1
00:00:00,040 --> 00:00:04,280
AI was supposed to make us more 
productive, which was supposed 

2
00:00:04,280 --> 00:00:06,200
to. 
Mean working less. 

3
00:00:06,400 --> 00:00:11,000
Yeah, a new study from UC 
Berkeley put researchers inside 

4
00:00:11,000 --> 00:00:15,240
a tech company for eight months 
and found, well, the complete 

5
00:00:15,240 --> 00:00:17,720
opposite. 
People using AI tools worked 

6
00:00:17,720 --> 00:00:21,480
more, not less. 
And to be honest, this mirrors 

7
00:00:21,480 --> 00:00:24,000
exactly. 
My experience and our. 

8
00:00:24,000 --> 00:00:27,440
Company's experience, too The 
study found that people took on 

9
00:00:27,440 --> 00:00:31,200
broader responsibilities, the 
line between work and rest. 

10
00:00:31,400 --> 00:00:32,040
Blurred. 
Very. 

11
00:00:32,040 --> 00:00:35,480
Fast and filled up every single.
Minute with. 

12
00:00:35,480 --> 00:00:38,400
More and more tasks nobody told 
them to. 

13
00:00:39,000 --> 00:00:42,280
The tools just made it easy 
enough that stopping felt like a

14
00:00:42,280 --> 00:00:44,800
waste of time. 
Today I'm covering exactly what 

15
00:00:44,800 --> 00:00:48,760
researchers found, why this 
pattern has repeated with every 

16
00:00:48,760 --> 00:00:52,640
major labour saving technology 
from the past 100 years, and 

17
00:00:52,640 --> 00:00:55,400
what sociologist theory of 
social acceleration. 

18
00:00:55,400 --> 00:00:58,240
Tells us about. 
Why Productivity Tools just 

19
00:00:58,240 --> 00:01:00,240
never seem to produce that 
spare. 

20
00:01:00,240 --> 00:01:02,440
Leisure time that they seem to 
promise. 

21
00:01:03,320 --> 00:01:24,840
This 
February, 20262 researchers at 

22
00:01:24,840 --> 00:01:27,160
Berkeley's High School of 
Business. 

23
00:01:27,280 --> 00:01:29,720
Published a piece in Harvard 
Business Review with the title 

24
00:01:29,720 --> 00:01:30,800
that. 
Well, it tells. 

25
00:01:30,800 --> 00:01:33,400
You a lot of things it says AI 
doesn't reduce work, it 

26
00:01:33,400 --> 00:01:36,000
intensifies it. 
They'd spent eight months inside

27
00:01:36,000 --> 00:01:37,720
a. 200. 
Person tech company. 

28
00:01:37,880 --> 00:01:40,120
Watching how people actually 
use. 

29
00:01:40,240 --> 00:01:42,040
AI tools in their day-to-day 
work. 

30
00:01:42,960 --> 00:01:46,200
So not in a lab, not a self 
reported study. 

31
00:01:46,640 --> 00:01:50,240
They were on site twice a week 
from April to December 2025. 

32
00:01:50,720 --> 00:01:53,880
And they did more than. 40 like 
in depth interviews across 

33
00:01:53,880 --> 00:01:57,360
engineering and product. 
Design research operations. 

34
00:01:58,120 --> 00:02:00,560
And they found. 3 distinct 
patterns. 

35
00:02:00,560 --> 00:02:03,680
Of work intensification. 
And all three of them are 

36
00:02:03,680 --> 00:02:06,760
actually voluntary and nobody 
was being forced to do more. 

37
00:02:06,840 --> 00:02:10,520
So let me run through those. 
The first was task expansion, 

38
00:02:10,759 --> 00:02:12,000
the second. 
Was. 

39
00:02:12,200 --> 00:02:15,280
Blurred boundaries and the third
was compulsive multitasking. 

40
00:02:15,440 --> 00:02:18,200
So for the first task expansion 
they called it. 

41
00:02:18,840 --> 00:02:20,240
Basically, they found that 
product. 

42
00:02:20,240 --> 00:02:23,760
Managers started writing code. 
Researchers took on engineering.

43
00:02:23,760 --> 00:02:27,800
Work People suddenly started 
absorbing tasks that would have 

44
00:02:27,800 --> 00:02:30,560
definitely been handed off. 
To another person in their. 

45
00:02:30,560 --> 00:02:34,000
Team or just never attempted 
because. 

