachman  03:18

I can. I can see it. Great.

 

Jean-Christophe Lanoix  03:20

Okay. So it’s basically the execution layer, the AI execution layer for solo consultants. The main limiting factors for solo consultants is they do not have the pyramid; they do not have the army of junior consultants to do all the research and all the nitty gritty details, and all the slide building, and so on. And the unfortunate reality for Solo is that he is his own pyramid. He builds his own slides. He does his own research, and the reality is that he’s spending most of his time on lower value task, and less of his time on high value task. Okay, so Turbo Consultant is a solution to that dilemma, and it’s basically a virtual team of AI agent under the consultant direction. So the consultant basically sits on top and directs a team of AI agents that cover the entire spectrum of activities of a solo consultant, going from upstream business development, lead generation, proposal building, research and monitoring. It has deep research capabilities. It can build methodologies. It can do the marketing, build marketing material, write content, etc. Build the deliverables that. A big, big part of it. Quality control. We’ll come back to that. Very important for consultant. It has various layers of quality assurance that are built in. It can help you prepare your meetings, do the follow-up, and many management and administrative tasks such as writing your contracts, etc. etc. can manage your emails, etc. So, from a technical point of view, Turboconsultant is a layer sitting on top of entropic cowork. So, cowork is agentic environment built on top of entropic LLMs, Fable Five, Opus Five, Sonet Five, Opus 4.8, etc. All the LLMs from Entropic are basically very powerful models, but they are pretty much useless to actually do things. You need a harness. You need an orchestration layer, Claude CoWork is such an orchestration layer. So it allows to go from question and answers. This is what you get from a standard LLM to actually instructions and actions. So with CoWork, you can actually do things within the entropic environment or outside. It can connect to many other tools: your emails, your file systems, your Canva, if you use Canva, or 1000s of different tools. Turboconsultant is a plugin within Claude CoWork, and it basically transforms Cowork into a consulting team. Okay, it adds the right method, the right guardrails, so Cowork behaves like a perfect team of consultants. Not only that, it behaves like your perfect team of consultants because it’s highly personalizable. Okay, we’ll come back to that in a second. So that’s very nice on paper, but in reality, we all know that AI has a big limitation for consultants. First of all, it is very generic. Okay, it gives very generic output. There is no differentiation. Okay, if you start using ChatGPT or Claude out of the box for your consulting work, it’s gonna sound like any other consultant using ChatGPT or Claude. Okay, TurboConsultant is not like that. It is very personalized because when you first use it, you go through a step of onboarding, where for two or three hours the system is going to ask you all the possible questions about your business, who you are as a consultant. Who are your clients? What kind of services you provide? What are your references? Who are your competitors? You’re gonna provide examples of deliverables, examples of proposals. You’re gonna provide your template, so the system can extract all your patents. Your semantic patterns is gonna start speaking like you. It’s gonna extract your visual pattern. It’s gonna build slides like you. It’s gonna extract your methodological patterns. It’s gonna use your own methodologies. Okay. So highly personalized environment. Secondly, AI is a yes man. Okay. Yes, with AI you can go faster, but the reality is you go faster into the world because the you have constantly that this reinforcing loop. Even if you’re wrong, the system will never say that you’re wrong. Here we I added critical thinking, so the system is going to push back. If you’re wrong, it’s going to let you know. Third, hallucination, made-up facts, errors, AI basically is great 80% of the time, but 20% of the time it’s not great at all. It gives you hallucinated numbers, fake sources, etc.

 

