Automating Podcast Production with AI: Lessons Learned and Real-World Challenges

What does it really take to automate your podcast production with AI? In this episode:
• Paul shares his real-world experiences automating every step—from audio editing to content and artwork creation
• Key workflow tricks, hard-earned lessons, and unexpected hurdles
• API integrations, tools like ChatGPT, and the balance between automation and manual approval
• What the journey says about the future of creative work with AI
Curious about leveling up your own podcast process or staying ahead of the automation curve? Tune in and learn how to harness AI for more efficient, less painful podcasting.

Show Notes

In this episode of Talking to AI, Paul shares a candid, behind-the-scenes account of his journey automating podcast production from start to (almost) finish using artificial intelligence. Drawing on several months of hands-on experimentation and coding, he breaks down both the successes and challenges in building a semi- and then fully-automated workflow. From handling audio quality and multitrack recording issues, to harnessing AI tools for content creation and managing the intricacies of APIs, Paul offers practical insights for podcasters and developers exploring similar paths.

Through trial and error, Paul discovered the limitations of off-the-shelf tools, why multitrack audio is crucial, and how ChatGPT (along with other LLMs) played a pivotal role in generating titles, summaries, tags, and artwork. He also reveals why some manual oversight—especially approving podcast titles—remains essential, and maps out the evolving stack he's adopted: from custom Python scripts to APIs for ChatGPT, WordPress, and hosting providers.

Looking ahead, Paul reflects on what these automation lessons reveal about the broader future of work with AI. He predicts a growing demand for high-level technical skills in orchestrating automation, and urges listeners (especially other creators and tech enthusiasts) to embrace disciplined experimentation as they shape their own AI-driven workflows.

🎙️ Hosted by Paul at Talking to AI — where real people, real problems, and real conversations meet artificial intelligence.

What is Talking to AI?

Audio conversation with AI chatbots

I am talking to AI.

A successful day, you don't need to know all the answers.

Just have good questions.

Chatting to AI is different from normal speech

and I hope you enjoy listening to the show

whilst getting ideas on how to hone your questions

to get the most out of AI.

My name is Paul.

The live conversations you hear are uncut

although sometimes the AI needs time to think.

In those cases, I've cut out the dead space.

What I want to do is give an overview

of what I've learnt, I guess,

over the last couple of months

around coding with AI

and maybe there's some hints and tips

if somebody's reasonably new

to coding with AI.

I will try to provide a bit of a dump

as to what I've been doing

and what some of the things I may have achieved

and some of the things that I've sort of found out

I guess through this endeavour.

Since I've been doing the podcast

I've been also obviously publishing the podcast

and earlier on I explained this process

that I was going through

to semi-automate the production of the podcast.

So there's actually a bit to creating a podcast.

You obviously have to do the audio which I'm doing now

and you have to sort of figure out

how to get all that to sound nice and work.

One of the big challenges I had was getting

recording many participants at once

including a couple of bots

and that caused severe, severe headache

and although it was a pretty interesting activity

in how to get advice from AI

and when you should be seeking AI for help I guess

and when you should be using your own brain.

Although it was helpful

I would say that in that particular issue

I probably solved the problem myself

rather than AI

and AI actually let me down a few paths

which were incorrect

and I learned a bit from that

but I've already explained that.

So what I want to focus on today

is the next level with producing the podcast

and that is to fully automate the system.

Now I'm still working on that

it's almost done

and I just sort of run through

some of the things that I guess I came across

and some of the challenges and sort of

so okay, without waffling

what am I doing?

So I'll tell you what I'm trying to do

with the process

and then I'll explain what I have done.

So what am I trying to do?

