Good morning, Budapest. It's awesome to

to be back. Today, I'd like to talk

about some people, a few thousand that

are having a terrible week uh this week.

And this is specifically people inside

Meta and Instagram. I talk with a lot of

people in the industry. I have a lot of

friends inside of these companies. I

have even more I guess contact software

engineers who message me to tell me what

they're seeing, what what's happening.

And this week has been the worst in Meta

or Facebook history in probably forever.

So what happened is on Monday, we've had

the goofiest ever Instagram exploit. It

wasn't even an exploit, but it it was a

security breach. It was an attack.

What what happened is

I mean I I mean this this is from a

software engineer writing a book. It

this is the the most most goofy thing.

So there was two steps to this exploit.

Step one is you had to fake your

location to a victim. Let's say you

wanted to take over Barack Obama's

account on Instagram with like I don't

know tens of millions of followers. You

fake your location with a VPN to the US

and then you went to Meta AI you and

said that hey my account has been hacked

and could you please send verification

code to the AI to this email that I own.

And then step two was there was no step

two. This was it. Meta AI sent out a

code to you and you could take over

anyone's account.

This is this is the first zero authent

zero off password reset and we're

software engineers. You know what this

is? This is this is a bug. But the thing

that I couldn't get my head around is I

know people at when it was used to be

called Facebook. They have a really

strong engineering culture. They have

the globe's best automated rollout

canary system. They have so many layers

of verification. They have really good

engineers. They have manual code

reviews. and none of it. They have a

trust and safety team for God's sake.

Their trust, Instagram's trust and

safety teams is closer to 100 engineers

whose job is to keep this platform

secure. And you know, a few things

happened. The next day on Tuesday,

Meta's chief information security

officer sent an email saying, "I'm I'm

out. I'm quitting." This was very

interesting because Meta has just kicked

off a se an outage investigation. They

call it SEV inside of meta. And in the

middle of that and in even before it

concluded, the chief information

security officer stepping down. So I

asked around I I asked the people I know

at Instagram. I I happen to know people

on Instagram's trust and safety team.

Well, turns out they were only on trust

and safety team. So they even, you know,

shared me more details. You're hearing

this for the first time ever, by the

way. It's not an attack press. It

probably will be. It was AI. Of course,

it faking was AI. The thing that caused

the issue was AI written code that was

reviewed by AI and not humans at Meta.

And I'm thinking to myself, how could

have this happened at Meta? I mean, it

wasn't just AI. There's more to the

story. It was AI maxing, it was layoff,

and it was AI psychosis at Meta. And

what I mean with this is a AIX.

If in April I I wrote about this this

new trend called token maxing which was

happening across so many companies

including Meta, including Amazon,

including Uber, engineers were starting

to be measured on AI token usage at at

all these companies and they start to

inflate it. They just want to get to the

to the top leaderboard. They told the AI

let's do some like dumb stuff and you

know I get to more tokens but I I don't

need the work. And at Meta there was a

leaderboard and you could get status

like session immortal token and legend.

Uh in April meta killed this project but

but people were burning crazy amounts of

of things. Now AI usage inside of Meta

was part of performance evaluation.

It it wasn't like officially made up but

people inside of Meta are smart. They if

you had a low token count you know

that's not a great signal. So people

just start to inflate their token count.

So they start to use AI for anything and

everything. Write it by hand. Nah, why

why do it? Ask the AI. Read the

documentation. Nah, let let me use the

AI to to read it for me so it can just

burn a bunch of tokens. This is the

craziest thing that's happening, but you

know, inside a meta AI is free. And

again, these people want to have higher

bonuses. And they just use AI for

everything. Um, and yeah, the the code

that caused this SE was also AI

generated. Of of course, they use it AI

to review it as well. They use it to

triple review it, etc. The second part

to this thing was layoffs set meta. Meta

told the 10% of of of staff 8,000 people

will were laid off in 20th of May but

Meta told people or the press told

everyone that the layoffs are coming a

month before. So what people were doing

is as they were thinking oh am I going

to be laid off all of them they start to

use more AI because they didn't want

their token numbers to be down because

they didn't want to be fired for not

using enough tokens. You you see where

this is going, right? And they were not

really busy, you know, doing their work.

They were just worried about like, all

right, like let me get this inflated. So

inside of trust and safety team, people

were not thinking about trust and safety

were thinking about token maxing. And

finally,

I was wondering if I should call this AI

psychosis because psychosis is a very

serious psychological condition and

that's why I put it in brackets. But

I'll I'll show you why I I chose this

this name. Instagram had a tr thread a

trust and safety organization that was

built up over like seven or eight years.

A really good team mostly based in

London.

40% of this team before 20th of May was

reassigned to do manual data labeling.

They they were told on Thursday that

starting on Monday, you are no longer

working on this team. you are moving to

this new team in Alexander Wang's org

xscalei and you will be doing AI data

labeling which means you get these tasks

it's a GitHub GitHub pull request you

need to review it you need to add some

tests you need to add some feedback and

then then you do the next and then you

add some tests and you add some feedback

and you and you do the next these highly

skilled people they were not given a

choice now inside meta until now every

engineer was treated like royalty they

were given a choice they were not given

a choice so 40% of the organization just

boom gone There's five closer to 5,000

developers inside of Meta doing manual

AI labeling. And there's a running joke

inside of Meta that this is bigger than

OpenAI. This data labeling or Meta

clearly wants to build this amazing AI

model. Oh, and after the layoffs and

after the reassignments, most teams are

less than half the size. Some don't have

on call coverage anymore, which means

that in some services, there's just no

one picking up on call. This again has

never happened inside of Meta. And this

is what I mean by AI cycles. This is

fully self-inflicted. This is coming

from Mark Zuckerberg. This is coming

from Alexander Wang. This is coming from

the top. They're saying we don't care.

