Techbromancer

Putting the romance back into computing

[Techbromancer @techbromancer]

Techbros really need to take art classes because theres a really bad lack of imagination

[Techbromancer @techbromancer]

New definition of midlife crisis just dropped

[Deedy @deedydas]

The vibes in SF feel pretty frenetic right now. The divide in outcomes is the worst I've ever seen.

Over the last 5yrs, a group of ~10k people - employees at Anthropic, OpenAI, xAI, Nvidia, Meta TBD, founders - have hit retirement wealth of well above $20M (back of the envelope AI estimation).

Everyone outside that group feels like they can work their well-paying (but <$500k) job for their whole life and never get there.

Worse yet, layoffs are in full swing. Many software engineers feel like their life's skill is no longer useful. The day to day role of most jobs has changed overnight with AI.

As a result,
1. The corporate ladder looks like the wrong building to climb.
Everyone's trying to align with a new set of career "paths": should I be a founder? Is it too late to join Anthropic / OpenAI? should I get into AI? what company stock will 10x next? People are demanding higher salaries and switching jobs more and more.

2. There’s a deep malaise about work (and its future).
Why even work at all for “peanuts”? Will my job even exist in a few years? Many feel helpless. You hear the “permanent underclass” conversation a lot, esp from young people. It's hard to focus on doing good work when you think "man, if I joined Anthropic 2yrs ago, I could retire"

3. The mid to late middle managers feel paralyzed.
Many have families and don't feel like they have the energy or network to just "start a company". They don't particularly have any AI skills. They see the writing on the wall: middle management is being hollowed out in many companies.

4. The rich aren’t particularly happy either.
No one is shedding tears for them (and rightfully so). But those who have "made it" experience a profound lack of purpose too. Some have gone from <$150k to >$50M in a few years with no ramp. It flips your life plans upside down. For some, comparison is the thief of joy. For some, they escape to NYC to "live life". For others still, they start companies "just cuz", often to win status points. They never imagined that by age 30, they'd be set. I once asked a post-economic founder friend why they didn't just sell the co and they said "and do what? right now, everyone wants to talk to me. if i sell, I will only have money."

I understand that many reading this scoff at the champagne problems of the valley. Society is warped in this tech bubble. What is often well-off anywhere else in the world is bang average here.

Unlike many other places, tenure, intelligence and hard work can be loosely correlated with outcomes in the Bay. Living through a societally transformative gold rush in that environment can be paralyzing. "Am I in the right place? Should I move? Is there time still left? Am I gonna make it?" It psychologically torments many who have moved here in search of "success".

Ironically, a frequent side effect of this torment is to spin up the very products making everyone rich in hopes that you too can vibecode your path to economic enlightenment.

[prayingforexits 🏴‍☠️ @mrexits]

Vibe coded my first project today!

Let me know what you guys think ❤️

[Collin Rugg @CollinRugg]

NEW: 50 empty Waymos invade Atlanta neighborhoods and circle their cul-de-sacs for hours early in the mornings.

Residents say they are getting waymo traffic than usual and have tried combating the cars with a neon green sign, which only made the problem worse.

The Waymos didn't know what to do and clogged the entire street.

"We have small animals and pets, got kids getting on the bus in the morning, and it just doesn’t feel safe to have that traffic," one resident said.

The residents say Waymo has not given them a response yet.

[tmuxvim @tmuxvim]

I put a prompt injection into my LinkedIn bio and recruiters are messaging me in Old English and calling me Lord.

[Techbromancer @techbromancer]

watching @MarcusJHutchins explain his exploit pipeline makes you realize how much hype the frontier models have

https://t.co/jFqEWMzPLR

[Techbromancer @techbromancer]

Infosec Thread:

[Techbromancer @techbromancer]

somber "amazing person has bad disease" day to all those who mourn

real sorry @KentBeck :( , this new hits me. I only started real swe after decades of toil when I digest your TDD book cover to cover. you still matter, ur work matters more than ever

https://t.co/vOD6lFecKc

[Techbromancer @techbromancer]

@theo in other news, water is wet

[Techbromancer @techbromancer]

&gt; when did you realize you're creating monopoly?

Monopoly is just a game, senator. I'm trying to control
the fucking world.

[PC Gamer @pcgamer]

A new California law says all operating systems, including Linux, need to have some form of age verification at account setup https://t.co/9qPq8EhtO4

[Techbromancer @techbromancer]

the tarball is ready to play if you cant find it through you package manager

[Techbromancer @techbromancer]

A AI in development thread:

[Techbromancer @techbromancer]

nice FOSS, local, cross platform, speech-to-text software:

https://t.co/o2fQHlINeR

[Techbromancer @techbromancer]

we'll know agi is here when every desktop app isnt running on javascript

[Techbromancer @techbromancer]

https://t.co/4rzy35hX4P

[BURKOV @burkov]

LLMs process text from left to right — each token can only look back at what came before it, never forward. This means that when you write a long prompt with context at the beginning and a question at the end, the model answers the question having "seen" the context, but the context tokens were generated without any awareness of what question was coming. This asymmetry is a basic structural property of how these models work.

The paper asks what happens if you just send the prompt twice in a row, so that every part of the input gets a second pass where it can attend to every other part. The answer is that accuracy goes up across seven different benchmarks and seven different models (from the Gemini, ChatGPT, Claude, and DeepSeek series of LLMs), with no increase in the length of the model's output and no meaningful increase in response time — because processing the input is done in parallel by the hardware anyway.

There are no new losses to compute, no finetuning, no clever prompt engineering beyond the repetition itself.

The gap between this technique and doing nothing is sometimes small, sometimes large (one model went from 21% to 97% on a task involving finding a name in a list). If you are thinking about how to get better results from these models without paying for longer outputs or slower responses, that's a fairly concrete and low-effort finding.

Read with AI tutor: https://t.co/MipHHO6rjX

Get the PDF: https://t.co/XQrqiaGwIO

[Techbromancer @techbromancer]

it's all fun an games til the corporate waterfall-encouched-in-scrum-types discover there's this thing called "Large Language Models" and then start writing tickets that are a mile long and make no sense

in the future it'll be slop talking to slop

☹️🔫

[Context Engineering Guild of New York City @ContextGuildNYC]

Meetup tonight @ 19:00 🤖 🦞 🔨

[Techbromancer @techbromancer]

@KentBeck * harder to get the AI to care about simplicity.

* Interesting Appendix section to steal from for .MD files, event for SDD tools

[Techbromancer @techbromancer]

@KentBeck * when building your coding process w/ AI, slow its cycles down so you can verify steps along the way. You can refine prompts &amp; .MD files along the way

* warning signs AI gone off track: Loops; Unrequested functionality, even if reasonable; cheating (eg disabling/deleting tests)