Jean-Christophe Lanoix  09:26

And basically, the time you gain during the 80% of the time, you waste it by reviewing reviewing everything by hand to make sure all of these errors never reach your clients. Here we have a triple level quality assurance. Everything is triple checked. The sources. You have an internal audit by cowork itself. External audit by external LLMs. So what you get is really. Something that is 99% client ready. Then you have an issue with normal well consumer AI. You have an issue with client sensitive data, especially if you use your cowork session or if you use your ChatGPT session with the memory, very memory is very useful, so the system remembers you. But it’s going to stop mixing mixing up information between clients, so you’re going to have a leakage of information from client A to client B deliverable. That’s a big big problem for consultants. Here, it’s fixed by design. Everything is siloed, and it’s just physically impossible to have such a leakage. I’ll show you why. And finally, with AI as a consultant, what you end up having is a patchwork of disconnected tools with various subscriptions, and you do not capitalize on anything because you have every time to start again, re-explain what you do, re-explain who you are, and you have to do copy and paste from one tool to perplexity to ChatGPT, etc. Here, it’s unified, it’s a personalized system, and it gets better every day. It knows you more and more, okay. Very quickly, it includes a whole library of consulting-grade methodologies in many different areas, from strategic consulting to market analysis, innovation and product data management, problem structuring, messy pyramid principle, M and A due diligence. You have various valuation methodologies that are built in that you can use if you want to, and the system will add to that library all the methodology that you use that are going to be extracted from you during the onboarding stage at the very beginning. So you have a lot of the system is going to use your methodology in priority, but it can also use methodologies consulting grade from McKinsey, from BCG, etc. Off the shelf. Okay, let’s start the the demo wheel. So we I’ll switch to the co work environment. So can you see it now?

 

Will Bachman  12:43

Yes,

 

Jean-Christophe Lanoix  12:44

great.

 

Jean-Christophe Lanoix  12:52

So this is cowork. So it it looks like a standard chat, standard LLM, but for those who don’t know cowork, as I said, it’s not question and answers. Well, obviously you can ask question and get answers, but it’s more instructions and action. The system do things for you. So basically, cowork sits into the settings. It’s a plugin, so in the settings you have this section here, plugin, and it’s very easy when you subscribe. You basically download a connector, which is here. You it’s a one-click install, and the connector basically connects CoWork to the actual plugin which hits on a on a on a server, okay. So it’s very easy to install 00 technical hurdle here, okay. So what we’re gonna do now is a couple of tasks which we’re gonna start in parallel, including building a proposal, preparing a kickoff meeting, and executing a work package in a typical client engagement. So what I mean by a typical client engagement is here I built. It’s totally made up as AI the AI to do it for me. I built an hypothetical request for proposal from an hypothetical client, which is named Kestrel Rich Partners, a lower middle market private equity firm investing in healthcare and consumer service in the U.S. Okay, so the topic is as follows: We are in exclusivity on a group of 42 veterinary clinics across the U.S. Southeast, approximately 120 million revenue. The business is founder. And has been built by acquiring independent practices, one at a time over eight years. So the objective is an independent commercial view to support our investment committee on August the 21st. So what is specifically requested? The scope is Market analysis is pet care spending still growing or was the pandemic surge a one-off? That’s the first question. Second question is retention: How loyal are pet owners? Okay, when a practice changes hand, then competition analysis, Runway and the investment thesis at the end. Okay, what we’re going to execute now will be the first work package on market. So what’s requested is yeah information available to the advisor, financials by clinic, three years, anonymized client list, set as information memorandum. So the deliverable expect is a 20 to 25 page deck, IC ready, supporting model, the timeline, and the indicative budget 55 to 75k. What the proposal should contain, approach and work plan, team and relevant experience, what you need from us, assumptions and risk, fees and terms. Voila! That’s totally hypothetical. This does not exist. So what we’re going to ask Turbo Consultant is to help us build the proposal. So I’m gonna ask. I just received the attached RFP. I want you to help me build the Proposal. It’s this one here. Voilà. Okay, we can start. All right.

 