We it's so important for us to build

this model that we will risk our

business and we don't care if you know

we get hacked or something like that.

Morale is as low as has been in in Meta.

I've I've seen low morale. This is way

worse than the 20 2022 203 layoffs. Uh,

and oh, and yeah, if this wasn't enough,

in the US, they're recording your

screen. They're recording all your

screen strokes to train an AI. So, I uh,

it's the easiest time to hire to recruit

from Meta right now. Uh, and the

engineers that I talked to, they just

feel super let down. Meta used to treat

engineers like royalty and salary,

composition. You you could choose your

team. It was a good world event. And the

CEO, Mark Zuckerberg, he is a software

engineer. He wrote a lot of Facebook's

code. and they feel we don't matter

anymore. We're tools. We've been thrown

away. Uh a lot of people are are have

been given large retainer bonuses who

have not been fired. You stay. We're

giving you money. They are still

interviewing and they told me they're

interviewing not because of the layoffs

because they know they can find a job at

Meta. You know, these are super highly

paid people. They they can get a not as

highly paid jobs. They're in demand. But

they said, "I don't know if I'm going to

be assigned to data labeling." And as a

professional, I did not sign up to

become a manual data labeler. And a

bunch of my colleagues are doing that

and interviewing. So Meta is destroying

their engineering organization that

they've built up over 22 years. And I

think this might be end of the

incredibly strong Facebook engineering

culture that I know and I I I've learned

to actually love even though I've never

worked inside of Facebook and so many of

my friends have. So this is because of

AI. Now, not all companies are like

meta. This is pretty extreme, but it's

happening. It's happening right now. The

these are these are facts. But the

industry has a pretty interesting time.

And today, I want to talk about this. I

want to talk about what how everything

has changed in the past six months when

it comes to software engineering or or

well at least coding.

I'm going to give you a tour of the tech

industry of what what other tech

companies are doing. I'll give you a

brief tour uh because this is what what

what my head is in in day in day out.

And again, I'm I'm I talk with a lot of

these people. I I visit these companies.

I'm friends with a bunch of them. And

then I'll share a few trends that are

happening across the tech industry. And

then I'll close with advice to software

engineers and engineering leaders on how

we can navigate to prepare to to do the

best that we can and and also just you

know come out of this whole thing

stronger.

So everything has changed in this past

six month. This is a pretty dramatic uh

uh thing to say and but

it it it it has changed. So uh DHH David

Hellmire Hansen, creator of Ruby on

Rails, he was on my podcast in February

and and he told me that he actually

wrote this uh on on Twitter that just in

summer 2025, he spoke with Lux Freedman

in October and he said that AI was not

writing any of his his code directly.

But part of his resistance resistance

was that the models were not good enough

and it has now flipped by February.

Most of his code is being written by AI.

Now this is a person, you know, he's a

he's big into software craftsmanship. He

is not paid by any lab, but he decided

the models are now good enough. They

write better code than I can. He

actually told me this on the podcast. So

I I listen to to people like DHH uh in

in this sense. Simon Willis is someone

who is the one of the most uh quoted

person on Hacker News. He is an

independent software engineer. I love

Simon. Uh he uh he's he's also a friend.

Uh he created Django and he writes this

really good daily newsletter pretty much

where where he just experiments, he

builds open source and tries out all the

models. And he said that the models

released in November 2025, specifically

Opus 4.6 and GPT 5.4 uh have elevated

agents to being genuinely useful. we've

had the six months to get used to this

idea now. So, no wonder that companies

are now starting to spend big money to

spend this. So, he's also saying that

it's has changed. I got some data from

some of our partners, my friends at

Linear uh shared this data never never

shared before on how

how t how teams are using now agents to

ship more code. They are comparing teams

that are on linear and they're not using

AI agents and teams that are and by now

the teams that are using agents are

shipping five times as more code. We'll

talk about quality later but th this is

massive 5x increase. I mean we've

probably had five increp

like 20 years before and this is in less

than two years. uh

friends at cursor have shared uh details

on how devs using cursor are changing

the lines of code they produce in a year

and in a year it has gone up by almost

two and a half times from three up 4,000

lines of code to more than 8,000 lines

of code just on cursor so you know we're

we're seeing this acceleration the size

of PRs also from cursor is up by 3x so

if you combine those two that's six

times as much code and you know a lot of

you are kind of like I see smiling I we

know that there's six times as many bugs

yeah we'll again we're going to get

there

and also data from cursor the percentage

of devs using cursor who are accepting

changes from the AI without any manual

review is massively up in January this

is when opus 4.7 came out uh GPT 5.5

came out and what a lot of companies

realize that clock code cursor codecs

They're actually really really useful

and they're starting to trust it. And

again, remember when I told about you

about meta

merging to production without human

review? Yeah, that that was somewhere

there. So, what are tech companies doing

right now? And let me give you a bit of

a tour of the industry. So, uh at

Entrophic, I I visited their offices

last fall and I I talked with Boris

Churnney just in February, the creator

of Claw Code. And here's what they're

they're they're doing. Uh Boris

specifically runs five parallel agents

on his laptop all the time. He ships 20

to 30 pull requests a date and this is

on top of leading all of quad code. He's

very much a hands-on leader. He told me

that the PRDS writing documents to plan

are dead. They're using prototypes

across entropic to replace them.

