Bo George

Dad, husband, dork, consultant, problem solver

[dax @thdxr]

anyone talking about their custom setups to make ai more effective isn't doing anything useful

coding used to be manual labor. typing the code out, doing large changes, jumping between files. a fancy, bespoke setup could make a difference

but it's not like that anymore, you have a magic box you can say stuff into and things happen

people haven't understood this, they're still spending their energy tinkering with what's behind the box. the underlying tone is always frustration. they're clearly not happy and maybe even on a burn out path

the best people at this are doing the best work of their life all while happier than ever they could do this even on a vanilla setup

the box can already do amazing things. it can even produce the best code of your life. it's limited entirely by the person using it and their creativity and their ambition

and you're not gonna get that in a skill file

[Founder Mode @Founder_Mode_]

Marc Andreessen worked at IBM at the peak of their power.

There were 12 layers of management between him as an intern and the CEO.

He describes what that meant: if one layer lies to the layer above it, maybe that's okay. Two or three layers, the lies compound. Six layers, they really compound.

Twelve layers... The CEO has absolutely no idea what's happening inside his own company.

IBM even had a name for it. They called it the Big Gray Cloud, the cloud of men in gray suits that followed the CEO everywhere and made it physically impossible for him to ever talk to someone actually doing the work.

"It was like a visit from the king. The king and the traveling court. A completely impervious bubble."

That company controlled 80% of tech.

Then it didn't.

Elon looked at that model and built the opposite.

The most dangerous thing in a large organization isn't incompetence.

It's the distance between the truth and the top.

[Peter Steinberger 🦞 @steipete]

This guy emailed me asking for a *token session refund* because his claw made mistakes. 🙃

[Adam Rackis @AdamRackis]

When your drug dealer complains you’re not doing enough drugs

[Antoine v.d. SwiftLee  @twannl]

The biggest lie in agentic development:

"Run 4 agents on 4 projects at once."

I built this animation to show why that fails.

Focus on 1 project → 4/4 tasks done
Context switch between 4 → 0/4 tasks done

Same time. Different results.

[dax @thdxr]

sent this to the team today

everything great comes from being able to delay gratification for as long as possible

and it feels like we're collectively losing our ability to do that

[Mo @atmoio]

I was a 10x engineer. Now I'm useless.

[Thariq @trq212]

https://t.co/nKTDfC7zMm

[first check $500k-1M pre-seed @ajhodls]

a whole new generation of developers is about to discover the difference between creating software and maintaining software

[IT Unprofessional @it_unprofession]

Our intern just asked me why we don't use Kubernetes.

I said because we don't need Kubernetes.

He said everyone uses Kubernetes.

I said everyone TALKS about using Kubernetes. Most companies are running Docker containers on three servers and calling it a day.

We have 40 employees. Our entire infrastructure runs on AWS with auto-scaling groups. It works fine.

Kubernetes is designed for companies running thousands of services across hundreds of servers. We have twelve services.

But he read that Kubernetes is "industry standard" so now he thinks we're behind.

This is what happens when people learn from tech Twitter instead of actual experience.

They think every company is Google-scale and needs Google-scale solutions.

We don't need Kubernetes. We need our MySQL database to stop running out of connections because someone wrote a query that doesn't close properly.

But that's not exciting. Nobody writes blog posts about "I fixed a connection leak."

They write about "How we migrated to Kubernetes and saved millions" even though the migration cost more than they saved.

I told the intern he should learn why tools exist before learning the tools themselves.

He looked disappointed. He wanted to put Kubernetes on his resume.

[dax @thdxr]

everyone's talking about their teams like they were at the peak of efficiency and bottlenecked by ability to produce code

here's what things actually look like

- your org rarely has good ideas. ideas being expensive to implement was actually helping

- majority of workers have no reason to be super motivated, they want to do their 9-5 and get back to their life

- they're not using AI to be 10x more effective they're using it to churn out their tasks with less energy spend

- the 2 people on your team that actually tried are now flattened by the slop code everyone is producing, they will quit soon

- even when you produce work faster you're still bottlenecked by bureaucracy and the dozen other realities of shipping something real

- your CFO is like what do you mean each engineer now costs $2000 extra per month in LLM bills

[Dr Milan Milanović @milan_milanovic]

Kubernetes killed more startups than server crashes ever did

You don't have Spotify's scale. You have 8 engineers and a single server that's running fine

But you watched a KubeCon talk, and now you've got 23 YAML files, a Helm chart nobody fully understands, and engineers debugging pod evictions instead of buildinga product

Your "cloud-native infrastructure" is just a cloud bill with extra complexity

A $50/month VM can handle millions of requests. Your startup will run out of money debugging networking issues long before you need horizontal pod autoscaling

The best infrastructure decision is often the simplest one

[Arpit Bhayani @arpit_bhayani]

Leadership across companies expects AI to magically cut time-to-ship in half.

Yes, AI can help engineers code faster. But coding was never the bottleneck.

The real drag is non-tech stuff - planning, periodic status updates, cross-team coordination, unclear requirements, stakeholder alignment, reviews, approvals, handoffs, deployment cycles, and on-call rotations.

Cumulatively, that's ~80% of the work.

Optimizing the remaining ~20% cannot produce a 50% reduction.

If leaders really want to see gains, they should focus less on coding velocity and more on eliminating process friction.

[Simon Willison @simonw]

I see a lot of complaints about untested AI slop in pull requests. Submitting those is a dereliction of duty as a software engineer: Your job is to deliver code you have proven to work https://t.co/Eso7BWaTtF

[Anders Hejlsberg @ahejlsberg]

Thrilled to announce... https://t.co/bC9ZVGfDco

[Bo George @bo_george]

@AWSSupport @gabceb How is people not being able to login informational and not an error?

[Bo George @bo_george]

@AWSSupport @gabceb We are seeing too many request issues for us east 1 with cognito.

[College GameDay @CollegeGameDay]

We love you, Ben ❤️

@KirkHerbstreit pays tribute to his best friend 🐶

[Sergio Pereira @SergioRocks]

No one wants to admit this, but:

- Serverless is technical debt
- Scrum is process debt
- Daily standups are communication debt
- RTO mandates are engagement debt

As with any kind of debt. These things can get you a lift on the short term, but you'll need to pay them back on the long run.