Jean-Christophe Lanoix  17:30

So in parallel, we’re gonna launch another task. By the way, what I’m doing is basically I’m using Turbo Consultant as any user would on a normal day. I didn’t show you the actual onboarding, okay, which is just a one-off task, which lasts two to three hours, as I said, because I did it myself before the demo, and what I can show you, just to illustrate an important point, is this is voila. This is here. This is an onboarded folder. Okay, when you start with Turbo Consultant, you start with an empty folder. You give CoWork a working folder; it’s totally empty, and then you go through the onboarding, and then the system asks you questions, and at the end, it builds a whole set of folders and files, which are the infrastructure of files that will be used later on by the system to work like a consultant and to work like you, basically. Okay. And one important thing here is the client subfolder here. Every time you have a new assignment, a new engagement, you create a new client folder. Okay, and then when you work on the engagement, you open cowork on this particular client folder. Okay, and this is quite crucial for for two reasons: one, it’s crucial for data management and data hygiene. Let’s say, because when cowork is working on that particular client, he only is only seeing what’s inside the folder. He’s not seeing what’s outside. He is not seeing the other clients. So that’s the architectural reason why the data leakage between clients is impossible, physically impossible. The second reason is when you create and when you ask TurboConsultant to create a client folder, it creates the same kind of. Folder structure, file structure, and folder structure entirely focused on the engagement. So when you work on this folder, the system behaves like a war machine aimed at executing this particular engagement. It’s not polluted by all the context outside of it, by all your other work-it’s only focused on this executing this work. It has its own cloud.md file, its own identity, just to execute this engagement. Okay, it is hyper focused. All right. So here, so we ask to build the proposal, so very interesting here. The first question the system is asking you here is, how do you want to work on this proposal? You can work autonomously. Well, the system can work autonomously, so you give a couple of input at the beginning, and then it goes straight to delivering you with a document. You have the exact opposite, which is co-construction, where you’re gonna be consulting every step of the way. Okay, the system is gonna ask you to validate everything. You’re gonna be brainstorming for every slide, every task, everything. Okay, it takes longer. It takes more of your time, but when you get there, it’s almost ready because you already gave everything you have. And this is what I would use if I was still a consultant using Turbo Consultant. And you have the intermediate, so it’s pretty much in the middle. You validate the big picture, and then boom, you get your document. So here, for the sake of the demo, we go for autonomous. Where do you want to price inside the 50 to 75k? Let’s say top of the range. Who is on the team? Me only. What is your relationship with the client? Let’s say it’s it’s called. But if you have a history, you can actually mention it, and he will use it in the proposal. What’s your track record? I can cite. Yeah, we we could give as much information as we want if we have a track record. Who is likely bidding? Let’s say MBB. No, let’s say CDD boutique and other independents. What do I want? Slides and let’s have give. Let’s have a synthetic presentation so it does not take too much time. Give me Synthetic proposal. Let’s say around eight slides. Obviously, if we want a 2030, slides, it it can do it also. All right.

 

Jean-Christophe Lanoix  22:58

So now we’re going to launch a second a second task in parallel. So let’s say we won the proposal. All right. So we are starting the project. So we have to give it the the client folder now here, so it’s this one here. All right, we are starting the project, and well, first thing to do is a kickoff meeting. So I I am starting the project. I want you to help me prepare for the kick-off meeting.

 

Jean-Christophe Lanoix  24:03

and also we’re gonna ask Turbo Consultant to execute work package one. I want you to execute work package one. So as a reminder, work package one is market is pet care spending still growing, or was the pandemic surge a one-off?

 

Jean-Christophe Lanoix  24:42

Okay, so we’re gonna go from one task to the other to see it’s gonna take time. So what you’re gonna see will is that it’s not the typical question and answer type of LLM experience. It’s it’s gonna take quite some time. Sometimes it takes 15 minutes, 30 minutes, 45 minutes. Sometimes, because the system does actually a lot of work in the background, it is following a very strict process and methodology. Okay, the methodology of the engagement has been defined and is following is following it step by step, and it takes a bit of time. So here, W. So one question on the work package one: What form do you want now? So what I want is four points and an Excel. And question number two, research depth.

 

Jean-Christophe Lanoix  25:54

A kickoff meeting. Who sits across the table at the kickoff meeting? So Dana Whitfield, well, that’s the person who sent the email and the deal team. Yeah, okay, let’s go. What should I produce for the kickoff meeting? Briefing note, briefing note, and short short kickoff deck, data room. So let’s go for yeah briefing note and short kickoff deck. Yeah, let’s go. How much external research before the kickoff meeting? Known structured only. Okay, just for the sake of of going faster. All right, so that that’s the system is working right now on the free task. What I’m going to show you now will is examples that I run before the demo, so you can actually see examples of deliverables. So it’s on another RFP, hypothetical RFP, on a completely different topic, which is EV charging, electric vehicles charging. It comes from a fake, a made-up company, Verdor Group, which operate 100, 1,100 supermarkets across six countries in Europe. Most sites have large customer car parks, and basically they’re considering the opportunity to have charging points for EVs on their parking lot. Okay, so today we lease parking space to two charging operators under long-term agreement and earn a nominal fee. The board believes we are leaving value on the table and has asked management to assess bringing charging in-house. A board paper circulated in June states that the European EV charging market will be worth 25 billion by 2030. We would like this figure to be tested before any commitment is made. Okay, so the the objective is an independent, defensible view on whether the company should operate charging itself, and if so, where and how? Scope: We have market WP one work package one, then segmentation, then geography, then competition analysis, entry mode, and plan. What we’re gonna execute is WP one market, so yeah. So what’s the deliverable expected is a board ready deck, Excel model, and one page recommendation. So I run exactly the same exercise with this RFP, I built a proposal, which is let me see