Today 100% of cloud code is generated by

cloud code. Inside Entrophic is not 100%

but it's closer to 70 to 90% and there's

no target. This is just people using it

again but this is entropic. we shouldn't

be too surprised. Uh and then the

company built cloud co-work in only 10

days. Uh and it's become a massive

commercial success for them. Uh it

generates so much revenue. In fact, I

have some sources inside of Microsoft.

Microsoft tried to build a cloud co-work

because cloud co-work is really good for

for Excel and Windows to use it on

machine. Microsoft still doesn't have an

answer two and a half months later. I

heard that Sacha Nadella gave a deadline

of a month to this team to build it and

they couldn't build it. So don't forget

that there's differences between

companies and traffic is accelerated by

AI. Some companies are kind of held back

despite AI like Microsoft and again

we'll talk a little bit about that as

well. Open AI open AI also at uh a

friend from uh the pragmatic summit uh

in San Francisco in February. That's us

on stage uh with him and the Codex team.

We talked about a bunch of stuff and and

what he told me is uh some interesting

stuff. They have inside of OpenAI they

they have an internal version of the

chat GPT app and they have fix it

button. You can literally just take a

screenshot and say fix this bug and it

goes to codeex. It generates a a pull

request and an engineer can merge it. In

fact, even a non-engineer can merge it

and there's safety nets there. AI code

review obviously is everywhere. They

have multiple layers of it. uh they have

tiered versions. There's some code that

can go in with just AI code review into

production and there's some code the

critical path that humans need to

review, engineers need to review. Uh

most devs obviously run several agents.

There's this joke that uh when you're

walking around engineers are bringing

their laptop and it's slightly open.

It's slightly open so the local agent

can still keep keep running. And when I

was I did a video interview uh with one

of the OpenAI folks and I was just

jokingly asking like, "Oh, so like

throughout this interview, did you have

agents running?" He's like, "Did you

have an agent running?" He's like, "I

didn't have an agent running. I had

five." And I was like, "Oh, okay." Like

it's it's common for people to go into

meetings and their agents are running.

They're thinking about agents. They they

keep it on track. Like again, but these

are they are the most AI pilled people

in the industry. And of course, you

know, they they greatly believe in all

this. They all talk about AGI and and

when it's coming, not if it's coming.

But this inside of them, most people

don't really write code inside of

OpenAI. This has changed in October.

They still like there were devs who

wrote 30% of their code and 70% with AI,

but 30% by hand. And I think it's just

slowly going away. The Codeex team

obviously writes it all with Codex. And

they're telling me that taste, knowing

what to build is becoming pretty

important uh in inside the company.

Codeex also improves itself as as a fun

fact. It tests itself all the time. It

runs all the tests overnight. They kick

it off because most of the team is in

San Francisco. So it's one time zone. Uh

they have codeex run itself and look for

ways to improve itself. And by the

morning it comes up with improvement

suggestions which they either accept or

or reject. And when they have meetings

and debugging sessions when they start

the meeting they have voice notes that

they send to codeex as it goes and it

comes back by the middle or end of the

meeting with like results. It's it

sounds like science fiction, but again

that that's how they're working inside

of cursor. I I visited their office in

October in in San Francisco. Um they

they have you take off your shoes and

it's sometimes it's a mess, sometimes

it's super organized. There's like a

sorting algorithm invisibly happening

inside of their office. It's it's really

interesting slashcool. Uh but they're a

very nice group of of folks. Uh they

have gone all in on agents as of January

as well. They're like it used to be all

tabs and the editor. They're kind of

like moving on to agents. They still

have the old old experience but it's

increasing the old one. They they built

their own coding model. They're one of

the only companies outside of open air

and traffic who have a really good

coding model. I have no affiliation with

cursor. Uh but their composer model is

cheap which is going to be important as

as I'll talk about it. Uh and they

operate tens of thousands of NVIDIA GPUs

in massive data centers. They're leasing

it from Azure uh AWS and so on. And most

of their inference used to be uh

inference used to be so generating the

the response. It used to be their

biggest cost, but now they're also

training their models. So they're kind

of turning into this mini AI lab. And of

course now SpaceX is about to purchase

them or not or who knows, but it it

seems it's going to happen. Uh they're

also just everyone at Cursor is

technical. This is Lee Robinson

developer relationships at at Cursor. He

wrote u with Cursor. He migrated all of

cursor's sites to a different CMS with

and of course you know he's sharing how

how much he's cost to show that it's

very economical but this is this is not

a software engineer by job and everyone

a cursor is like that so these labs are

everyone goes there Google uh briefly

everything is custom at Google

everything including their ID Google's

internal ID is called cider they have

strange names for everything it used to

be a web-based tool now it's a visual

studio fork uh they have a thing called

jet ski which is anti-gravity but the

internal version which is integrated

with their their monor repo piper and

all of their other internal systems uh

they have critique a code review tool

which again they don't use github they

don't use all these everything is custom

inside of Google AI is of course

integrated gemini is integrated nicely

in there they have code search which is

the source graph for rest of the world

in fact source graph got inspired by

Google has some of the best code search

inside of Google they don't they don't

make it available uh uh outside and they

Google has so many internal systems.

Borg which is their version of

Kubernetes uh Monarch which is their

version of data dog uh many many more

piper their version of monor repo AI is

integrated into all of these things and

it's all integrated together really

really nicely so inside it's a really

good experience only problem inside of

Google is Gemini is just not as good as

Opus or GPT 5.5 and inside of Google

whenever engineers can use cloth code

they do but only they can only use it

inside the Gemini or which means that

Google doesn't have as good of adoption

of AI than some of the other companies.

