How to Build a High-Performing Team for the AI Search Era

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 lefelu'r staff o ran y ddylai llyfrgell ddiwylliannol, a ydynt yn ceisio gwneud model LLM o ran y staff? Felly, dwi eisiau mynd yn y ffordd i gynnig i ddechrau gyda hyn, ac rwy'n eich eisiau i chi ddweud yn gyntaf, a ydynt yn cael ymwybodol o staff a'u gwella gyda'r AI, neu a ydych chi'n oeiniadu ei fod yno i gysylltu â'r staff sydd ar gael? Felly, rwy'n credu bod y cyfrifiad yn ddigwyddiadol, o ran yr hyn rydych chi'n ei wneud.

Mads Singers: Rwy'n credu, pan ddechreuodd AI, roedden ni'n gweld llawer o ffyrdd o weithwyr sy'n stopio'u hyfforddi, ac roedd y ffyrdd o weithwyr sy'n ymgyrchu ar y sefydliad. Mae wedi bod yn ddiddorol iawn i weld y 12 mlynedd diwethaf. Nid ydyn ni wedi tyfu'n fwy na'r ffyrdd rydyn ni'n tyfu nawr. Felly mae llawer o bobl yn sylweddoli, amser, eu bod nhw'n ei gynllunio, amser, maen nhw'n dal i fwyno, ac oherwydd AI, gallant fwyno'n fwy na'r ffyrdd, ond maen nhw'n dal i fwyno staff. Felly rwy'n credu bod y cyfrifiad yn rhan o'r rhan yma i'r rhan fwyaf o'r cymdeithasau. Felly bydd y rhan fwyaf o'r cymdeithasau yn dal i fynd i'w hyfforddi â phobl, ond byddai'n ymddangos yn ychydig o ffyrdd gwahanol o bobl. Oherwydd, ar hyn o bryd, byddwn i ddim yn hyfforddi unrhyw staff newydd os nad oes ganddyn nhw sgiliau gyda'r AI. Felly byddwn ddim yn edrych ar hyfforddi'r cyfrifiad, byddwn ddim yn edrych ar hyfforddi'r cymdeithas, byddwn ddim yn edrych ar hyfforddi'r bobl hwn os nad oes ganddyn nhw sgiliau AI. In-house training, it's a lot easier and it's it's not that difficult to train, so we definitely start by training our in-house team first. But when we're looking at new people, if you find people who already have some decent understanding of AI, it's a lot faster getting them out to speed.

James Dooley: When you're looking to build a team in the AI era, then I want to role play something here, because it's happened in one or two of the businesses. One or two of them have been absolutely fine, but one or two of the businesses, we've got existing staff that are not willing to embrace AI. And some of them was A players, some of them was brilliant members of staff. But since AI has come along, you can see them dipping and dipping, all the KPIs, they're dropping. And some of these, what I would deem as being lazier members of staff back then, that would switch off and stuff like that, they have seemed to have excelled because now they like going and getting AI to do the work from it. But the point is, it's that good now with regards to the KPIs. The people that I initially thought was quite lazy, but we kept them on, it was just about good enough. They've now excelled, and some of them that was the A players that was literally in the top 10 performers, now are struggling. And at what point, if they're not willing to embrace the AI, even if you've tried to nurture them along the way, they just like the point blank refuse to have it helping them, saying, oh, I know better. At what point there do you have to think we need to replace?

Mads Singers: So from a management standpoint, it's key to make it clear. And what I mean with that is that when you're talking with your staff, it's not just, hey, you should be using AI. It's, James, 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 let them go.

James Dooley: Yeah, for sure. And then we've got the new staff, right? So you're looking to build out the team in the AI era. You're saying, OK, we know 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 realises 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 starts 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.

James Dooley: And then I've got another one, freelancers 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: 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. 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. A good example of it would be 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 is things that we want to do continuously? I generally much prefer hiring in-house.

James Dooley: 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?

Mads Singers: 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.

James Dooley: Do you think trying to play devil's advocate on the flip side, 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 FOMO or they're strengthening up a team too much with AI that they're trying to do everything? They're trying to do codex as well as cloud 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.

Mads Singers: 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 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 looks like, if you don't understand the platforms, you aren't going to succeed. So the starting point is look at what are you doing today? Sit down, find a staff member, literally sit down with them and look at what are they doing. Because reality is anything you do on a computer today can be optimized.

James Dooley: 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.