Building a Team for AI Search: Hiring, Upskilling and Productivity with Mads Singers

James Dooley: Gweithredu tîm yn yr era AI, heddiw rwy'n cysylltu â Mads Singers, ac nid oes un o'n i'n well i siarad am hyn na'ch hun. Yn amlwg, rwy'n gwneud llawer o gysylltiadau busnes a hyfforddiant. Rydych chi wedi helpu i mi gyrraedd tîm fawr yn enwedig dros nifer o busnesau gwahanol, ond mae llawer o anhygoel mewn sefydliad gyda, a ydynt yn cymryd mwy o staff? A ydynt yn cael ymwybodol o staff? A ydynt yn ceisio cynyddu staff o ran ddysgu diwylliant ddiwylliant? Beth y bydd modd LLM yn ei wneud o ran staff? Felly, rwyf am ddod yn ôl i mewn i ddechrau, ac rwyf am i chi ddweud yn gyntaf, a ydynt yn cymryd mwy o staff a'u gweithredu gyda'r AI? A ydych chi'n meddwl y byddai'n ymwneud â chyflwyno staff o ran ddysgu diwylliant? Felly, rwy'n credu bod y cyfrifiad yn ddigwyddiadol yn ymwneud â'r hyn rydych chi'n ei wneud.

Mads Singers: Rwy'n credu, pan ddechreuodd AI, roedden ni'n gweld llawer o fyrdd o weithredu'n cymryd, ac ar y ddechrau, roedd yn ddiddorol iawn i weld y 12 mlynedd diwethaf. Dydyn ni ddim wedi tyfu'n fwy na'r hyn rydyn ni'n tyfu nawr. Felly, mae llawer o bobl yn sylweddoli, mewn amser, eu bod nhw'n angen cymryd staff, ond mewn amser, maen nhw'n dal i fyny, ac oherwydd AI, maen nhw'n gallu fyny yn fwy cyflym, ond maen nhw'n dal i fyny yn angen staff. Felly, rwy'n credu bod y reoliad yma yng nghanol i'r rhan fwyaf o'r cymdeithasau. Felly, bydd y rhan fwyaf o'r cymdeithasau yn dal i fynd i'w hyrwyddo o bobl, ond bydd y rhan fwyaf o'r cymdeithasau yn wahanol o bobl. Oherwydd, ar hyn o bryd heddiw, byddwn ddim yn hyrwyddo unrhyw staff newydd nid ydyn nhw'n cael sgiliau gyda'r AI. Felly, byddwn ddim yn edrych ar hyrwyddo margedur, byddwn ddim yn edrych ar hyrwyddo gweithwyr, byddwn ddim yn edrych ar hyrwyddo'r bobl hyn, os nad oedden nhw'n cael sgiliau AI. Mae'n llawer mwy cyffredin, ac nid yw hynny'n anodd i'w hyrwyddo. Felly, byddwn yn deffinio dechrau gan hyrwyddo ein tîm ymhell ymlaen yn gyntaf, ond pan ydyn ni'n edrych ar bobl newydd, os ydych chi'n troi pobl sydd ganddyn nhw gwybodaeth dda o AI, mae'n fwy cyflym iddyn nhw allu siarad. Felly, pan ydych chi'n edrych ar y tîm yn yr era AI, rwy'n eisiau gwneud rhywbeth yma, oherwydd mae'n digwydd mewn un neu ddau o'r busnesau. Un neu ddau o'r busnesau, rydyn ni wedi cael staff sy'n byw, nad ydyn nhw'n eisiau cyflawni AI. Roedd rhai ohonyn nhw yn chwaraewyr, roedd rhai ohonyn nhw yn aelodau briliant, ond ers bod AI wedi dod ymlaen, gallwch eu gweld nhw'n dipio a'u dipio, mae'r holl KPIs yn dod, ac rhai ohonyn nhw, yr hyn rydw i'n ei ddimio fel aelodau mwyaf o staff, yn ôl hynny, a byddai'n newid a pethau fel hynny, maen nhw'n edrych ar hynny, oherwydd nawr maen nhw'n mynd i gael AI i wneud y gwaith ono. Ond y pwynt yw bod hynny'n dda nawr o ran y KPIs. Roedd y bobl rydw i'n debyg ei fod yn ddiddor iawn, ond roeddwn i'n eu cymryd ac roeddwn i'n debyg eu bod yn dda iawn. Maen nhw wedi cyflawni nawr, a rhai ohonyn nhw sy'n aelodau briliant, roedd yn y top 10 o gyflwynor, ac maen nhw'n siarad. Ac ar beth o bryd, os nad ydyn nhw'n ddiddor iawn i ymdrechu â'r AI, efallai os ydych chi wedi ceisio eu hymdrechu ar y ffordd, mae'r pwynt blaenau yn ymddangos eu bod yn eu helpu, yn dweud, rydw i'n gwybod'n well. Ar beth o bryd yna, mae'n rhaid i chi feddwl ein bod yn rhaid i ni ddewis?