Kind of weird, but they're working on

it. The CEO knows, he admitted it. They

want to get a better model about it.

And finally, Meta uh they they want to

build their state-of-the-art AI model.

Everything is about this. Uh they do

have an internal tool like Metamate.

That's their that's their AI tool for

coding. They have this thing called

trajectories. Whenever you you know when

you see GitHub commits inside of Meta,

you see the exact prompt that people

did. They rolled it out in December and

people in Meta got upset because no one

told them this would be public and you

could see like you know like staff

engineers saying like can you write me a

for loop and it it was all public and

everyone could see it. So some people

inside of meta, I talked with this dev

and he said like, you know, I started to

write my my my uh my uh chats with the

meta AI the code generation in Polish

because fewer people can read it now.

Okay, it but you know right now at Meta

they have bigger things to to worry

about. Uh this force reassignment to

build AI model force tracking of

everything. It's clear meta Mark

Zuckerberg wants Meta to have an model

that's better than Opus 4.8. eight. I

think either he's going to get it in a

few next few months or all of meta is a

lot a lot of meta is going to be like

disb not not disbanded but very very

demotivated.

Uh Uber my old company uh I talk with

them in detail. I have a deep dive on

the primatic engineer if you're

interested in learning about more of

these details. They built so much

in-house tooling and a lot of companies

do this but I'm just going to like

quickly show you how much in-house AI

tooling a company like Uber built. Uber

has about 3,000 engineers. So, just keep

that in mind. They have an AI, well,

they have a developer experience team

who is now pretty much an AI experience

team of like about 20 people or so. So,

they built an internal MCP gateway.

Pretty clear. You can, you know,

discover, register, do all do all sorts

of jazz. They built an Uber agent

builder, which is a no code way to build

agents for the rest of the business.

They have an Uber agent studio where you

can like drag and put together your

agents. Again, there's uh OpenAI has

something like this publicly. That's

open a As a Asian builder, but it's it's

for the nontechnical folks. They have

Uber Asian Builder Registry, which so

Uber is 3,000 engineers, but 20,000

other people. Those 20,000 people use

this thing. They create this stuff, they

plug it up, and engineers built this for

them. Uh Uber has an AI FX CLI. I'm just

going to call this the cloud code for

Uber pretty much. They built it

themselves, integrated with all their

system using all the different models,

etc. They have Uber Minion, which is

running background agents at scale. Uh

so you can again this is sim similar

thing as cursor background agents except

it's integrated into Uber's monor repo

and experimentation system called

morphus and and all of the other jazz

really really nicely and it works a lot

better. So even though devs can use

cloud code they will use minions because

it just works better and faster. For

example uber minions when you give it a

prompt it will analyze it and it will

give you a suggestion that ah these

prompts could work better results faster

cheaper etc. So this clock doesn't have

this yet. They have Uber code inbox. Uh

people are getting so many AI so many

pull code reviews that are are now you

know mostly AI reviewing code that

they're creating a system to show this

one needs your attention. This is

important. Focus on these things. So

people when they get into work they

start going through these things.

They're trying to make code a bit more

fun. They have something called smart

assignments where there's SLAs's where

you need if this is not this person

doesn't respond in like a day it goes to

the next one. It's a bit like on call

tooling again all all custom. They have

risk profiles. They will try to identify

this code change looks faking risky. You

need to you know like look at this

closer. And they have U review which is

the code rabbit or the uh the the sonar

uh for for for

Uber's internal again all all custom

work. So they build all this MCP agent

builder CLI minions etc. And the other

large tech companies they're doing the

same. I'm not going to run you all this.

Stripe has minions tool shed blueprints.

Z boxes ramp has inspect glass dojo

sensei. Sensei is a funny one. Shopify,

Sidekick, LM proxy, dev MCP server,

Airbnb, One everything, Catalyst and so

on. They all build their own own stuff.

Uh they have a dedicated infraorg

building all of these for all these

companies. So if you thought, you know,

you're pretty cool for like integrating

Slack into into integrating AI agent

into Slack, you are pretty cool. But

this is this is next level. I talk with

a bunch of startups and I'm not going to

go through all of them, but the general

trends I I see there uh it's kind of the

usual agents are are doing coding, doing

code review. There's a bunch of

creativity mostly about Slack. You know,

people tax Slack. I I saw a startup

recently that raised $70 million uh in

series B. They just told the agent like

fix all bugs in the codebase. Haha. And

everyone's laughing in Slack. And then

the agent came back like, "Oh, I

actually found like four critical

authentication issues where your back

door was wide open." And people were

like, Okay. I mean, that's that's what

startups are. They they didn't know like

their how their house is exposed. Uh uh

they're they're usually plugging in the

AI agents, integrating them, and some of

them are having fun vibe coding SAS. I

think it's just engineers having fun. I

don't think it's really a business

thing, but it's it's it's it's I only

see this inside of startups, not really

inside of big companies. And inside

traditional companies, so this is the

most interesting thing. It's all the

same. I mean, not the level of Uber.

They don't have dev platform teams, but

they are not really lagging behind. Uh,

for example, Cisco rolled out Codeex to

18,000 engineers back in January when

Codex was pretty small and they're doing

a bunch of complex migrations. JP Morgan

Chase built a multi- aent framework,

which is a fancy way of saying that it

just uses multiple specialized agents to

label customer interaction data. They

use evals, judgebased aggregates. Like,

it's it's kind of cool stuff like even

inside of these companies.

So this is what's going on inside. Now I

want to give you some of the trends that

I see crosscutting everywhere or most

mostly everywhere.