46
00:02:34,080 --> 00:02:38,040
AI just made it feel possible. 
And the downstream effect of 

47
00:02:38,040 --> 00:02:39,480
this? 
Wasn't efficiency. 

48
00:02:39,480 --> 00:02:40,600
It was actually. 
Just load. 

49
00:02:40,600 --> 00:02:43,560
Redistribution, removing some 
bottlenecks. 

50
00:02:43,840 --> 00:02:45,880
And. 
Redistributing it across teams, 

51
00:02:46,200 --> 00:02:48,200
engineers found. 
Themselves becoming as well the 

52
00:02:48,200 --> 00:02:50,080
researcher. 
Described and as most people 

53
00:02:50,080 --> 00:02:53,880
working with AI coding quality 
inspectors. 

54
00:02:54,040 --> 00:02:55,560
For what could be described as 
a. 

55
00:02:55,640 --> 00:02:58,880
Sometimes fantastic, but often 
junior colleague as. 

56
00:02:59,080 --> 00:03:01,840
I said you had product. 
Managers starting to write code 

57
00:03:01,840 --> 00:03:04,000
themselves. 
In the product function, we're 

58
00:03:04,000 --> 00:03:07,040
already starting to see product 
manage pick up smaller bugs or 

59
00:03:07,040 --> 00:03:09,040
tasks. 
The same with designers. 

60
00:03:09,160 --> 00:03:12,040
Why would a designer? 
Design things just in Figma. 

61
00:03:12,040 --> 00:03:14,640
When you could be in core code 
with access to the code based. 

62
00:03:14,840 --> 00:03:16,440
On your local machine and start.
To. 

63
00:03:16,440 --> 00:03:19,880
Create things as well that could
actually just be merged there 

64
00:03:19,880 --> 00:03:21,600
and then. 
We've seen this happen, 

65
00:03:22,160 --> 00:03:23,480
everyone. 
Across our product. 

66
00:03:23,480 --> 00:03:28,120
Organization is now in an Ida 
developer environment basically,

67
00:03:28,840 --> 00:03:31,640
so suddenly everyone in the team
has access. 

68
00:03:31,640 --> 00:03:33,800
To the entire code base, both to
talk to to. 

69
00:03:33,800 --> 00:03:38,400
Investigate ideas and problems 
and theories to plan work. 

70
00:03:38,600 --> 00:03:40,680
But also to just. 
Start fixing things and getting 

71
00:03:40,680 --> 00:03:42,120
stuck in. 
And if people have the right 

72
00:03:42,120 --> 00:03:44,800
system set. 
Up what our company has suddenly

73
00:03:45,520 --> 00:03:48,760
anyone can start to produce 
something so yeah, that task 

74
00:03:48,760 --> 00:03:51,560
expansion certainly means that 
people are just. 

75
00:03:51,560 --> 00:03:54,040
Doing more work. 
That they previously didn't do. 

76
00:03:54,200 --> 00:03:57,480
And this brings us on to the 
second area of work 

77
00:03:57,480 --> 00:04:01,800
intensification that AI brought 
which was blurred boundaries so 

78
00:04:01,800 --> 00:04:03,240
because. 
Prompting an AI. 

79
00:04:03,240 --> 00:04:06,840
Is just so simple and easy it 
literally takes seconds it feels

80
00:04:06,840 --> 00:04:09,760
like nothing work. 
Started to easily seep into a 

81
00:04:09,760 --> 00:04:11,360
lunch break. 
You could go on your phone. 

82
00:04:11,360 --> 00:04:14,560
I do this all the time and just.
Quickly voice note Claude. 

83
00:04:14,720 --> 00:04:16,959
Because you know it's important 
for the next task and you want 

84
00:04:16,959 --> 00:04:20,480
to make sure that Claude is 
working whilst you rest and eat.

85
00:04:20,640 --> 00:04:23,120
I'm terrible for this, whether 
I'm with friends with whom 

86
00:04:23,560 --> 00:04:25,880
having lunch, whether I'm in a 
meeting. 

87
00:04:26,120 --> 00:04:27,440
I'm thinking about what the 
next. 

88
00:04:27,440 --> 00:04:29,280
Prompt is or. 
The next thing is that I need 

89
00:04:29,280 --> 00:04:32,200
this different set of AIS to go 
and do for me and so very 

90
00:04:32,280 --> 00:04:35,800
easily. 
I have 456 tasks going on and 

91
00:04:35,800 --> 00:04:37,960
I'm doing them and managing them
at all times of the day. 