So you record the show

then what you have to do

is you then have to

create a bunch of content around the show

so you have to come up with a title

you have to come up with some summary information

about the show

and then

to host it on iTunes or whatever

you have to tag it appropriately

you have to create images

for the podcast

and a few other bits and bobs

and I've chosen to publish this

on a hosting company

and that was Lipsin

and so that company

what they do is they host the MP3 files

they have a sort of scalability

within their hosting

so that if you get a lot of people

downloading it

they manage all of those

potential issues

because MP3 files can be quite large

and it can cause issues

if you were just hosting it yourself

you can have issues with the

hosting provider not liking you

having that amount of downloads

and just slowing down

so for that reason

most people that have podcasts

they use a hosting provider

and I've also set up a website as well

because I think it's quite good to have a website

you never know

you can't really rely on platforms all the time

at least if you've got the website

you've got a website

you've always got someone where you can point people towards

so I've got a website and I have that updated

and that's using WordPress

so I've got a WordPress website

and I've started off with Lipsin

host

so what you do is

you create the MP3

and then you create the content

then you go into Lipsin

and you update all the stuff

in Lipsin

and then you go into WordPress

and you update WordPress

with all the new stuff

so there's two

there's a few parts to this but basically

once you've created the MP3 file

then once you've created the content

then that content needs to be

put into two platforms

right

so in my semi-automated

process

I'd created a prompt

in chat GPT and that prompt

would take the

well no actually

before I get to the prompt my full process

the semi-automated process was to

once I had completed

well actually

a few bits to this right

so the first problem that I had

with recording this was

because

at the beginning

at the beginning when I first did these podcasts

I was recording using some software

on my laptop

and basically

all the audio was getting recorded

into one file

and then I'd basically take

that file

and do a bit of

editing and that's my MP3

file created which is the show

I soon

found out that that wasn't a very good way

of doing it because

by doing it you end up with

normally you end up with differences in volume

between the two speakers or the three

speakers and the three people participating

in the podcast and you might

want to treat the audio differently

so the podcast that I'm being

recorded in are all recorded

through my iPhone headphones

and I like that because that means I don't have

to have a proper studio

I can just move around and I can record them

the issue with that is that

the recording quality is not as good as

is from a normal

like proper microphone you'd have

a normal audio recording

you'd have a high quality microphone

you'd have a pop guard

and that would do

some enhancing to that would prevent some problems

that you get I'm not getting into detail

and you'd also have probably

a podcasting studio that you're in

and it would be properly sound

isolated

and all that good stuff

I'm not doing any of that

I am in a room with a door

but so

when I'm talking on my microphones

a whole bunch of quality issues

that would be there

but they're not there now because

what I like to do is I like to effect

the audio

of my voice

to remove the problems

and enhance the sound

and I do that with audacity and I've got a whole macro

that does a bunch of stuff

to that and if anyone's interested

the way I came up with that macro

was I asked chat GPT to tell me

what effects I need to apply to an audio

with my iPhone

headphones to get a good sound

and I basically used that

and then made a few little tweaks

so but

what that means is if I was to apply

those effects to an audio file

with two speakers on it

me and chat GPT say

it's going to do all of those effects

to both and

that might sound great for me

but it won't sound good for chat GPT

because chat GPT's already been optimized in a bunch of ways

and then you probably end up making it sound too basic

and it just doesn't do

your good job the way any professional

sound engineer

would tell you is what

they need to do is you need to separate off

all of the different sounds

and then treat them separately

so that meant that I had to basically

multitrack record the podcasts

something that most people do

right however

the software I was using

the only way I could do that was

create a certain file type

that's an NKV type

it's also a video

type but that allows me to do

multitrack recording great

the problem was

my process

is to use audacity

to basically

what I do with that is I

I mean it's very minimal

but basically I've got an intro and an outro

I slap them on the beginning of the end

and then I normally have some nasty bits at the beginning

where I muck it all up

so I have to delete some of that

and then I sort of slap it together

sometimes I might have to do another recording

so I might record twice and slap two things together

so there's a little bit of sequencing required

and then to get to the point where

it's sequenced up

it runs alright and then I

export it as an mp3 file

however the issue with that

is I can't load in an mkv file into

audacity it doesn't accept them

there might be some way

there's normally some way it's supposed to work

but I could never get it to work

I tried to get it to work so I gave up on that

so instead I have a python script

which strips the mpv file

the mkv file

and turns it into just WAV file

so that's the standard

Windows audio file

for each

participant

so it creates four WAV files

for every mkv file

so that allows me to have four participants on the call