One of the big things that comes from

Laura Tacho. Uh this is me at the

pragmatic summit with Laura and and with

Martin Valor in San Francisco. She uh I

I messaged her last actually last night

and she replied this this morning. Uh I

was asking what do you see Lara? Uh

because she was C2 at DX. she's now uh

heading up pretty much developer

experience at AWS and she said that many

organizations get stuck uh not seeing

they see individuals doing great but the

teams are not like the team output is

not there and she said is because they

are thinking about AI as a productivity

tool for engineer for individuals and

she calls it of the individual speed up

juice things like email summaries slack

automations even code generation

however the companies that are moving

faster and they're seeing the result.

For teams, they are doing something

different.

They begin with a business outcome. For

example, I want to deploy to production

faster or I want to push more features

out with the same quality or I want to

improve quality. Spotify is a very good

example. We don't hear too much about

Spotify, but I talked with their CTO

about a month and a half ago. We had

lunch and he told me that their quality

for their their bar for using AI is the

quality needs to stay the same. So

they're not seeing a huge increase in

output but they have built a lot of

internal tools to check for the quality

and they're slowing down the rollouts of

AI versus you know what Meta is doing or

whatever they're not doing. And again,

that was their goal at Spotify. And

Laura was saying that you need you want

to build an agentic system that reduces

handoffs, that makes it easier to find

information and removes friction while

maintaining quality. That last part is

very important. Few companies do that.

And and you know, maturity comes from

applying AI to the system and not the

individual. And a lot of people are

focusing on the indiv individual and

that's why we're not seeing it. And she

wrote this mental model. She created

this. uh she was saying most companies

are in this thing where when you have AI

usage that is either individual or team

level and decision-m that is either

simple automation or agentic systems

most companies are in this bottom uh

left corner where you have individuals

doing simple automation where most

companies want to be is where they have

team level agentic systems but to get

there you need to do what I've shown you

Uber to do you you need to build a lot

of systems that integrate you need to

iterate on this it takes time. It takes

a massive investment. You're not going

to be able to buy claw code or cursor or

whatever vendor tells you to do that uh

that it does it because you need to

build it into your system with your

engineers. That's what Uber is doing for

sure.

Now, other trend token maxing and

tooling addiction. Um

hopefully some of you might be doing it,

some of you might not. It's going out of

style by the way just just I'm talking.

There is just a big pressure to look

productive and to not have a low token

count, especially inside of US tech

companies that don't really care about

budget until they do. But right now,

they some of them still don't. It's it's

it's ending. A token maxing is is when

you're just burning all these tokens

without value shipped on purpose. And

again, I I've talked to this happens at

Meta, Amazon, even in Microsoft

everywhere where they have internal

leaderboards. Microsoft still has it. I

don't know why they're not shutting it

down. They should listen to me. Uh there

uh also the pricing of these tools feels

a bit of addictive. You buy the $10 plan

or the $20 individual plan and then you

run into a limit and a generous limit.

But then you run to a limit and then

you're like ah let me buy the $100 plan

or the $200 plan. And once you buy it,

you now feel pressure if you're buying

it for yourself that you're not using

your your allowance. So you're starting

to use it more. And next thing you know,

you went out and you're now on on API

pricing. And also with every prompt once

you start using the AI agent the first

few months it's a bit like it's gambling

for some people get sucked into it

really like gambling. It's just one more

prompt one more prompt. People are not

sleeping that well. You're you're waking

up and thinking about your agents. If

you're paying if you're uh your company

if you're paying out of pocket you feel

AI being wasted. It's it's it's weird.

It's addictive.

Another trend is middle management

managers are just being cut either laid

off or inside of meta reassigned to

individual contributors or being told

you you need to be hands-on meaning you

need to manage less and and do more more

work. uh there's just a flattening

happening and the interesting and a and

whenever a management is fired or or

laid off it's said oh it's because of AI

whatever it doesn't help but the

interesting thing about this is

what happens if we have less middle

management I mean it's popular to hate

on middle management on managers senior

managers and directors top level

management is a sea level the CTO and

the middle management is everything in

between uh maybe until front line

management engineering management and

you know usually we don't know what

directors do uh or or if they're

necessary. However, in my experience,

good middle management, good directors,

good senior entry managers, they are

very technical. They could be hands-on,

but they choose not to. But they listen,

they see what's happening. They pay

attention and they make small changes.

Ah, there's a lot of outages we're

having right now. And software engineers

will just pile on and and do nothing.

They will stop and be like, "Okay, let's

create a task team. Let's build this

system. uh you you get I will pull you

off these teams and we'll make our

engineering culture better. Good

engineering management improves

engineering culture and a lot of

companies are getting rid of engine

management or or bidd management and

engineering culture will go down. This

is a fact as far as I'm concerned.

Another interesting trend at the same

time CEOs and CTOs are back to coding.

uh Gillor Moranch uh founder and CEO of

Verscell. I I had a lunch with him on on

one of the investor events in in

February as well. uh he was right saying

recently that he is seeing so many cos

and CTOs are back to coding with a fury

with all this enthusiasm and he has

public company CEOs DMing him saying hey

we're using Versell or cloud code and

you know like I'm I'm doing it I'm so

excited again and this is all the time

while we're having less middle

management now imagine having less

middle manager to protect engineers and

the co and CT are coding vibe coding and

they're saying oh it's they think it's

complete but you know it's it's not

really complete

a mega trend that is happening like and

it starts to like I noticed this a week

two weeks ago. So, I wrote about it a

week ago and then today uh

like to uh hold on and and then today I

I see uh Sam Alman, this is just from

this morning saying that he is noticing

that AI budgets are seemingly become a

huge issue for some companies and

something that has come up and something

that has never happened before. And I

was pinging people at OpenAI like does

he read my newsletter because I wrote I

I wrote about this last week for

subscribers and someone open said like

someone posted into Slack and like Sam

read it and but it's happening and this

is coming out of the blue. There's this

joke going around as of yesterday on

Reddit saying hey uh oh baby I see

$15,000 are gone from your from your

shared account. Like is this what I

think it is? engagement Frank.