 

Jean-Christophe Lanoix  29:17

This is exactly the same experience than what you’re seeing right now, I said I have just received the attach RFP. I want you to help me build the offer. Okay. Then the system asked a couple of questions, just like he did. How do you want to work? I said intermediate. What fee are you targeting for the eight weeks? I want to follow a realistic bottom-up approach with a detailed budget breakdown at the task and subtax level. You can come up with various scenarios and options. Who deliver me? What format PowerPoint relationship with existing relationship with customer called? Who has his likely bid? MBB Energy Specialist boutique and other independent. Okay, then the system went and delivered in a matter of maybe 10 minutes proposal of a structure for the well proposed structure for the proposal. So 70 slides, and well, obviously you listeners only listening to the podcast cannot see it, but it’s basically an overview, an outline of the presentation with 17 proposed slides in very different sections. So, at the beginning, pretty much the context, what we already know before the engagement starts. So the starting assumptions, let’s say, and then more of the objectives, the work packages, so the methodologies 123456, and the organization and the budget. Okay, so the the system gives you the overview of the proposal and asks you to to validate. So you don’t see it here, but I had a like a question box asking is it okay or not? So I said yes, and maybe half an hour later, the system has been working pretty hard, and it delivered a proposal in my template. So it’s natively within CoWork. This is Turbo Consultant template, which you saw before. Okay, and I get a fully fledged proposal. So here we have the content. Well, actually, I will open PowerPoint so we can see it better here. So the overview with the three sections. Okay, the introduction, the work packages, methodology, and then the budget and organization. So, well, here for example, on this slide, in the introduction, co-work outlines the missing data. So most of the available data from available scenarios on EV charging in Europe focus on everything but public charging. Okay, so right from the beginning, the system identified a missing element in the in the key data needed to execute. so we have, yeah. So you here another piece of of the presentation. This another piece of missing data is the system looked at all the well the selection of eight competitors, and basically they disclose information on on the charging point and the tariff, but nothing on the actual usage and their economics. Okay, so this is right from the beginning. We see that this is something that’s going to be pretty key in executing the assignment. How we get the data. And basically, the data will come from the client because he has already two parking operating with charging points with lease agreement. So this is what it is explained here. So the system, the key, the idea here is not to go in too much into the details, but just to show you that the system has perfectly understood the context and what is at stake, and what’s missing, and what we need to do to actually find that missing data. So we can keep going. So you see, this is really consulting grade slides. Okay, it’s not yeah, it’s not only in your template. It’s actually consulting grade. Okay, which is quite difficult to find on the marketplace. To be honest, either you have something in your template but not consulting grade or consulting grade, but not in your template. Here you have both natively inside of CoWork, and it it’s a huge time saver because you can actually rework everything right out of the box. Okay, so here you have the methodology with the different. Work packages, and yeah, the the detail of each work packages.

 

Jean-Christophe Lanoix  35:06

So here you can see in the RFP they proposed build by or partner, and the system actually proposed a fourth option, which is repricing their existing leasing agreement, which is again a smart idea. It’s it shows that it really understands what is talking about, and then we have the last section with the timeline. And yeah, something I didn’t like is the way he presents the budget. So I basically said it here. Oh yeah, I asked for a detailed budget in an Excel, so that’s what I had here.

 

Jean-Christophe Lanoix  36:05

Yeah my yeah the effort for each subtask, and then I say I don’t want to disclose the number of man days. This was only for internal use. I want you to rework the slides, certain slides, including how we present the budget. I don’t want to show my Mondays. Okay, if necessary, la la la. Only give me two, three slides separately. No need to rebuild the entire deck, and then it gives me yeah maybe five minutes later, two slides. So one on work package one presented differently without the mandates and the actual offer with the price, the value, but not the cost, not the mandates. So you can. It’s very easy to rework. You can do it manually, or you can ask the system to do it for you. Let’s go for. Let’s go and see where.