92
00:04:38,160 --> 00:04:39,960
So yeah, the research found that
workers. 

93
00:04:39,960 --> 00:04:42,400
Realized, often in hindsight, 
that. 

94
00:04:42,400 --> 00:04:44,800
Downtime no longer. 
Provided that. 

95
00:04:44,800 --> 00:04:46,200
Same sense of. 
Recovery. 

96
00:04:46,400 --> 00:04:49,800
And as a result, work fell even 
less bounded and a bit. 

97
00:04:49,800 --> 00:04:51,480
More ambient, something that 
could. 

98
00:04:51,480 --> 00:04:53,040
Always be. 
Advanced a little. 

99
00:04:53,040 --> 00:04:55,280
Bit further with just a little 
bit of effort. 

100
00:04:55,400 --> 00:04:58,240
So again, that was another. 
Way that AI. 

101
00:04:58,240 --> 00:05:01,680
Intensified work. 
And this comes on to the third. 

102
00:05:01,960 --> 00:05:05,080
Way that AI intensified work. 
Which was? 

103
00:05:05,560 --> 00:05:08,640
Compulsive multitasking. 
Suddenly they found that workers

104
00:05:08,640 --> 00:05:11,120
are running multiple. 
AI processes just at the same 

105
00:05:11,120 --> 00:05:13,560
time, you know, keeping several 
threads. 

106
00:05:13,560 --> 00:05:17,000
Alive at once. 
Reviving you know certain tasks 

107
00:05:17,000 --> 00:05:20,200
because the AI could just handle
them in the background. 

108
00:05:20,960 --> 00:05:23,080
And in this research? 
Study, they actually said, and I

109
00:05:23,080 --> 00:05:25,000
quote this. 
Created a rhythm where the both 

110
00:05:25,000 --> 00:05:27,680
the human and the. 
Machine were constantly in 

111
00:05:27,680 --> 00:05:31,520
motion and I think one engineer 
captured this fantastically in 

112
00:05:31,520 --> 00:05:32,880
this paper. 
You had a. 

113
00:05:32,880 --> 00:05:35,120
Thought that maybe. 
Oh, because you could be more. 

114
00:05:35,120 --> 00:05:37,720
Predictive with AI. 
Then you could save some time 

115
00:05:37,720 --> 00:05:39,080
and you could. 
Therefore work less. 

116
00:05:39,440 --> 00:05:41,320
But then really. 
You don't work less, you just 

117
00:05:41,360 --> 00:05:43,040
work the same amount. 
Or even more. 

118
00:05:43,520 --> 00:05:46,320
And our team often jokes about 
this Barry, the CEO who who, you

119
00:05:46,320 --> 00:05:49,000
know, programs every single day,
often jokes that it's made him 

120
00:05:49,000 --> 00:05:51,920
tireder than ever before in his 
entire career. 

121
00:05:52,080 --> 00:05:53,600
And I just said I'm terrible for
this. 

122
00:05:53,600 --> 00:05:56,480
Just suddenly multitasking all 
the time with different tasks. 

123
00:05:56,640 --> 00:05:59,280
And it could even be personal 
tasks as well and personal 

124
00:05:59,280 --> 00:06:01,320
projects I'm making sure I've 
got on the go. 

125
00:06:01,320 --> 00:06:04,800
And you know, just naturally you
suddenly have increased 

126
00:06:04,800 --> 00:06:06,960
expectations to. 
Produce more work. 

127
00:06:07,160 --> 00:06:09,400
And as a result of those 
expectations rising. 

128
00:06:10,200 --> 00:06:12,320
There's no real. 
Productivity game because you 

129
00:06:12,320 --> 00:06:15,920
fill that spare time doing more 
to meet that expectation. 

130
00:06:16,040 --> 00:06:19,760
So yeah, these three patterns 
created a self reinforcing cycle

131
00:06:19,760 --> 00:06:21,800
and the the research report 
talks about this. 

132
00:06:22,200 --> 00:06:24,960
Essentially AI accelerated. 
Certain tasks which raised 

133
00:06:24,960 --> 00:06:27,960
expectations for speed, not 
through certainly explicit 

134
00:06:27,960 --> 00:06:30,600
demands, but just what became 
visible. 