Yeah, I I feel for that guy. He's soon

going to be single,

assuming it's it's it's not a joke. Uh

but it's it's happening and it's getting

worse. Uh Antropic has turned on API

pricing for enterprise customers,

meaning anyone who's not a startup or an

individual is not getting discounts.

GitHub Copilot turned it on just two

days ago on the 1 of June and people are

pissed because they are have burned

through their usual budget of let's say

$200 or or however much it was in three

days that used to take a month and they

are and this is hitting everyone right

now. Everyone will be paying a lot more.

Now Uber is an interesting case again

because in March their CTO uh said that

they have burned through the whole

budget for the year with AI costs and we

were wondering what they're going to do

but we now know they are now setting a

cap of $1,500 $1,500 per month per

engineer on AI and if you hit that

you're going to use the free models and

I've been doing research this is what a

lot of companies are doing a lot of

companies not doing this much some doing

$200 and then you're going uses zero

models on GitHub copilot and now

engineers want to do it but this is a

very very fresh trend costs are it's

ridiculous when it's as much as an

engineer and no one no one wants to pay

that no matter what the AL apps say

and finally some trends across the

software craft we've talked about like

kind of business trends and and and AI

trends but what is happening to software

engineering and and the craft the

conference that we're here one is a huge

drop in quality everywhere this one

comes from yours truly that's my account

I was so pissed off at claude.ai,

their flagship website, for about a

month for a month. Every time I went to

the website, this is the website itself.

Uh I I did a screen recording after I

got pissed off enough uh because it kept

happening and no one was fixing it. You

went to the main website, cloud.ai, and

I immediately start typing my my quote.

And here I'm starting to type, how can I

do this? And as soon as I type, how can

there's a refresh? Now, there's a React

uh life cycle component happening here

where the page finally refreshes and it

loses all that I've typed before and I

maybe I'm old school. I use the website

so much it just kept happening and

happening and finally I tweeted about it

saying like how on earth does Entro oh

and I'm paid user. I'm not a free user.

There's millions of people hitting this

every single day and Entrophic doesn't

care and they're building AGI. So, I

tweeted about it. Uh and the product

manager on the team said, "Oh, great

feedback. I dug into this. this it will

be fixed. This is the short way of

saying, "Oh, thanks. We have no clue

that millions of people every day are

doing this. Oh, and we are not even dog

fooding our own stuff." And this was

there for a month. So, and oh, and we're

the fastest moving and biggest and most

profitable company, but we don't like a

a bank does so much better in this

sense. There's not these I mean, we can

argue if if they fix it that quickly,

but and they did fix it eventually, but

this is entropic. And and it's not just

entropic. Open AAI OpenAI

bragged about how they built this

amazing agent builder that is similar to

Uber's internal agent builder in only

six weeks with one engineer with, you

know, codecs. Amazing. Great. Um,

quality is terrible. People on launch

tried to use it and they kept running

into so many issues. Their forum is full

of of comments which are unresolved.

OpenAI did not come back and fix it.

This is from three months after launch.

someone saying I was bullish on agent

builder when it came out but for example

P 0 type bugs are not getting fixed or

takes ages it just seems like

abandonware so I mean was it worth it

for them building this thing and then

just forgetting about it and AI clearly

didn't help build higher quality

software it's faster but it's just

Amazon uh

a AWS

an engineer allowed the internal Cairo

AI coding tool to make certain changes

and the agent opted to delete and

recreate an environment inside of Amazon

causing a massive outage. Amazon had AI

bugs that were happen because the AI

generated code where Amazon stores their

com's flagship website part of it went

down. This never happened with Amazon.

Same thing as it never happened with

with meta and this is over reliance on

AI or not caring about quality. Amazon

has has made this change uh that it now

requires a senior engineer to review any

AI generated change because they realize

the junior engineers will just say looks

good to me and it causes an issue.

Open code uh is the leading AI hardness.

Uh they're they're like the cloud code

for open source and they use all

different models. Daxrad is the founder

and I love DAX because he's super

honest. They are building a super

popular AI tool. They have almost a

million daily active users. They're

growing. They've grown 10x since the

last four four or five months and he's

very and he doesn't he's kind of

skeptical of AI hype but this is a guy

who's built developer tools but it's I I

love Daxis he's really authentic on my

podcast just last week he told me we're

shipping way more hacks where we should

have first rethought the whole system

from the ground up redesigned it to make

more flex make it more flexible so I

think our judgment meaning the open code

team's judgment is off and he was also

saying how you know we're in the AI

coding tool space but you know what's

not happening?

No competitor is beating us because

they're using AI better than we do. And

he said that frankly, I don't think

we're using AI that well. Like we're

actually telling ourselves to use less

AI and there's no competitor that is

beating us because they're doing faster.

In fact, they're kind of winning because

they're still one of the most quality

harnesses because they're slowing down.

Do you know what is a contradiction?

a CEO and founder of an AI company

saying we need to use a bit less AI and

he he actually told me we need to do

more thinking we should build fewer

things and build the things that matter.