so that's the first thing that I had to automate

in a semi-automated manner

and I had a little chat

with the chat gpt and I got this nice

well originally yes

originally I was doing this

with

I tried it with chat gpt

didn't really work I tried it with another

service and it

did work but

the issue you've got is that you're going to have to start

paying for that

because that's actually quite a intensive

operation transcribing

mp3

no sorry I'm getting confused sorry I'm not talking about that

I'm talking about splitting the files

sorry

yeah no sorry forget

the last 30 seconds

basically so I've got the mp

mkv files

and I've got a chat gpt to get a python script

to

split those

so I've got that running on my

Mac

and the python script now

I just give it the URL

for where it is on my computer

the path file

not the URL

and then it consumes that

and voila

it spits out the WAV files

and then I take those WAV files and then I use those

to sequence it up

in my audacity which then creates

the mp3 file

and then the mp3 file

is

what I then use

for all of the content generation

moving

after this so this is quite clever

but

it's not me really

it's not me being clever

it's chat gpt being clever

or grok I tried both

but I ended up with chat gpt at the end

so basically what I then did in my

semi automated process

is I then

created a prompt

took me quite a long time to create this prompt

quite a lot of toing and froing with chat gpt

to get this to work

and it's a multi step prompt

so

you

I sort of

sometimes it's wise to have this notion

of steps

and you explicitly say step 1 do this

step 2 do this, step 3 do this

and this was required

because

I basically wanted so the process that I wanted

it to do was to take

my transcription

that I've done

on my Mac

and then load that

into chat gpt

so you insert it as a file

you can do that

and then the prompt says

look at that transcription

and what I want you to do is I want you to create

a title for my podcast and that has to be

SEO optimised

and it has to be intriguing

and a few other things around the prompt

there to make the content interesting

and then I want you to create a summary

of the post like a few paragraphs

explaining what this

particular show is about

and then

I want you to create

oh yes and I want you to create two

different versions of that summary one is

for Libsyn so that goes into iTunes

and they don't have as much space as they have

on Wordpress

and Wordpress needs to be more

SEO optimised as well

than the

iTunes

text but I also want

there's also stuff about the feel

and I think I quite like the

text that's come out

and then

I also get it to create a list

of tags for both Libsyn and

Wordpress

and create

two different images

one is a square image which is used for

iTunes the other is a rectangular image

which is used for

some of these

I think iTunes and Spotify I think they do use

the rectangular image in some

circumstances depending on your screen

that you're listening to the music on

and it's also used on Wordpress

so Wordpress is a rectangular image

the way I've set it up

so they are the things

that it creates

and in the semi-automatic

process it had to be

a step-by-step process because

you can't just ask

chatGBT to do all that in one go

and the reason for that is

that images

when chatGBT creates images

for you the way it works

is chatGBT

talks to Dali

before it talks to Dali chatGBT

generates a prompt for Dali

and then it

asks Dali via the prompt

to create your

image for you

now Dali has got certain rules that it runs

by and one of those rules is

it won't release any images

it won't release more

than one image at a time

and after every image that it releases

if it's being communicated

to via the chatGBT

chat window

it will ask for your approval

you can't get around that

and the issue one of the big

things that was causing me a lot of

grief was that chatGBT

was not aware of this limitation

really with

Dali

so it thinks oh this is a great

prompt yeah great

I'll go ahead and do that absolutely

and then it goes ahead and tries to do it

and you end up with this kind of half hang

it just crashes

and chatGBT thinks it's doing a great

job but it's not it's doing a rubbish job

like my prompt has gone

halfway through and just hung

so I had to create these steps

and these steps have to explicitly

explain that

Dali will then ask for an approval

and then you have to put in the text

do you approve this

so I had to actually type

in my prompt the prompt

that it was going to give me to approve

the file and then I had to

do it again for the second one

and then it would then create all the other images

so that was

one reason why I had to structure it with these

with these steps

but the other thing I wanted to do

was basically

in an ideal word I just wanted to

output a zip file with a bunch of files

in it

and that turned out to be

truly a pain in the butt

and although

you can get chatGBT

to do this you can get chatGBT

to give you a file with a file name

I've done it it's happened to me

but

most of the time it doesn't work

like if you want it

and a lot of the time I don't know if you've ever had this

where it gives you a link and the link

doesn't resolve

because of some kind of internal conflict

there's something going wrong there

but it doesn't know that it's going wrong

and this is when chatGBT can be super frustrating

but the thing that I

realised with the files

was that really the chat window

isn't really set up for sending you

files

but you can do it

but it's not

reliable

so that's what caused me to start

thinking along the lines

of the next evolution of this process

so I did get this process to work

so this process was working

it wouldn't

download the files

but it would

create

the files in text so I ended up

at the end of it I ended up with a few

with

all of the tags