135
00:06:30,880 --> 00:06:34,360
And normalized in everyday. 
Work, you know, higher speed 

136
00:06:34,360 --> 00:06:37,880
made work is more reliant on AI 
increased reliance. 

137
00:06:37,880 --> 00:06:41,360
On AI, widen the scope of what? 
Therefore, people attempted to 

138
00:06:41,360 --> 00:06:43,840
do, you know, taking on task 
from another person's job role 

139
00:06:43,960 --> 00:06:45,840
and as a result of that. 
Wider scope. 

140
00:06:46,480 --> 00:06:48,720
The total volume of work 
Therefore, suddenly. 

141
00:06:48,720 --> 00:06:51,960
Increased and then the cycle 
continues with nobody really at 

142
00:06:51,960 --> 00:06:54,240
the controls. 
So yeah, increased capability 

143
00:06:54,240 --> 00:06:57,680
leads to increased output, which
leads to increased expectations,

144
00:06:57,920 --> 00:07:02,760
which then increase the amount 
of pressure to expand and 

145
00:07:02,760 --> 00:07:05,640
improve further. 
So essentially self regulation 

146
00:07:05,640 --> 00:07:07,720
failed. 
You know, self regulation of all

147
00:07:07,720 --> 00:07:10,960
of us individuals has completely
failed and. 

148
00:07:11,120 --> 00:07:12,440
The researchers were quite 
explicit. 

149
00:07:12,440 --> 00:07:14,040
About why they think this 
happened. 

150
00:07:14,440 --> 00:07:16,440
And they put it. 
Down to three reasons, which is 

151
00:07:17,320 --> 00:07:20,840
#1 the intensification felt 
really rewarding, you know? 

152
00:07:20,840 --> 00:07:23,560
Workers described. 
Momentum and the ability to 

153
00:07:23,560 --> 00:07:26,040
expand capability. 
Or the thrill of suddenly. 

154
00:07:26,040 --> 00:07:27,200
Being able to do things they've 
never done. 

155
00:07:27,200 --> 00:07:29,320
Before I I've. 
Certainly felt that as a huge 

156
00:07:29,320 --> 00:07:31,520
driver. 
Second, because the work was 

157
00:07:31,520 --> 00:07:34,480
voluntary. 
Neither the workers nor their 

158
00:07:34,480 --> 00:07:36,000
managers. 
Recognized it as. 

159
00:07:36,040 --> 00:07:41,000
Overwork and 3rd as colleagues 
expanded their output informal. 

160
00:07:41,000 --> 00:07:43,840
Expectations also reset. 
So what was once, you know, 

161
00:07:43,840 --> 00:07:47,080
extra effort became just, you 
know, the minimum standard of 

162
00:07:47,080 --> 00:07:50,080
expectation for performance. 
And I think for those that have 

163
00:07:50,080 --> 00:07:53,120
gone really far. 
Into using AI within teams 

164
00:07:53,120 --> 00:07:56,160
structuring everything around AI
and how to get the best out of 

165
00:07:56,200 --> 00:07:59,640
AI like our entire way of 
working at our company is 

166
00:07:59,640 --> 00:08:01,160
stricture around AI you're 
probably. 

167
00:08:01,160 --> 00:08:02,920
Going to resonate with a lot of 
what I'm saying. 

168
00:08:03,520 --> 00:08:05,760
It's described exactly what's 
happened at Mindset. 

169
00:08:05,760 --> 00:08:08,440
Our output is insane and. 
What you. 

170
00:08:08,680 --> 00:08:13,120
Might expect from a single 
person over weeks a year ago. 

171
00:08:13,640 --> 00:08:16,240
I have an expectation to produce
in days. 

172
00:08:41,799 --> 00:08:43,240
Because I know it's. 
Possible if you're. 

173
00:08:43,240 --> 00:08:46,440
Using AI properly again, back to
that schools discussion last 

174
00:08:46,440 --> 00:08:49,080
week and it's really interesting
I mean for those that listen 

175
00:08:49,080 --> 00:08:52,240
every single week, any 
opportunity to look back in time

176
00:08:52,240 --> 00:08:55,600
and trying to understand, you 
know, why does this feel like it

177
00:08:55,600 --> 00:08:57,800
keeps happening because it isn't
new. 