I'm paying attention to him

I'll I'll

I'll send that to Dax. And another trend

related to this is just everything is

broken. Uh GitHub is is such a prime

example. Uh this was two weeks ago. all

your poll requests were gone on GitHub

for about 8 to 12 hours. Uh there's a

there's an alternative GitHub uptime

tracker. I think it's you just have to

search for the actual the missing GitHub

status. Uh something like that which

tracks all outages that they report and

it estimates and B based on this

estimate they don't even have one nine

which is means they're down some part of

GitHub is down 10% of the time which is

absolutely unserious but this is a

serious company. I talked with the

GitHub team. I talked with their COO and

they gave me data that they didn't give

anyone else because they published

graphs without the numbers but they gave

me the numbers and they told me it's

because of the load. Now the load is

this. It is a 3x load increase over 2

years time. And they were like, oh, you

know, like this is a huge load increase.

We could have never prepared for that.

And I'm saying

really

that's it. This is bringing GitHub down

to nines. I I'm I do not buy this. Maybe

there's other things, but something was

really broken inside of GitHub. I'm not

going to say this is AI generated code

but if GitHub cannot

deal with a 3x increase over two years

and sure this will be 5x increase later

you're doing something wrong guys like

other startups pick up this load

laughing and there there's there's

details github has a has a Ruby on rails

model and so on and so forth but yeah um

it's just breaking and uh Mario Zechner

the creator of pi which is what powers

open code uh this is the Austri it's

with Armenure the Austrian AI mafia who

are on my podcast he told me it just

feels software has become a brittle mess

everywhere 98% uptime feels like the

norm on most services user interfaces

have the weirdest bugs I showed you one

and on on on cloud but it's everywhere

and he says that I give you that it's

been the case for longer than agents

exist we've always had it but it feels

to be accelerating everywhere you feel

you see this I even saw with modar

telecom the other I don't think I was AI

generated because I don't think they use

AI but yeah I had a big like software

issue with them and I needed to call

customer support.

One more trend is slob buries the

software engineer who still care. Here's

what's happening.

There's a lot more poll requests. Uh

there's just a lot more code. Uh and a

lot more are AI generated. Uh most

developers inside a company uh have

review fitting and they see it's AI

generated. their AI review went and they

said let's they said it looks good to me

LGTM or you know I'm not sure how uh but

they just do a thumb and they never

reviewed it. There are a few developers

who do review it. Hands up if you

actually like still review code like

properly. Hands up if you if you give it

an honest shot.

Yeah. But there there are many of you

who still try and you still catch the

bugs and you still push back and you

still see that the agent has duplicated

code or well the developer is the agent.

You push back and they are being

overwhelmed. They are being burnt out.

They are being fed up. They are feeling

that they're not rewarded. Oh and when

it comes to performance review time,

they're not going to be rewarded.

They're not seen as the ones pushing out

all the features. So some of them are

burnt out and some of them just quit.

Dax told me that at open code they are

hiring a bunch of these people who are

leaving their companies h because

they're just burnt out being the sole

person still keeping things alive and no

one care. Engineering management is

gone. They've either let them go or

they're now now less hands-on. So

there's no one left to care.

Finally, I I talked with Kent Beck. Uh

he'll be this keynote peer tomorrow and

he summarized this really well. Kent is

amazing at summarizing findings. He

said, "We're accumulating code faster

than we accumulate trust." He said that

with code you need to trust it. You need

to understand it. We don't have time to

do that right now.

AI also amplifies software engineering

experience. So seniors gain the most uh

judgment is rewarded. And we see this

everywhere. Hill Wayne, he'll be a

speaker tomorrow. But he was telling me

how some people are saying oh AI will

help with formal verification with TLA a

very complicated language. He'll show

you a demo tomorrow. And he said the

only people who have been successful

with AI generating TLA plus

specifications that work are TLA plus

specification experts who in the prompt

gave the exact specification of what

kind of prompt to generate. Everyone

else good luck with that. And this is

true for software. If you're a junior

engineer, if you've never built a mobile

application, you can prompt a native iOS

app, you can prompt the agent, it'll

build something, but you know, it's not

going to be maintainable.

Uh old patterns are seeming to coming

back. Uh Dax told me how domain driven

design and verbals guardrails they're

using this open code all the time

because agents are the new junior

engineers. You can start off a lot of

them but these junior engineers I mean

if you think of it like that they need a

lot of guardrails and we used to these

boring enterprise patterns used to

become unpopular because they're long a

long winded you have to explain you have

to type out but they keep agents in

check. So, it might be time to dust off

some of these books and start to use

design patterns again. I'm actually dead

serious about this.

So, this is where we are. Uh, it's it's

just a lot of change, all all sorts of

of things. It's confusing. I'll leave

you with with a little advice. One is is

the the title of the talk, slow down to

speed up

you. My suggestion is to cap your daily

agent usage to what you can either

review or verify. You might not need to

read the code. Peter Shamberger, creator

of OpenClaw. I did a podcast with him.

He said that he ships code that he does

not read, but he builds his own

verification systems. He thinks in

architecture. He always looks at the

module. He has the AI draw AI diagrams

for him. So verify, do not ship more

than you can verify or this might mean

reviewing. By the way, as well, uh, tech

depth is now very cheap to remove. We're

talking about how it's built up. Have

the eight kick off the 80 to remove the

tech deb. Be the chief tech deck remover

on your team. you will feel better for

it and it's much easier. Forget that

it's hard to remove it. It's not. And if

you're not removing it, you're not using

AI efficiently for yourself.