James Dooley: Felly, o ran gweithredu, mae'n bwysig gwneud hynny'n glir. Ac yr hyn rydw i'n ei ddweud gyda hynny yw, pan fyddwch chi'n siarad gyda'ch staff, nid dim ond, hei, byddai'n rhaid i chi ddefnyddio'r AI. Mae'n dweud, James, you know, you used to be our number one guy. However, now seven people are way faster and better than you. If you don't get into AI, eventually I'll have to let you go. So it's setting clear expectations on that front up first. Now, at some point, if just like I do with anyone, if you have people that are not performing, and it doesn't really matter what the reason is, but if your people are not performing compared to the rest of your team, at some point you'll let them go.

Mads Singers: Yeah, for sure.

James Dooley: And then with regards to new staff, right? So you're looking to build out the team in the AI era. You're saying, okay, we're now, we're going to embrace it. We're here, we want some new staff. You mentioned there about the need to have some sort of AI experience, but surely as long as they're asking the right questions and they're willing to learn it, at that point, let's say some people, I know certain people that are very intelligent and I think would be good with AI. And they just thought that AI was chat GPT and then it realizes other LLM models. But what point there do you think, actually, I think these would embrace it. They would be good at it. You can hire those people for sure.

Mads Singers: What my experience has been, so we use Cloud Code a lot. And what I've seen with people using Cloud Code already, even if they have less skill, because they already get it, the productivity just start insanely high. So I would personally, right now, look for people who have done a bit with it. Because again, if you haven't been used to prompting, yes, you can learn it, but it will take a bit of time to learn. So again, you always need to look at the potential talent around. If you have someone who is miles better, would I take them based on someone who doesn't really know what they're doing? For sure. But if you have people that are somewhat around the level, equal level, and one of them have used a lot of AI and the other one haven't, I would definitely pick the AI person, even if they're slightly behind another metric. Just again, because it's all about productivity. It's all about outcome. And then I've got another one, freelancers.

James Dooley: Yep. Outsourcing the work versus in-house staff. You're looking to grow in the AI area. You're looking to build a team. They could be freelancers, could be someone you outsource to, or they could be in-house staff. They could be remote, or they could be in the office. At what point do you decide whether it's better to use freelancers or it's better to kind of have the team in-house?

Mads Singers: So for me, there's generally not a right or wrong. What I love doing is that when there's expertise, we don't have in-house and that I don't necessarily want to own. So that could be, let's say we want to set up a particular kind of website or we want to do something that we don't normally do and we might not plan to do it long-term. So a good example of it would be like a very good UI designer. I might get a UI designer in to do a specific project or a specific website or a specific app. And then when that's done, I don't need them anymore. Now in that case, I really prefer freelancers because I don't need to find someone, make sure they can do their thing even though I don't know what it is. So finding a freelancer who knows what they're doing, getting them to do the thing and then say, okay, thanks, all good. When it's things that we want to do continuously, I generally much prefer hiring in-house. And then as a business coach and a business consultant at present, what are you seeing business owners doing wrong with regards to maybe it's not even embracing the AI either, not even embracing cloud code, which is what you've mentioned. What are you finding people doing wrong that you're going, they're on a recipe for disaster?

James Dooley: Again, wrong is always a difficult word. I think the biggest thing is people are just missing out on opportunity right now. I think right now it's probably the biggest growth opportunity for most businesses. And it's so easy for people to say, oh, I'm too busy to look at this stuff. I think the biggest mistake for most of the companies is that they're really struggling to embrace AI. And a lot of companies are using it to an extent, but everything is possible now.

Mads Singers: Do you think trying to play devil's advocate on the flip side, which I don't, by the way, but I'm just trying to play, so you're looking at both sides. So you're saying that it's just really almost like they're not ambitious enough and understanding the opportunity. Do you think there's ever anyone at present that's getting formal or they're strengthening up a team too much with AI that they're trying to do everything, that they're trying to do codex as well as code code and they've got one team using this LLM model and someone over here is using a different thing that they're trying to take over the world, but then they're not being cited by exactly who they are and what they do.

James Dooley: So the biggest thing that I talk with my clients is start by doing the things you're doing today. Where I see people getting super sidetracked is that when they start trying to AI a bunch of stuff that they've never done. So, so many companies are like, oh, we've never done social, let's automate social. It's like, if you've never done it, if you don't know what success look like, if you don't understand the platforms, like you aren't going to succeed, right? So the starting point is look at what are you doing today? Like sit down, like find a staff member, literally sit down with them and look at what are they doing, right? And say, hey, like, because reality is anything you do on a computer today can be optimized, right?

Mads Singers: Yeah, for sure. Anyone who's watching the episode of building a team in the AI era, I'd strongly recommend checking out a couple of links in the description. We've got one on how to hire staff in the AI era and then we've got another one about leveling up existing staff. Mads, it's been an absolute pleasure. As always.