178
00:08:57,960 --> 00:09:00,520
So there's a really interesting 
history to this and a really 

179
00:09:00,520 --> 00:09:04,200
interesting theory about why us 
as humans cannot just be 

180
00:09:04,200 --> 00:09:08,400
satisfied with that increased 
output and suddenly have leisure

181
00:09:08,400 --> 00:09:12,360
time to go enjoy with our family
and and our hobbies and and do 

182
00:09:12,360 --> 00:09:14,520
things that are nice. 
Because yeah, this isn't new. 

183
00:09:14,680 --> 00:09:16,960
And this pattern has repeated 
with almost. 

184
00:09:16,960 --> 00:09:18,960
Every technology sold as a time 
saver. 

185
00:09:18,960 --> 00:09:21,760
For over 100 years in the 
1920's, the average American 

186
00:09:21,760 --> 00:09:24,560
woman spent roughly 60 hours a 
week on housework. 

187
00:09:24,800 --> 00:09:27,760
So cooking, cleaning, washing, 
fixing things. 

188
00:09:27,960 --> 00:09:32,160
And so by the 50s there was. 
Now a washing machine, a vacuum 

189
00:09:32,160 --> 00:09:35,040
cleaner, refrigerator and a gas 
stove in most people's homes. 

190
00:09:35,520 --> 00:09:38,160
And so the difference. 
Between the 1920s spending 60 

191
00:09:38,160 --> 00:09:41,200
hours a week and the 50s with 
all that new technology to make 

192
00:09:41,200 --> 00:09:43,480
things easier. 
You know, what do we what do we 

193
00:09:43,480 --> 00:09:47,720
think the. 
Housewife spent on cleaning per 

194
00:09:47,720 --> 00:09:50,000
week. 
It's about 60 hours a week 

195
00:09:50,000 --> 00:09:51,840
again, and you can look at other
technologies for the 

196
00:09:51,840 --> 00:09:55,960
spreadsheet. 20 hours of manual 
calculation suddenly done in 15 

197
00:09:55,960 --> 00:09:57,480
minutes. 
Well. 

198
00:09:57,480 --> 00:10:00,680
What was the outcome? 
Accounting clerks of people 

199
00:10:00,680 --> 00:10:04,560
doing accounting fell by 400,000
people when it was invented, yet

200
00:10:04,560 --> 00:10:08,320
counters and auditors rose by 
over 600,000 with e-mail. 

201
00:10:08,880 --> 00:10:10,760
Handful of memos. 
Per day. 

202
00:10:10,760 --> 00:10:13,160
Became 100. 
And 21 emails and 11 hours of 

203
00:10:13,160 --> 00:10:15,600
work a week for cars, a 
researcher found. 

204
00:10:15,600 --> 00:10:18,960
That in 1994, humans spent 
roughly one hour. 

205
00:10:18,960 --> 00:10:21,000
Per day. 
Commuting regardless of era 

206
00:10:21,000 --> 00:10:22,760
culture. 
And even technology. 

207
00:10:23,040 --> 00:10:24,920
So basically. 
As cows got better, we traveled.

208
00:10:24,920 --> 00:10:27,520
For further inside them. 
Because they were. 

209
00:10:27,520 --> 00:10:28,880
Better and it was easier to 
travel. 

210
00:10:29,000 --> 00:10:31,280
The point being the. 
Mechanism is always. 

211
00:10:31,280 --> 00:10:35,080
The same so technology gets 
better and reduces the cost per 

212
00:10:35,080 --> 00:10:38,200
unit of that activity. 
So it makes it easier to do that

213
00:10:38,200 --> 00:10:41,080
thing yet. 
As a result, the volume of that 

214
00:10:41,080 --> 00:10:44,080
activity just. 
Increases, so we do more of it 

215
00:10:44,680 --> 00:10:48,560
and we just consume the savings 
in time and effort that we would

216
00:10:48,560 --> 00:10:50,720
have gained regardless of the 
technology. 

217
00:10:51,320 --> 00:10:53,320
So that new volume just becomes 
the baseline. 

218
00:11:16,000 --> 00:11:17,400
And there's a lot of theories 
behind this. 

219
00:11:17,600 --> 00:11:18,840
There's a well. 
Known thinker who? 

220
00:11:18,840 --> 00:11:21,680
Explains how this happens 
perfectly called Hartman. 

221
00:11:21,680 --> 00:11:24,520
Rosa, a German sociologist, and 
it gives you a really 

222
00:11:24,520 --> 00:11:27,360
interesting perspective on not 
just this discussion. 