the titles were all in the chat window

and I ended up with a couple of images

in the chat window as well

pretty well actually and the images came

out pretty much like I wanted them

to come out

but I wanted to

get this to the next level

I basically wanted to get it to the point where I could

just sort of fire and forget

my dream with this

is to do a podcast, record the audio

then I go over

to my computer and I run

I maybe copy the URL

for the MP3

dump it in

a

well I'm using Jupiter Notebook

to get this started just because it's easier

but just dump it as a parameter

for a function

and then

submit that so that it starts working

and then just go away

have a cup of tea, have my lunch

and bang

I've updated Libsyn and WordPress

without anything at all

that was my fantasy

and I think

I'm getting quite close actually

so

in order to do that I had to fully

automate the process and the process was just

half automated

so what I realized is

and one of the things

so there were two problems that I had to solve

I had to solve this sort of issue with

photos being

requiring this sort of communication

and I also had to solve this problem

of being able to get physical files

because I can't do it

I can't do any automation

if I'm having to go to a chat window

to pull stuff out

so

pretty rapidly realized

that I was going to have to use the API

so

I'm now using the API

for chatGPT

I tried using the API

for GROC

and I'm also using the API

for WordPress

and

I tried using the API for Libsyn

but there isn't actually an API for Libsyn

so that meant that I had to actually change

podcasting providers

to a different one called Transistor

where they do have an API

so

what is an API you might ask

well yes

I do have this habit of getting rather into the weeds

but what is an API

an API is basically a way of

moving data into an app

over the internet

you call what is called an endpoint

which is just a URL

and you can

depending on the way this is configured

you can then sort of read data

from that endpoint or you can update data

or you can change data

from that endpoint and that requires

you to have

some security to allow you to do

that

and that is called a token

and I won't get into all of that

but basically that's what an API is

it allows you to write some software

that then communicates with all the software

and brings back data

an API is exactly what is happening

when ChatGBT

is trying to answer your question

and the answer is not

within

its data

that it's been taught on

so

I've explained this before

but ChatGBT

they run the model

in 12 months and this is when a new

version of ChatGBT comes out

and what that does is

you basically get the model

you've made some changes to the model

then you train the model

and it pops out

now I've fully formed

of ChatGBT version 7

and

so there's a whole load of

stuff in that model

and so you can get quick answers

most of the time and it just looks at the model

and answers your question

however if you're asking questions which rely on

more timely data than what it was actually

modelled on

asking about something that happened yesterday

and the last time the model was created was 6 months ago

it's going to have to go

and find that data

and it does that with an API

so it's using APIs too

so sometimes when you see ChatGBT

and it's like you're waiting for it to do something

it's not actually

doing the work

it's created an API call

which is what it's called where it's asking

some other piece of software for some information

it's waiting for that

and that's what an API call is

so anyway I'm going to go into the world of

APIs now with my automation

and this is going to get me much closer

to my dream

however there is one thing that I still need

to do in this automation

which is interactive

and that is approve the titles

because sometimes I was finding that the titles

that ChatGBT would come up with

they weren't really in line with what I wanted

sometimes when I'm doing these episodes

say

I've got the philosophy

miniseries

kind of thing

I'm on philosophy number 4

and it's on such and such

so it'll come up with a title

which will be based on the content

so it'll be completely not thinking about that

so sometimes I'll just

change the episodes

and sometimes it comes up with terrible ideas

so I just say well have another go

that was rubbish

so what I've done now

is I've got a new process set up

and that's using

APIs

and it's fully automated

now

I went through a bit of a process

here as well so I wanted

to

automate this

and

involved in writing prompts

for ChatGBT

you start to realise that things can get to rather messy

especially when they get long

and I was wanting

a way that I could

in programming

you have this concept of modularity

where

you split things down

into more manageable chunks

and I wanted to get

a bit of that going

in the code

a lot of my process is not

actually ChatGBT

reliant

all this calling APIs

well that's nothing to do with ChatGBT

that's just code

although ChatGBT is helping to write the code

just makes it quicker

but yeah

so I've got this sort of requirement

for some code-based stuff

and also some ChatGBT

or GROC or LLN

based stuff

and I want to get some more modularity

into the whole thing

to make it a bit tidier

so originally

I looked into something called N8N

and

it's like a lot of these graphical interfaces

look super cool

you basically and this would be a good thing

for a lot of people I think

if you're wanting to create some kind of agent

that does something because this is in effect what I'm doing

is creating an agent

then you use this N8N

and

I'm quite familiar with data processing

I've

done it as a career

in the past

so it reminds me a lot of these

sort of data processing workflows

basically what you do is you have some kind of trigger

so that could be someone in a chat window

or it could be

a trigger caused by