 

Jean-Christophe Lanoix  37:36

All right. So now kickoff preparation. So I did exactly the same. The project is starting. I want you to help me prepare for the kick-off meeting. 10 minutes later, I get my deck again in my template, it’s a very-it’s not a very difficult work to do as a consultant. It’s just you take your offer and you transform it into a deck for the kick-off meeting, but it’s just-it just takes time, right? It just takes takes time here. It’s so what we need from the client. So that’s the the data request. Okay. The timeline. Speaking of data requests, so he built me the table, the detailed Excel table of the data I need to request from the client here.

 

Jean-Christophe Lanoix  38:59

So let me zoom in here. So every piece of data item requested. Why is it needed? What work package? How critical? Etc. Etc. For all the data points that we need, this takes honestly two three hours if you’re a consultant. It gives me my briefing note that you can send to the client. Again, it’s not rocket science. It’s just again, it’s the proposal reformatted differently, but it just takes time. Okay. And it gives me my own internal briefing. So, who is in the room? The one thing to get right. So, the key objective of my meeting: who is in the room, what they want, what to give them. Yeah, this 25 billion number that we need to double check from the board how to handle it, and then the questions to ask in priority order, the objections, and what we can answer to the objections. So we already know the market is 25 billions. What need need you to? We need to tell us what to do about it. So what you what you should answer to that. The agenda here. All right. So now let’s let’s have a look where we’re at. So it’s still working. So you see, it’s you see it’s doing work here. So it’s the preparation of the kickoff meeting from for the other engagement. So it read the RFP, it wrote the kickoff briefing note, and now it’s building the kickoff deck. Okay, so you can see the to do list here. Now, the yeah. So let’s go back to the EV charging engagement, and I said I want you to help me execute work package one on market. Okay, same as you already saw. So it’s it worked. It took a it took a long time. It took maybe 45 minutes. And again, this is an extreme case. I do not recommend to go for such extreme level of automatization, okay, I do recommend to go co-construction and to interact as much as possible with the system. But this is just for the demo, and what we got is another very nice PowerPoint in my template. It could be in anyone’s template. Well, during the onboarding, you provide your template, and the system will just ingest it and reuse it. So you get here a very nice executive summary slide with the key the key conclusions, okay, and then yeah, the whole analysis. And one of the key part of the analysis is double checking the 25 billion of the from the board, and basically this is the the system is not a yes man because he actually pushed back on this number quite a lot, and it turned out this number is completely false. It’s just a capex total capex, but it’s not the actual revenue the company could get, and that was part of the analysis here. Okay, so what? Yeah, that’s that’s what you see here. You have the total market, and then then different. You peel the onion, and in the end, the real scope is is much smaller than anticipated. So here you see again a lot of analytical consulting grade slides,

 

Jean-Christophe Lanoix  43:55

And but the next question is, how do I know that it’s actually correct, and it’s not full of mistakes and hallucinations. And I’m glad you ask because I run the audit of this, and it’s here. Let me see. Yeah, it’s here. All right, here. So it’s in another thread. I want you to do the three audits for WP One Market Deliverables, both the PowerPoint and the Excel, and give me the three full audit reports. So the first layer of audit is full source traceability. For each claim, identify the sources, evaluate the quality of the sources and the level of confidence. Level two is internal audit; it’s co-work, creating a sub-agent who’s going to audit the main agent work. And l3, the third layer, is external audit. So it’s two external models, two external LLMs. Via via API, so you have Fable five, and you have GPT 5.6. So it’s a very powerful model that are going to audit the deliverable. Do not modify the deliverable just yet. Just provide me with your recommendation as well as the key point where my decisions are needed. So he went on, and maybe 30 minutes later delivered a report for the sources. Sources verification, yeah. So you see the summary here. So factual claims 47 verified 14 probable nine hypotheses 13 contradicted six unverifiable five confidence label that needs downgrading five and confidence label that needs upgrading one okay and then you have all the details. And one second, just one second. My screen is going to. It should be updated. Where is? Oh, sorry about that. All right.