223
00:11:27,880 --> 00:11:30,080
But why the world often in 
modern? 

224
00:11:30,080 --> 00:11:32,440
Times just feels quite chaotic. 
You know Rosa. 

225
00:11:32,440 --> 00:11:34,120
'S core argument, which was laid
out in the. 

226
00:11:34,120 --> 00:11:36,440
Book. 
Social acceleration, is that 

227
00:11:36,440 --> 00:11:38,480
modern? 
Societies are caught in what he.

228
00:11:38,480 --> 00:11:41,320
Describes a triple acceleration,
so you get. 

229
00:11:41,320 --> 00:11:43,840
Technology acceleration. 
So things just get faster. 

230
00:11:44,600 --> 00:11:47,560
Acceleration of social change. 
So institutions, norms and 

231
00:11:47,560 --> 00:11:50,520
expectations shift really fast 
as a consequence. 

232
00:11:50,680 --> 00:11:53,040
And the acceleration of the pace
of life. 

233
00:11:53,160 --> 00:11:55,760
Despite all the time saving 
technology, individuals just 

234
00:11:55,920 --> 00:11:58,840
feel more time pressure and the 
critical insight I think is that

235
00:11:59,320 --> 00:12:02,160
these three just feed into each 
other, into a loop that has no 

236
00:12:02,160 --> 00:12:05,560
natural stopping point. 
And which is the just the story 

237
00:12:05,560 --> 00:12:07,880
of? 
Capitalism, Rosa actually called

238
00:12:07,880 --> 00:12:11,320
this the process of dynamic 
stabilization, which is 

239
00:12:11,320 --> 00:12:14,560
essentially a fancy word for the
modern institutions and 

240
00:12:14,560 --> 00:12:18,760
companies and economies can only
maintain their stability by 

241
00:12:18,760 --> 00:12:22,040
continually trying to grow and 
accelerate and go faster. 

242
00:12:22,920 --> 00:12:25,080
And standing still means you're 
falling behind. 

243
00:12:25,600 --> 00:12:28,120
Just like the bicycle. 
You have to just constantly keep

244
00:12:28,120 --> 00:12:30,120
paddling, otherwise you're just 
going to fall over. 

245
00:12:30,280 --> 00:12:30,960
So what? 
What's? 

246
00:12:30,960 --> 00:12:32,560
Really interesting about this is
and what does. 

247
00:12:32,600 --> 00:12:35,320
What does it explain why 
everything continuity still 

248
00:12:35,320 --> 00:12:38,760
feels the same no matter how 
much cool technology comes 

249
00:12:38,760 --> 00:12:39,840
about? 
Well. 

250
00:12:40,280 --> 00:12:42,520
Rosa called that. 
Standstill, which is when 

251
00:12:42,520 --> 00:12:45,680
everything is in constant motion
but nothing changes. 

252
00:12:46,240 --> 00:12:49,200
So the act of constantly being 
in motion means that nothing can

253
00:12:49,200 --> 00:12:51,400
change. 
Technology shift, fashion 

254
00:12:51,400 --> 00:12:53,680
changes, work gets busier. 
And yet the basic. 

255
00:12:53,680 --> 00:12:55,720
Experience of. 
Falling or feeling like you're 

256
00:12:55,720 --> 00:12:59,360
behind, Feeling stretched, 
feeling like things are never 

257
00:12:59,360 --> 00:13:01,200
enough. 
That just stays the same because

258
00:13:01,200 --> 00:13:02,680
the treadmill is only getting 
faster. 

259
00:13:02,800 --> 00:13:04,800
And I think that Berkeley study 
is a case. 

260
00:13:04,800 --> 00:13:06,640
Study of this playing out. 
On the level. 

261
00:13:06,640 --> 00:13:09,960
Of individual workers in AI. 
But the more they did, the more.

262
00:13:09,960 --> 00:13:13,120
That was expected and you know, 
this expectation becomes the new

263
00:13:13,120 --> 00:13:15,800
flaw and that's why. 
AI so far. 

264
00:13:15,960 --> 00:13:18,800
Doesn't save us time, it makes 
us work more. 

265
00:13:19,000 --> 00:13:22,040
Anyway, I hope you enjoyed the 
episode and I'll see you next 

266
00:13:22,040 --> 00:13:22,280
week.