like a date coming up

or somebody entering something on a form

on a website or something like that

and then this trigger

and then the trigger then

starts a cascade of things happening

so you know

you could type some things into a web portal

and then what happens is

I don't know maybe you chat

maybe you chat in something that you would

you would like a PowerPoint

I want my PowerPoint to do blah blah blah

and then the first thing is it goes to chatgbt

ask chatgbt to create

a

a list of the slides

and then it goes to

maybe

maybe you then take that list

and then update a Google Doc spreadsheet

with that list

and then you could do something

whatever you can do

in this N8N

you can put things in a Dropbox

it's got all these different

it has all these

API connections already sort of embedded

into it so you can

it makes it more easy to use

and then it's a sort of graphical interface

if you want it

so it looked pretty cool

what I didn't like about it

was the fact that it was a graphical interface

basically and I'm finding that

the more I work with

well the more coding I do

the less I like graphical interfaces

and especially

when I'm doing chatgbt

stuff and doing code

with AI it's a lot easier

to just get the full code

and dump that somewhere

than to be worried about

getting bits and bobs and updating

drop downs and things like that

it just makes it easier

I know that there is a way of uploading

JSONs into N8N

but I didn't much like that

I would have been more happy

with a complete code solution

and then what really

did it was that

the code that you use in N8N is

JavaScript look and I'm quite

happy with JavaScript

but I think if I'm going to be doing data stuff

I'm better off with Python

that's really what it's

for

people would dispute that

but I think

especially if I'm moving around files

on my computer

and stuff like that

Python is just really the thing

that I feel I should be using

and I think it's a more appropriate tool for the job

so I started looking for

works that use Python

that also work with

LLNs and I came up again

I came up with something and it's called

CrewAI

so my system now is using

CrewAI

and that system

basically

when I

there's a few manual

processes at the beginning because obviously

I've got to

I've got to do the recording

manually

then I still

using this semi-automated process

which basically just takes the

NKV file and creates the WAV files

but it doesn't take long and it just runs on my computer

so I'm doing

that and then I have to create

the show manually

again so

these activities probably take me about 5 minutes

to be honest 10 minutes

they can take me an hour or so

if the podcast is requiring

a bit of finessing

but they don't necessarily take me very long

and then I get to the point

where I've got a finished

transcription

I've got a finished MP3 file

and a finished transcription file

and once I've got those in the folder

then I have this

new process which is running in Python

all the code is running in Python

and the semi-automated stuff as well

but this is like a sort of app that then runs

in Python

and what that does is it then

takes in the

URL of the

transcription and the MP3 file

and

loads them all in

and creates

all of the content

while it's creating the content at the very beginning

it gives me the option to approve the titles

or disprove the titles

basically I can

yes, no or put in my own title

and it will do this

so I can

submit maybe

podcasts

but let's say 5

I tend to work on a batch process

so I can submit 5 URLs

for MP3s

and all of these transcriptions are in the same folder

so it finds them anyway

and then it takes those

and creates the title

etc etc I approve it

or whatever

and then it then goes ahead and creates all the content

puts that content into some JSON files

stores them on the

computer

and then uses those JSON files

to update the APIs in WordPress

and Libsyn

so

my aim with this is, my feeling is

if I can get this podcast to the point where

I am not overwhelmed

by the administration

then I will continue to do it

I am a curious person

I am always talking to chat GBT

I am always trying to find out answers to questions

and I love it

so I can't see any problem for me doing that

but

the manual stuff of actually loading things in

and all that kind of stuff

makes me want to stick pins in my eyes

so if I cannot stick pins in my eyes

that's what I want because that means that I will actually continue to do this

so

and I think I am very close

so

are there any other key learnings

one of the things I can tell you that I sort of

I mean

I mean I have been coding

I have been coding for the last couple of years

so I have been using AI

to assist

but a few things that have cropped up recently

I mean I am not using, so for example

I am not using

I am using Visual Studio Code

but I am not using the AI agent with the Visual Studio Code

I just don't like it there

I would rather only use it when I need to use it

but if you do that

and you don't have something that is constantly

looking at your actual repo

with your code

the difficulty you can have is

it doesn't really appreciate

you are asking it a question

but it doesn't have all of the context of everything

that is in your repo to understand exactly

how it all works

so one of the classic problems that I get

is

especially with Python at the moment because I haven't installed

any tools in Python that will

correct the code

if I was to change file names

and folders and things like that

because when I am working with JavaScript

I have got plugins

which basically say

you have just changed this file over here

which is imported in this file over here

I will just change the imports automatically for you

because it is a real pain

especially if you are refactoring your code

so that was all done for me in JavaScript

in Python

it is not done for me