Uh experiment with different different

usage of AI agents because there's no

one-sizefits-all and and you know,

listen to talk with with with friends

how they're using it. Get ideas, tell

them what you're doing. And you know,

like just spend more time thinking and

understanding. This is what Dax, the

creator of Open Code, he says that he

used to spend 95% of time thinking and

5% of time coding. And he said like,

"Yeah, AI is cool because now I can uh I

can now spend 25% less time coding. So I

spend 96% of time thinking and 4% of

time coding." You're not going to have

the luxury, but you know, like it's a

good way to think about it

and you just spend time thinking and

understanding

one thing about working in different

way. Michelle Hashimoto is the creator

of GOI uh founder of of Hashikarp, a

really nice guy. He was also on the

pragmatic engineer podcast in March and

his rule for building software. He came

up with this. He is not an AI maxi but

he likes to be productive. He has one

agent in the background always doing

something. He said if I'm coding I want

an agent planning. If they're coding I

want to be reviewing. And he always has

just one extra agent. He does not use

multi- agents. But this is what I mean

by experiment. Some people use five

agents and they can manage. I don't know

how personally. Michelle found that he

can use only one agent. He has like this

this buddy that he has all the time and

he said it works for him for now at

least. So just experiment, try different

ways of doing things. You don't need to

go overboard. He's a very productive

engineer. He does not care about AI. He

cares about like writing high quality

software.

From Addios Manny uh I I met him two

years ago back in Google and also also a

friend. He

said one of the best things, don't

outsource learning. It's just too easy

to let the AI write code while you skip

all of the learning. The bug get fixed,

but your mental model does not. We're

trading off your capacity for present-

day speed, and the tools don't force us.

So, you need to just whenever you use

these AI agents, do not skip the

learning. Understand, learn something

when you use an AI agent. And this is

what I mean. You don't need to review

all the code, but you need to learn

something from or build a system, have

it build something for you.

Uh when when I look around on a job

market, I have I have some good news.

The job market seems okay globally. I

they did a deep dive in the pragmatic

engineer. Uh and you'll have access to

to that deep dive, the full one, uh very

soon. Um the top tech companies are

hiring more than they have before. So

it's going up. It's not as good as as

before. Now the bad news is that in in

the US and in the UK, we're seeing 20%

increase in software engineering. This

is not AI engine. This is software

engineering. In Germany and France,

we're seeing 13% and 10% decrease, which

is it's not terrible, but it's not

great. This is from two years ago, and

in Canada, it's flat. I don't have data

deals from Hungary, but as we know,

Hungary is very much tied, as we know on

the press, to Germany a lot. So, a

similar trend might be happening. This

is data from indeed. It's a pretty

reliable data source. Uh, and I I I

trust them. uh now on the job market in

the US and and US tech companies the top

tech companies AI engineering is an

absolute blast in hiring so this is AI

engineering is part of software

engineering it's now taking up about 10%

of all software engineering is going up

so anything a engineering means you're

building rag you're building evals

you're building systems that are doing

something with LLMs

future profiting for your career my

personal advice build things that that

build on top of AI and LMS because you

will get hands-on with rag AI

engineering by the book by AI

engineering by Chip Huan. It's a very

practical book and try to build

something either on the side build your

own podcast recommendation system or

whatever or at work show off to your

colleagues answer and even your managers

and your your you know your your

colleagues will be happy to see oh

really cool like you just built an

internal tool to do XYZ.

Don't uh outsource your your your

thinking to AI. Try to think more on

product understand the business. Um

there's a book called product uh the

product-minded engineer. I have a blog

post called the product-minded engineer.

Talk to product managers. Uh and you

know just understand how the business

works. It it is more important and try

to become a domain expert. Uh try to

become this industry insider. If you are

working in agriculture company,

understand the agriculture because

there's a lot of software engineers but

there's very few who have talked with

farmers. If you're working at an

automotive company, talk with the

mechanical engineers as well. Again, if

you build that domain expertise outside

of software engineering, you will be in

demand the next time your company is

does either downsizing or you want to

move elsewhere.

If you are engineering leaders, my

advice to you, you need to be hands-on

or you need to stay hands-on. Some of

you will think, uh, not again, yes,

again, otherwise you will be out this

time. And it is easier to do this with

AI. You can turn to AI to explain stuff

for you. You can you can start to to

contribute stuff. I'm hearing at

companies where the top of the top

hundred committers, five are uh are

product managers and so on or or

engineering leaders. And also you can

just help integrate AI into the systems

level. That removes friction

except you will be doing less people

management. You will and the business

expects you to do less of it. If you

love doing people management,

either you know either you burn yourself

out or or you will do less of it. And if

you're an engineer, if you're a

developer, you will get less career

support. Also, we're probably going to

less pay rises and some of those things

for a while. But again, it's just we

will have less management with all the

good and and all all the bad parts of

it. Finally, I I'll close with this. The

change I I I talked with Martin Fowler,

I talked with Grady Bush, I talked with

all these people. They all said change

has never been this fast in the software

industry since the 60s easily in in in

12 months. We've had AI go mainstream

across coding tools. If you are

overwhelmed, absolutely okay. A lot of

us are overwhelmed. I I was overwhelmed.

Sometimes I still am overwhelmed with

with how fast this change and how not

predictable it is. But from just time

time to time, pat yourself on the back.

You are keeping up. It's hard.

Look around. just stop for a little bit

and make a change. How can I make this

more sustainable? How can I produce more

quality? How can I stop do how can auto

automate some of these things? And then

rinse and repeat.

Gerge Oros everybody.