 

Jean-Christophe Lanoix  46:36

So you see all the details here. Of you don’t have to read it yourself. You just ask the system to iterate, improve, audit again, and in five minutes or in 15 minutes you get a new version that is way better. Audit the second audit, internal audit, again here. Okay, so it’s pretty detailed, and the third layer of audit here. So you, what you see here is very interesting. So you have the two models, and you have all the criteria. Okay, internal coherence, conformity with the firm standard, voice and tone consistency, source quality, analytical rigor. You have, I don’t know, 20 different criteria, and two models that assess the deliverable according to these criteria. Okay. So what I did is to ask for a summary because it’s too much information. So he gave me a quick summary here, and it’s actually a very interesting one. The model is the strongest artifact in the engagement. The deck is writing checks it does not cash. Okay, so it has mistakes In it, and that’s why the audit is so valuable. Okay, because the document looks very nice, but in reality there are mistakes. And then he gives me the eight decisions I need to make on the perimeter, on WP one headline number, etc. His recommendation, and then I said, I want you to rework the deliverables by integrating all the relevant findings, including your eight recommendations. And then, yeah, maybe 30 minutes later, I get a new version here that integrates Everything. I think it it added additional slides, if I remember correctly. Yeah, this one is new. So it’s actually super useful, and it’s a key safeguard against a huge limitation of AI for consulting. The fact that it makes so many mistakes is, for me, it’s a absolutely absolute blocker for the use of AI in consulting, and this this layer of quality assurance is, in my opinion, a game changer. Because again, in very short amount of time, you can iterate and get to something that is ready for. Final review. So let’s see where we are at. It’s still working. Yeah, it’s still working on the kickoff preparation. It’s still working on the exhibit on the work package one, and it’s still working on the proposal as well. All right, so let me show you a couple of other features. This one here. Writing of service contracts-that’s another small task for a consultant that takes time, and it’s always the same. You have your template, just like here. Oops, is my screen still sharing? Hello.

 

Jean-Christophe Lanoix  51:22

Hang on one second. Stop sharing. All right. All right. Service agreement. So that’s that’s a typical service agreement, a template that any consultant has, and yeah, you have all those placeholders and for everything for your name, for the client name, the the address, the the scope, the engagement dates, etc. and you have your proposal, and you have to put your proposal inside your template. Okay, we we’ve all done that in the past. It takes time. It’s very annoying. So here, you just go. I have one. The attached proposal. I want you to prepare the service contract using my own template available in your workspace. So I gave it to him. So he asked me a couple of questions. I gave my own company’s information as a leave blank for the client, and then five minutes later, I get

 

Jean-Christophe Lanoix  53:04

service contract here, so it has filled in my company’s information. It left blank for for the client, and then we have the actual scope, the deliverables, the fees Here, the milestone for payments. Well, it took the proposal, put it in in in the contract. No rocket science, but again, it’s you save two hours here.

 

Will Bachman  53:36

That’s very cool. So powerful tool that you’ve built for listeners that want to go check it out, learn more. Where what’s the website? Where do they go online to check it out?

 

Jean-Christophe Lanoix  53:50

Sure, let me go back to the PowerPoint. You can go to www.turboconsultant.com And yeah, again, there is a promo code for your listeners. Unleashed underscore TC. They can also go to my LinkedIn account. I try to post every day on AI in consulting, so it’s Jean Christophe Lanois. I guess you will give the the link in the description.

 

Will Bachman  54:27

Fantastic! All right. Well, Jean Christophe, congrats on building Turbo Consultant. Looks like a pretty powerful tool. The powerpoints look beautiful. Really nice, nicely constructed pages. Thanks for joining, and thanks for extending the discount offer to listeners of the show.

 

Jean-Christophe Lanoix  54:47

Thank you very much. I’m glad you you liked it. It’s really a tool to yeah both. I mean, you according to my own measurement, and according to my actually my client feedback, you. Get a 25x on task like we saw today, proposal building or deliverable writing 25x. You can do several in parallel, so you get possibly a 50x, 100x, and the quality is preserved if not increased. So yeah, I’m very very excited and very glad that you invited me. Will, thank you very much.

 

Will Bachman  55:28

All right, thank you for joining.