it is just because I haven't got round to figuring out

I wouldn't even say figuring out

I haven't even had time to think about it

I have been prioritising other things

but that hasn't really been a problem so far

because the Python stuff isn't

it is quite flat

there is not a whole load of depth to the code

and

one thing I figured out

is that you can actually just zip up an entire

directory or subdirectory

attach it to chatgbt

and say here is my code

it is good for you to fix this

and then it will go ahead and do that

and it will change all of the interrelationships

with everything

so that is super good

especially for refactoring

if you want to refactor one of the things I have done a bit

today is just

simplify

simplify the code quite significantly

and in order to do that

that is actually a really good use

I mean I have done it before

but not in that way

not sending it

so it is not that irrelevant

but I just thought it comes to mind

something I found useful today

but

yeah so I hope

that explanation explains

how I am using AI

and

some of the

things I suppose

reflection

now after working

on this podcast

and automating this process

because before

when I was programming I wasn't

I wasn't coding with

I was using AI to help me code

but I wasn't actually using AI

to solve a problem with the app I was working on

which I am doing now

yeah I guess

so

oh yes I remember

yeah so my point

so after doing all of this

it does make me think

about the use case

for AI in the workplace

and how

the challenges

and

how things are going to pan out I guess

and it sort of reinforces my thoughts

that I have been having in some of these other podcasts

about where I think it is all going

I don't think

I think ultimately

programmers are going to become obsolete

but I don't think

the short term thing

I think in some ways

they are

but

I think there are other occupations

that are going to be more obsolete

more quick

and in the short term I think there is actually going to be

an increased use of people

with technical

programming skills

but they won't be programming

in the same way as they were before

and they will be

required to

recode people's jobs

I mean the obvious

thing that I am sure most

big companies are doing at the moment

is using AI

to

follow people around

if you have got various

for process mapping

but you can get

documentation

and once you have got the

documentation then you can take it to the next

stage and think well how can we

are there

you can do analysis on that

documentation you can say well

out of all these processes

strategically can you look at it now

and tell me

is all of this required

first question

and then you

obviously can remove quite a bit

just like a tangled web of code

you look at all these process maps

and you

not you, AI does

and figures out what is redundant

what is duplicated

so that is the first step

and then once you have done that

you can reorganize according to that

and then the second step will be

to well what is automatable

what is easily automatable

and then you are going to need people to create

those automations and I would argue

that when you start getting

to the point where you are actually

automating stuff in a meaningful way

then

I don't think people

general people

will

they will have the skills

to do something but

I think there will be a difference

because it really

is programming at the end of the day

but it is just very high level

it is very high level programming but

the power that you have is very high as well

so there is a

focus on being

what would the word be

disciplined in your thinking

if you go off

ad hoc without

some disciplined thought about what you are trying to achieve

you are likely to get

in a mess and I think a lot of

you know the more I do this the more I see

I know what the next thing in AI is going to be

is going to be big

corporate companies saying oh we tried AI

and we made a complete mess

and

and I think that is going to be the case

and there will be successful

companies that manage to focus

and work out how to not make a

complete mess and to take advantage

and there will be other companies

which will just be I think the majority

of companies will be saying yeah we are doing AI stuff

oh yeah we are really clever

we are doing AI stuff and they will be saying that

because they are worried that if they don't say that

the share price will go down

and then

but they won't be

they will do it half arcing it

and probably

they will either be overly cautious or they will be making

a great big mess one or the other

so

I think that is going to be the big challenge

and that is going to require people with the technical

ability

to coordinate these activities

and work with AI

to

get what you want

in these companies

so I am not particularly concerned being a developer

I think

there is a lot of change and it is a good time to

understand AI for sure

you know if you are

if you are sort of not flexible

obviously that is going to be a problem

and there is a lot of jobs that won't exist

you know

I mean obviously call centre jobs and things like that

they can probably be done better with AI

and there is tons like that as well

marketing jobs

it is scary how good it can do marketing

anyway I think I am waffling now

so I hope you found that interesting

I am happy to

answer any questions about

what I have done

I am no expert I am just learning AI stuff

as I go

and I hope

it is difficult like talking about

code without actually having seen it

and you know people will

know different things about code

so I turned myself into

a

code tutor

but I hope I didn't go

I hope I kept it quite high level

and you will understand what I was talking about

maybe I should have done it with chatubt

could have explained a few concepts better maybe

but anyway I have done it now

so I hope you enjoyed this

and speak to you next time, goodbye

talking to ai.show