Artwork for podcast "Women in Tech Wisdom" by David Kaselow
From Linguistics to AI: Why Your Non-Linear Path is Your Superpower
Episode 11 • 4th March 2026 • "Women in Tech Wisdom" by David Kaselow • David Kaselow
00:00:00 00:44:07

Share Episode

Shownotes

In this first English episode, we sit down with Dorota Mleczko, a linguist turned AI specialist who has navigated the complexities of tech across multiple countries.

Dorota shares her unique perspective on how language models are evolving, the reality of the gender pay gap in different European markets, and why women must take the driver's seat in their careers.

This episode is a must-listen for anyone interested in the intersection of humanities and technology!

Guest Bio:

Dorota Mleczko is an AI trainer and consultant and always is empowering women to claim their space in the tech ecosystem.

With an international career spanning several countries, she teaches business professionals how to use AI effectively - explaining complex tools in plain language that anyone can understand.

Key Takeaways:

  1. The Linguistic Edge in AI: Understanding why a background in languages is vital for the development and ethics of Artificial Intelligence.
  2. Navigating the Gender Pay Gap: Practical insights on why women often start at a disadvantage and how to negotiate based on market value, not just past salary.
  3. The "Expat" Growth Mindset: How moving between countries (Poland, Spain, etc.) fosters resilience and a broader professional network.
  4. The Power of Mentoring: Moving from seeking guidance to providing it, and how role models change the trajectory of a career.
  5. Career Sovereignty: Why Dorota advocates for "not waiting to be picked" and instead creating your own opportunities.

Memorable Quotes:

"Stop waiting for the perfect moment. Especially for women—stop waiting to be hired, stop waiting for permission. Start your own thing."

"AI is not just about code; it’s about how we communicate. That’s where the magic happens between technology and linguistics."

Resources & Links Mentioned:

  1. Dorota on LinkedIn: https://www.linkedin.com/in/dorota-mleczko-ai-for-agility/
  2. Dorota’s website and Skool Community: https://www.palomasacademy.ai/

https://www.skool.com/palomas-ai-academy/

  1. Women in AI online Panel, March 9th, 7PM CET (LinkedIn/ Zoom): https://tr.ee/F7x0Jl

Call to Action:

If you enjoyed this episode, please leave a review and share it with a friend who is looking to transition into tech! Don't forget to subscribe for more inspiring stories from women leading the digital revolution.

______________________________________________________

Willkommen zum neuen Podcast „Women in Tech Wisdom“ von David Kaselow. Es erwarten euch Realtalk und Inspiration mit spannenden Frauen aus der IT- und Tech-Branche!Über ihren Werdegang, Vorbilder und alles, was sie Mädchen und jungen Frauen mitgeben wollen. Damit sich noch mehr Mädchen und Frauen für Mint-Berufe entscheiden. Hört rein und abonniert den Kanal!

Transcripts

Speaker:

there was a time when I worked

2

:

as this translator at this company and I realized

3

:

from different sources that I earn much less

4

:

than my male colleagues

5

:

so I got very angry

6

:

and I went to my manager I mean I prepared for

7

:

seven days probably I don't remember

8

:

but it took me of course a lot of courage to go to him but I told him

9

:

that I

10

:

translate three languages

11

:

whereas I have colleagues who do only two

12

:

and I still earn less than them

13

:

so how is that and I want a raise

14

:

and I remember his super surprised face like

15

:

no understanding in his eyes like not none whatsoever

16

:

he was looking at me and like what

17

:

that's not true you earn even a bit more or or equally

18

:

like Marta Kasia Klara and

19

:

and I was like yeah but I'm not talking about the women

20

:

I'm talking about the men like Tomek Przemek Maciek

21

:

you know I I started naming my male colleagues

22

:

and his surprise was like it was real he was really

23

:

surprised that a woman came into his office

24

:

and dared to compare herself to men

25

:

although I had higher qualifications

26

:

higher more skills more language skills

27

:

but he was so surprised that he gave me this raise

28

:

because for him it was

29

:

I think for the first time he realized oh maybe women

30

:

shouldn't earn less it was like he was thinking

31

:

in two different categories like women workers

32

:

employees

33

:

and men employees and that was like different

34

:

different categories

35

:

so when I jumped in in his head in this

36

:

in this male category it was he was very confused

37

:

but he gave me that raise

38

:

hello dear listeners today my first episode

39

:

internationally so directly recording in English

40

:

I'm very happy to have Dorota with me

41

:

uh Dorota and Paloma at the same time

42

:

so maybe Dorota can explain

43

:

uh why I'm already thinking

44

:

uh about Paloma not only about the water oh

45

:

yeah OK

46

:

first of all happy to be here thank you so much for

47

:

inviting me I'm always in

48

:

with such initiatives that support women

49

:

uh and why why you're thinking

50

:

of Paloma many people think of Paloma

51

:

when they see me or hear of me they even confuse

52

:

the names Paloma is the name of my AI Avatar

53

:

she's my AI twin she looks like me she speaks

54

:

a bit like me although

55

:

she's getting more and more British now but

56

:

I don't know I think she

57

:

she thinks that she's smart she

58

:

she um seems smarter when she

59

:

speaks British so that's the reason probably

60

:

uh anyway yes so she's my she's my AI twin

61

:

yeah for our listeners um

62

:

would you introduce you maybe not only on AI level

63

:

but on on your personal level

64

:

a bit so that we get to know you a bit and then

65

:

sure

66

:

um I'm Dorota Mleczko I am Polish I grew up in Germany

67

:

bilingually and um

68

:

I lived then for a long time I studied in Poland um and

69

:

I was not a woman in tech

70

:

for a very long time because I was a linguist

71

:

I speak many languages

72

:

and I was a translator and then I became a

73

:

linguistic project manager

74

:

and at some point I decided to switch to it

75

:

and that is how

76

:

after some years I became an agile coach

77

:

and I loved that and some at some point

78

:

two years ago I realized that I cannot

79

:

be an adult coach and help improve processes

80

:

while ignoring this whole new technology that is AI

81

:

that um that

82

:

that is the technology to improve processes

83

:

the perfect one so I started

84

:

learning I started exploring

85

:

and then I started teaching

86

:

and that happened over a year ago I started

87

:

being an AI trainer and AI consultant

88

:

and then at some point I had to

89

:

decide whether I want to keep

90

:

being both as a coach and AI trainer

91

:

it was too much so I

92

:

decided to go full into AI AI training AI consulting

93

:

and that is already

94

:

7 8 months that I do only that so full time AI now

95

:

that's very interesting

96

:

so you discovered it or tech or AI quite quite um

97

:

quite late in your career yes um that's true

98

:

how comes did you have I don't know like

99

:

uh inspiration from outside or mentors or something

100

:

um how did you

101

:

decide to get more into it or tech or AI

102

:

yeah I wish I had

103

:

mentors I don't I didn't really I just felt I

104

:

have to do something about my career because

105

:

the translation industry was very rough back then

106

:

I cannot imagine what's happening to it now with AI but

107

:

back then already it was very rough very difficult

108

:

and I wanted to change industry

109

:

and I wanted to change it to tech because I was always

110

:

interested in it

111

:

but it was only that and it

112

:

it took a lot of courage because I didn't really

113

:

it was hard for me to believe oh and I

114

:

I think I didn't tell you that but when I was leaving

115

:

the company the translation company

116

:

I told my boss and he said well what

117

:

where are you going

118

:

what will you do I I said I'm going to it and he said

119

:

he looked at me and he said the last words

120

:

I heard from him were you will never make it in it

121

:

so that's the mentor

122

:

if you're asking for mentors I didn't have them

123

:

that's the

124

:

support that I got so so bad Idol yeah I guess uh

125

:

yeah

126

:

it's good that you made it anyways

127

:

yeah I sometimes remind myself

128

:

granted yeah I would like to call him

129

:

discourage yeah

130

:

say hello from me and from all our listeners

131

:

ha ha I will thank you yeah maybe maybe uh

132

:

even from Paloma that would be cool that

133

:

oh yeah I let Paloma talk

134

:

yeah yeah yeah she's like very make a record make a

135

:

record of it

136

:

I guess it would be oh yeah that's a good great idea

137

:

you're very pity that that you had uh

138

:

such discourage uh by

139

:

by men by managers in in the past

140

:

okay so you

141

:

decided on your own that technology would be very

142

:

interesting and your uh

143

:

first fields of of uh languages

144

:

did you have uh idols there or

145

:

you just said yeah speaking like what

146

:

7 languages now is just why not or how comes

147

:

well like um I think it's it's I developed

148

:

naturally into this language industry

149

:

because of growing up bilingual because of loving

150

:

I think that started it that I loved

151

:

learning languages all my life so I Learned

152

:

I started learning English when I was 10

153

:

although I wanted

154

:

earlier I asked my parents but they said no no in the

155

:

in when you will be 10 there will be English

156

:

in the fifth grade in Germany

157

:

so English and then in the 7th grade French

158

:

and then it's just went from there so I studied

159

:

German later in Poland but also Russian

160

:

for several years and then I also of course Latin

161

:

was always there somewhere

162

:

well not of course but in Germany you learn Latin

163

:

you can learn Latin as the third language

164

:

and then in in in the gymnasium in the gymnasium

165

:

and then in when I

166

:

when I was studying linguistics of German

167

:

philology there was also Latin

168

:

so that's another language

169

:

what more oh and now I live in Italy

170

:

so I need to learn Italian so I'm learning Italian now

171

:

my third fourth year here

172

:

so that's the seventh language that I'm learning

173

:

and so languages

174

:

were there all the time it didn't come from

175

:

well what maybe this um

176

:

yeah I had this um I I had there was a girl that

177

:

spoke so many languages and she was only I think eleven

178

:

because she grew up internationally

179

:

her father was Scottish her mother was Icelandic

180

:

and she lived in Aachen

181

:

or they lived in Belgium but they came because

182

:

you know Aachen is like right at the at the border of

183

:

Netherlands and and Belgium

184

:

so she I think they lived in in Belgium

185

:

but she went to school in Germany

186

:

so she spoke German also and French because of Belgium

187

:

and I think maybe she inspired me

188

:

I thought oh I want to be like her

189

:

but that was so so so much earlier that

190

:

so languages were kind of naturally there and I think I

191

:

I think that was a natural path to follow for me

192

:

and between you always uh use technology or

193

:

was it in the beginning of your career like languages and stuff

194

:

a lot analogue or

195

:

have you always been the the one I don't know

196

:

doing scripts using PCs using a whatever technology or

197

:

was it quite late that you know no we needed

198

:

already being a in a localization company

199

:

we needed to use

200

:

sometimes 10 15 different tools per day

201

:

because we had different customers um and different

202

:

each customer had their own translation tools or they

203

:

had their preferred

204

:

translation tools they had their own systems

205

:

so already in that company I became so um

206

:

acquainted with all kinds of software

207

:

I mean it was usually translation

208

:

software but it was in different systems

209

:

we had to have VPNs

210

:

to log into the customer system sometimes

211

:

sometimes it was something completely else

212

:

sometimes it was Citrix sometimes it was

213

:

I don't know I I was so I

214

:

remember when I joined the service desk and

215

:

someone told me an it service desk later later uh

216

:

and my uh manager told me

217

:

you know you will have to learn a lot of tools

218

:

here sometimes

219

:

three different tools or something like that

220

:

and I I I said yeah that's nothing it's fine

221

:

so it was kind of yeah all all my

222

:

career I needed to adjust to technological changes

223

:

new tools learn tools every day

224

:

so and I loved that part that was actually very

225

:

yeah I liked it

226

:

and uh getting to AI did you have to use it uh

227

:

in your profession or did you just say oh wow there's a

228

:

uh development outside of my

229

:

of my job I want to learn it I want to integrate it or

230

:

was there something in your former company that is

231

:

that have a look on it uh please explore

232

:

please explain it to us or

233

:

no I wish or did you explore

234

:

yeah yeah no that that wasn't I was um

235

:

as I was an Angel coach at

236

:

big corporation German

237

:

Automotive Financial Corporation

238

:

and there was no AI I mean

239

:

not for us there were some projects going on but the

240

:

um let's say that the normal

241

:

worker did not have any a any contact with AI uh

242

:

it was also a very strict very regulated environment

243

:

because of the financial part of this company

244

:

uh so many like there were only some tools allowed

245

:

for the employees I was like an um

246

:

an external employee that was different

247

:

but um at work we were only supposed to use several

248

:

strictly

249

:

um established

250

:

defined tools so there was no AI in the company

251

:

it was me who realized

252

:

that I want to learn that that is important

253

:

and I had to do it in my personal life so first I did it like only for personal

254

:

stuff and then I started

255

:

building for example I build an assistant

256

:

for adult coaching so I did not use internal company

257

:

data but I could still get help for preparing

258

:

for my work or doing preparing workshops or uh

259

:

getting for example um advice on difficult situations

260

:

as an agile coach or on process improvements

261

:

so I started building my my assistance already then

262

:

and I I also well started

263

:

kind of introducing it and at some point I Learned that chat

264

:

GPT is allowed

265

:

if you if you use it there is no company um license

266

:

but if you want to use it it's allowed just no

267

:

internal data so I built a

268

:

a retrospective Rita Retro she was called

269

:

an assistant a custom GPT that runs retrospect

270

:

retro I like it

271

:

do you have a public I would

272

:

I would love to yes I can I can I have to

273

:

check her she's old so I have I have to update her

274

:

with the newest models I guess you do so we could

275

:

put that in the show notes I guess

276

:

okay I could use it for my project also that's yes

277

:

Rita Retro she's she's built to run retro you know

278

:

naming is

279

:

is very important Rita Retro is is nice it's very nice

280

:

okay good right I'm glad you like it you should

281

:

may I don't know

282

:

whether it's still possible to have like GPT's

283

:

to monetize I guess it's over or all of free or

284

:

are there assistants GPT's that that you can monetize

285

:

I don't know I think they are

286

:

they are free in the store but yeah

287

:

I mean you can find a way at least at least

288

:

as lead magnets you can use them so

289

:

you should you should

290

:

I I'm trying I have I have Peter prompt

291

:

he writes prompts

292

:

for you so if you

293

:

don't so that you don't have to and I have Anna Architect

294

:

she built helps you write instructions

295

:

for custom GPT's

296

:

and other AI assistants like Claude Projects

297

:

Gemini Gems so I have a few of them

298

:

that that are public

299

:

I can give you the links later

300

:

yeah that's very cool I guess

301

:

nice very nice

302

:

and um

303

:

looking back what would you change in your career

304

:

you already mentioned to be

305

:

earlier in in tech um but do you have like concrete

306

:

dedicated stuff that you would point out or

307

:

would have done otherwise

308

:

yeah so definitely

309

:

like I said I think I said it before the recording

310

:

that I I would have changed I would have switched to

311

:

it much earlier

312

:

because I just didn't think that I could

313

:

I didn't believe in myself enough to do that

314

:

it took 10 years to start believing that and

315

:

I would have done that earlier and yeah

316

:

if I could like talk to myself back then now

317

:

I would say just just have the courage to explore even

318

:

to to also to

319

:

to follow what what you feel you you like doing

320

:

I I felt already that I like the tech

321

:

stuff my parents always said it that I'm like this

322

:

actually my father always told me I should

323

:

study tech stuff and I didn't even

324

:

know what what he meant like why I'm a linguist what

325

:

I was born he knew you very well right you know he knew

326

:

he knew me yeah he's not he's not alive anymore

327

:

but he was the one who told me and back then it was such a

328

:

such an abstract thing to say to me

329

:

but I always liked it I always liked like the um

330

:

informatic in in school and

331

:

it was it was always something that I liked so

332

:

maybe I would have

333

:

become a developer because I don't write code I

334

:

I only vibe code

335

:

I still don't know how to write code I would love to

336

:

but well it never happened for me

337

:

so I'm a non technical woman in tech but maybe

338

:

if I started earlier I would have Learned also more

339

:

yeah deeper technical stuff like writing code

340

:

software development

341

:

who knows so I would have I would have

342

:

wanted to have more courage and

343

:

believe in myself and much less imposter syndrome

344

:

yeah

345

:

it's a big issue for all

346

:

uh all guests so far here in the podcast I guess it's

347

:

it's really an issue with with a lot of women

348

:

despite their so experience they have so so many

349

:

languages if you want to share um

350

:

the little story that you mentioned in our

351

:

talk before so with your with your manager and um

352

:

the language that you spoke and the man

353

:

spoke I guess that would be very interesting

354

:

because you took a lot of courage then

355

:

ah yes so

356

:

there was a time when I worked

357

:

as this translator this company and I realized

358

:

from different sources that I earn much less

359

:

than my male colleagues

360

:

so I got very angry

361

:

and I went to my manager I mean I prepared for

362

:

seven days probably I don't remember

363

:

but it took me of course a lot of courage

364

:

to go to him but I told him that I

365

:

translate three languages

366

:

whereas I have colleagues who do only two

367

:

and I still earn less than them

368

:

so how is that and I want a raise

369

:

and I remember his super surprised face like

370

:

no understanding in his eyes like not none none so ever

371

:

he was looking at me and like what

372

:

that's not true you earn even a bit more or or

373

:

equally like Marta Kasha Clara and

374

:

and I was like yeah but I'm not talking about the women

375

:

I'm talking about the men like Tomek Przemek Matek

376

:

you know I I started naming my male colleagues

377

:

and his surprise was like it was real he was really

378

:

surprised that a woman

379

:

came into his office and dared to compare herself

380

:

to men although I had higher qualifications

381

:

higher more skills more language skills

382

:

but he was so surprised that he gave me this raise

383

:

because for him it was

384

:

I think for the first time he realized oh maybe women

385

:

shouldn't earn less it was like he was thinking

386

:

in two different categories like women workers

387

:

employees

388

:

and men employees and that was like different

389

:

different categories

390

:

so when I jumped in his head in this

391

:

in this male category it was he was very confused

392

:

but he gave me that raise

393

:

so but that's the same boss that later

394

:

told me you will never make it in it so

395

:

yeah congrats to your

396

:

to your courage and congrats that you made it and uh

397

:

for all for all the listeners yeah be brave negotiate

398

:

because if you don't ask you

399

:

most probably will not get

400

:

raise at all or not as high as you would wish to

401

:

speak up or or what additional advice would you give

402

:

for that

403

:

from that experience

404

:

yeah that's a good good question um

405

:

so in in general I I tell women now

406

:

that it's our time now

407

:

we have to like give up all these

408

:

I mean it's it's not easy I know

409

:

believe me I know giving up imposter syndrome

410

:

giving up doubting yourself and

411

:

listening to these bosses

412

:

that tell you you will never make it and in general

413

:

give it all up because that is now is the the moment

414

:

where we can really lead something we can get

415

:

we can jump on this technological revolution

416

:

that is happening

417

:

we can be part of it and we can even lead it

418

:

we have the possibilities now because the last

419

:

revolution this big that happened that was like 20

420

:

or even 30 years

421

:

ago the internet revolution I would compare it because

422

:

the internet also changed our lives

423

:

changed not only the way we work but

424

:

that changed everything for us our lives now

425

:

this is something similar maybe even more scary more

426

:

like yeah more maybe even more impactful

427

:

and back then we couldn't be part of it us women

428

:

we were like maybe 13% I think of um

429

:

leadership roles in tech companies were held by women

430

:

now I'm not saying it's much better because I think it's 25

431

:

but it's still it's progress

432

:

and we can now if we have if we find the courage

433

:

I think currently the problem is mostly

434

:

not even men not wanting us to have a career

435

:

but more us not believing in ourselves

436

:

so I'm telling women all over now that

437

:

this is the time because we're good in AI

438

:

even if you're not

439

:

a programmer a very technological person

440

:

AI is a lot about communication

441

:

about emotional intelligence

442

:

because models need to be trained for example

443

:

to be emotionally intelligent otherwise

444

:

humans will not be able to chat with them

445

:

and this is where women shine

446

:

I mean we're naturally born with these skills

447

:

often times of course I'm generalizing a bit but

448

:

we are now very important and we also are very good at

449

:

leading transformation helping people through change

450

:

with human centered approaches right that's

451

:

that's where we shine so and now the world needs it

452

:

so I tell women now always like come learn

453

:

first learn AI learn what it is learn how it works

454

:

and then combine it with your expertise

455

:

that you already have whatever you're doing

456

:

if you're a project manager

457

:

combine it with AI and you will be a super expert

458

:

if you are a

459

:

I I don't know human human resources

460

:

expert you can also combine that with AI and then it

461

:

it's amazing so whoever

462

:

whatever your expertise or even your passions

463

:

your hobbies are if you combine that with AI

464

:

then something great can come out of it

465

:

and yeah so I encourage women now to

466

:

jump on this and help lead

467

:

even you know not only take part be part of it now

468

:

not like then we weren't even part of it I would say

469

:

now we can be part of it but we can also lead

470

:

this transformation

471

:

because humanity is undergoing a transformation now

472

:

it's not only businesses anymore

473

:

but it's whole humanity because AI is everywhere

474

:

our children use it

475

:

yeah so I get emotional

476

:

that's good

477

:

that's good it's a good call for for the women and

478

:

yeah I still think about your career pass

479

:

so a lot of people say that

480

:

especially LLMs yeah they're a lot of linguistically

481

:

do you know do you think that was your experience

482

:

in languages that helped at the beginning

483

:

or is it just coincidence you were

484

:

just interested in technology and

485

:

just evolved or do you think was your

486

:

ability to learn to communicate

487

:

it was always an advantage

488

:

for you to use LMS and other AI

489

:

that's a I never thought of that

490

:

what's maybe yes

491

:

maybe it made it easier for me to learn prompting

492

:

cause prompting is about well

493

:

it took me some time to realize

494

:

that prompting is not a technical skill but

495

:

a linguistic skill

496

:

yeah communicate communication skill

497

:

and once I realized that

498

:

I became very good at it so yeah maybe

499

:

maybe you're right maybe these 10 years

500

:

of in the translation industry we're we're rusty

501

:

yeah I guess yeah no it's yeah maybe yes

502

:

yeah advantage yeah cool nice

503

:

and um yeah now

504

:

yeah of course now you combine everything

505

:

you combine your

506

:

language skills your drag skills and now

507

:

yes it all kind of comes together

508

:

that's true very cool

509

:

and um

510

:

also with with international with language skills

511

:

did it help you later in the it field uh I'm working uh

512

:

like hybrid

513

:

so we have an international team at the moment

514

:

I guess more and more tech companies

515

:

do did it help you there also or do you think

516

:

English would have

517

:

being just enough or

518

:

to have so many languages did it help you

519

:

yes definitely it helped not only the languages

520

:

because for example when I were

521

:

when I have a call one on one with a German manager

522

:

or a German product owner we always spoke German

523

:

it was natural for example

524

:

so that already felt for them maybe also

525

:

better more comfortable that they are

526

:

they were speaking their own language

527

:

so maybe they trusted

528

:

me more or you know it was easier to to get this bond

529

:

that you need in order to

530

:

support them as an agile coach um but also I think the

531

:

understanding of different cultures so my international

532

:

um upbringing let's say in Germany where yeah I

533

:

I I I was

534

:

in a classroom with many different people from all over the world

535

:

that all grew up in Germany like me

536

:

so that was already something that I felt was natural

537

:

and later in life I was always seeking

538

:

that also in in companies so I would not like I

539

:

I worked for some time in a very Polish company

540

:

um but in in a bank it was very nice but I missed this

541

:

internationality so whenever there was an

542

:

international project I just

543

:

jumped on it and of course I got it because of the

544

:

many languages

545

:

so yes I definitely helped helped in the career German

546

:

companies hired me because of the German language

547

:

and although it was not the project

548

:

language but still they wanted at least for example

549

:

agile coaches or scrum masters they wanted

550

:

them still to speak German to be able to communicate

551

:

with all the departments where

552

:

maybe English was not that popular yet or spoken yet

553

:

and um but also the cultural

554

:

understanding knowing how to

555

:

let's say navigate it's a very AI word but navigate

556

:

a very international environment

557

:

well that that helped a lot in it

558

:

so you lived and worked in Germany Poland now Italy

559

:

are there more

560

:

countries not yet

561

:

no no these three come countries yes

562

:

and Italy I've heard you uh

563

:

you live in Geneva

564

:

now never been there but I heard about nice mountains

565

:

and and sea seems to very very nice so did you

566

:

uh choose it for work or how comes or just it's so nice

567

:

here I want to be there in the middle of Europe I want

568

:

mountains and sea and all

569

:

how comes that you have chosen the letter

570

:

yes we just chose it because I work remotely

571

:

and my boyfriend works let's say everywhere

572

:

he can work remotely

573

:

sometimes sometimes he has to be in Poland

574

:

or sometimes in Iceland for example but it wasn't that

575

:

that important where exactly we live for the jobs

576

:

so we could choose

577

:

um and when I saw

578

:

Genova and I saw the sea and hear the mountains

579

:

um it reminded me a bit not the mountains

580

:

but it reminded me a bit of Gdansk where I

581

:

lived most of my life in Poland and

582

:

just just warm and with palm trees

583

:

because Dinesh is beautiful

584

:

but it's very cold and now they have like minus 15

585

:

degrees so I'm happy because we have 15

586

:

but plus and sun

587

:

um yeah so I wanted a sunny place

588

:

I wanted a change after the pandemic I was

589

:

kind of depressed of all the greyness and everything

590

:

I think many people did changes after the pandemic

591

:

and I was one of them I just wanted to live somewhere and we loved

592

:

Italy for travelling of course so

593

:

we decided to check it out started learning Italian

594

:

and then this place was just chosen

595

:

by me I immediately

596

:

like after 1 2 days I said OK that's it

597

:

let's start here at least and we might stay here yeah

598

:

and even there did a

599

:

technology job help right AI job technology job

600

:

helps to choose a dream a dream location

601

:

seems very nice I envy you about the the sun at least

602

:

yeah but you know that was

603

:

that was three and a/2 years ago so um

604

:

chat GPT wasn't even live yet it came a month later

605

:

and it took me some time to realize

606

:

how helpful it could be

607

:

I I wish I had it to help with the documents

608

:

here with translation with renting an apartment

609

:

translating and understanding the whole

610

:

uh

611

:

the whole documents everything

612

:

that I had the contracts and

613

:

uh helping me acquire my residency I now

614

:

help people do that with AI

615

:

if they are experts somewhere and I I have a

616

:

I have now a

617

:

a great process for that a great AI workflow and

618

:

I wish I had it because it took everything

619

:

took so much time because I didn't

620

:

speak the language well I didn't understand

621

:

this this processes

622

:

I never had to apply for residency anywhere so this was

623

:

I wish I had it back then now it helps a lot whatever

624

:

email comes like Gemini translates it for me

625

:

and I immediately know what to write back and it's

626

:

yeah it's a dream for expats AI

627

:

that's cool

628

:

maybe that would be a good sidekick for you also right

629

:

you're right AI for expats

630

:

amazing I you gave me so many ideas today hahaha

631

:

uh

632

:

you're welcome yeah cool nice and now um you see

633

:

yourself as an woman in AI or woman in tech

634

:

I do

635

:

and how does it feel how

636

:

how do you feel fulfill that role

637

:

from your personal point of view hmm

638

:

um I think being a woman in tech today

639

:

is something completely else than it was

640

:

30 20 even 10 years ago I guess because

641

:

back then women in order to even

642

:

get a role or get a career in tech they had to

643

:

be like men they had to adjust

644

:

more so be more aggressive be more

645

:

like I'm generalizing again but

646

:

you know what I mean we had to

647

:

imitate I even heard a woman lately

648

:

on a woman in tech meeting

649

:

um she said she's a developer and she said that

650

:

at one point she joined a company

651

:

started going to an office as a programmer

652

:

and her boss told her at one point that

653

:

she should maybe change her the way she close

654

:

clothes this bit because she liked colorful dresses

655

:

he said

656

:

you know it's not very important but maybe you could

657

:

like look more blend in like look like the developers

658

:

which were and it wasn't like a

659

:

customer facing role or anything

660

:

it wasn't about looking more elegant nothing like that

661

:

it was about could you please blend

662

:

in a bit more like wear hoodies

663

:

or whatever they were wearing because they were

664

:

they were developers

665

:

so she was and she realized

666

:

after some years that she really started

667

:

doing that she stopped wearing dresses and rocks

668

:

uh skirts she just

669

:

started to blend in and she felt sad about it

670

:

and that is how I think it shouldn't be now anymore

671

:

and I will tell you why I will tell you a story

672

:

if we have time

673

:

of course that's why we are here OK good

674

:

so the story about AI like how I started learning AI I

675

:

like I said I decided two and a/2 years

676

:

ago I said okay now I need to really dive

677

:

in I need to learn it

678

:

and I started looking for courses

679

:

joining free webinars

680

:

looking for courses I was ready to pay

681

:

but I wanted to find a good course and everything

682

:

that was out there back then that was men

683

:

that was men teaching mostly

684

:

um software developers so it was very technical

685

:

it was very boring and very impractical

686

:

so some of the courses were completely abstract

687

:

like you could use

688

:

AI here you could use AI there but nobody was showing

689

:

I use AI like this look and you can do it

690

:

like that like that like that

691

:

so they were not practical

692

:

they were theoretical they were

693

:

boring and very technical

694

:

and I thought

695

:

OK I need to learn it myself

696

:

and I started learning myself and then the first

697

:

really good courses that were fun

698

:

really practical felt natural to watch them and

699

:

helped me really learn something

700

:

uh were from women so a few women

701

:

in AI that I then started following I currently follow

702

:

mostly women in AI and I learn from them

703

:

and that's how I also started realizing OK I will

704

:

do something like that myself I will create a course

705

:

that will cover all of that that I

706

:

wanted back then so the whole fundamentals of AI

707

:

and then of course advanced also master classes

708

:

but I will start with an

709

:

AI fundamentals course for non technical people

710

:

that is practical and fun

711

:

and I did that and that's how I I felt I'm I'm I'm um

712

:

closing a gap

713

:

and that is why I also think that more women

714

:

should be in AI because yes being a woman in AI

715

:

or in tech now means being yourself

716

:

you don't have to imitate anyone anymore

717

:

you don't have to adapt you don't have to blend in

718

:

now you have to stand out so if you are yourself

719

:

if you're being yourself

720

:

you it's it's better you bring your

721

:

personality your value and the female like

722

:

strength that we have

723

:

you can now all bring that you can wear your colorful dresses

724

:

the women in AI that I follow are so natural

725

:

they are completely themselves they don't care about

726

:

I mean that's how it seems and

727

:

when I speak to them it seems also that they say OK

728

:

I don't care I know I'm messy for example or

729

:

I know I'm I'm completely

730

:

non techy but I do teach this AI

731

:

because I know how to do it practically

732

:

so why why wouldn't I teach it

733

:

or they are completely like

734

:

so natural in their webinars they just relax and they

735

:

speak what they think and they ask you

736

:

10 times how can I help that's also a very

737

:

female thing right how can I support

738

:

is it fine for you what I'm saying is it clear

739

:

can I show you so what could what could I show you

740

:

and yeah I think I feel from my experience learning AI

741

:

it's really much easier to learn it as a non

742

:

technical person

743

:

maybe also as a woman

744

:

it's much easier to learn it from women

745

:

but I don't have only a female clients

746

:

men also join my academy so it's

747

:

it's not my target I would say but it's something that

748

:

well I felt I I fill the gap hopefully

749

:

I can imagine yeah like I said um

750

:

women are very good in learning

751

:

so at school I guess even their studies in school

752

:

mostly girls are better than than the boys

753

:

maybe because most boys only

754

:

uh

755

:

have um their interests in schools later

756

:

often very often not not each and every

757

:

boy but mostly later

758

:

and as you said you had 3 languages

759

:

your colleagues only your

760

:

male colleagues only 2 learning non stop

761

:

yeah yeah

762

:

that yeah is your advantage now so often uh

763

:

women are better in AI because they approach

764

:

technology first

765

:

that's cool thank you yes maybe you're right

766

:

and that you lower the barrier for for women

767

:

from woman to woman that's very nice yeah

768

:

that is a good point I think women always

769

:

that's also of course but yeah we are often

770

:

better in school we often well I think we also

771

:

needed to learn more because we also

772

:

we always needed to know more in order to

773

:

you know keep up

774

:

with men in in the careers in school also

775

:

we needed always to prove ourselves

776

:

and I don't know even to be part of conversations

777

:

that men held

778

:

we had to be knowledgeable because we always

779

:

felt at least we had to prove ourselves

780

:

much more than men so I think that is also a reason

781

:

why women are always learning

782

:

and yeah you cannot

783

:

be an AI without learning you have to learn

784

:

you know constantly in order to

785

:

you don't need to keep up with everything of course but

786

:

yeah you have to have an overview

787

:

of the technology how it's changing and that takes yeah

788

:

a lot of my time now just to keep up how do you

789

:

do it there are so many sources at the moment

790

:

so many new models and versions

791

:

and crazy every every week sometimes every day

792

:

yes I had to streamline

793

:

it a lot so I I have a lot I get a lot of newsletters

794

:

but in the end so first I build a an automation

795

:

that summarizes them and gives me an update but that

796

:

wasn't the same because I I'd rather see who's writing

797

:

it you know where where did it come from

798

:

I ended up having only one or two from women

799

:

and they update they they send out newsletters

800

:

with updates as women I trust I know they are amazing

801

:

I know they're rocking it so when they send an update

802

:

I know it will be relevant

803

:

it will be practical it will not be some

804

:

super hype about I don't know very uh I

805

:

what is it generally agenic

806

:

something something that we're waiting for

807

:

I'm not interested in

808

:

in that very abstract um things I'm interested

809

:

in the very practical

810

:

side and my my clients and my students as well

811

:

so I need to know practically what is

812

:

important what changed like what what do I need to

813

:

try out now or why does cloth look different

814

:

now what is co work I don't know these things

815

:

I don't need to know like any and and the politics

816

:

I don't need them many I listen

817

:

to many AI podcasts in the beginning I like them

818

:

but they tended to

819

:

talk a lot of politics uh like business politics

820

:

let's say about

821

:

Elon Musk and Sam Altman and what didn't

822

:

then he said and then he said and then he said

823

:

and it's always he said it's never she said

824

:

I don't need to know what they said

825

:

so I stopped I stopped listening to these podcasts yeah

826

:

I can imagine do you regularly um attend podcasts or

827

:

no no I like it I'm

828

:

that's why I'm very happy that you invited me

829

:

I was in one last year I think in one only

830

:

that was about vibe coding and I was invited as a

831

:

vibe coding expert that also helped me get rid of my

832

:

imposter syndrome because this guy contacted me

833

:

and he said

834

:

he wrote me you know I want to have an expert on vibe

835

:

coding in my podcast could you please come

836

:

and I answered but I'm not an expert in vibe

837

:

coding I do it but I I don't see myself

838

:

as a real expert and he answered

839

:

I don't think there are any real experts

840

:

and I looked at it and I thought I think you're right

841

:

I mean that's so it's so fresh it's so new yeah

842

:

that who can be who can be

843

:

a 10 an expert with 10 or 20

844

:

years of experience in vibe coding nobody

845

:

everyone's just starting to do it so is that okay

846

:

of course I did research and um

847

:

I I had already built several things but I researched

848

:

other tools that I don't use usually

849

:

I came prepared and it went great

850

:

but yeah I'm not not often

851

:

invited to podcast so I'm I feel very

852

:

very honored to be here

853

:

thank you I will forward you to in a ipodcast so

854

:

oh great yes speak more yeah

855

:

I can speak about AI for hours

856

:

no problem that's good that's good yeah I guess

857

:

they will invite you more than once I guess it's fine

858

:

amazing thanks ha ha ha yeah we are um

859

:

little by little coming to an end um

860

:

so by tradition so the last one or 2 minutes

861

:

are for the guest we have um

862

:

still some advices for girls for women

863

:

who are interested in

864

:

technology maybe like for you to be uh

865

:

not coming directly

866

:

from tech but maybe coming from another profession

867

:

mm hmm

868

:

yes so I said it a bit already but I

869

:

maybe I will sum it up a bit um

870

:

if you are in any way thinking of

871

:

becoming a woman in tech or if you're interested

872

:

in AI or interested in technology

873

:

uh just do it

874

:

don't let anyone tell you don't let your boss

875

:

tell you anything or anyone else

876

:

don't let your imposter syndrome come in the way

877

:

uh just do it just pursue it do it now

878

:

and even if you're not thinking of becoming

879

:

a technical person you don't need to anymore so AI's

880

:

like closing the bridge the gap between

881

:

non technical and technical people a lot

882

:

we can now easier understand each other we can easier

883

:

work together and

884

:

people who are not really technical can now become a an

885

:

important

886

:

person in tech like I said and a transformation

887

:

leader for example or a change manager um an adult

888

:

AI transformation coach

889

:

all these things they are just emerging

890

:

these roles and they are very important and women

891

:

are amazing at these things so I think yeah just

892

:

be very open now

893

:

to what might and don't wait

894

:

maybe this is important because people sometimes

895

:

wait what will happen to them and

896

:

for example you're you're

897

:

you're afraid that you might lose your job or

898

:

you're already looking for a job and you're waiting

899

:

for someone to hire you I would say stop waiting

900

:

to the women especially

901

:

stop waiting start your own thing start something

902

:

you can do so much now in AI without

903

:

even technical knowledge so it's now the moment

904

:

it really the moment is the best one to start a career

905

:

even

906

:

to or to jump on a career that you always dreamed of

907

:

just start by covering the fundamentals of AI

908

:

and then you can do you can do anything now

909

:

yeah I think that's that

910

:

thank you daughter

911

:

thank you so much David for having me

Follow

Links

Chapters

Video

More from YouTube