@TedUrchin @Nigel_Farage Can someone get Ted a glass of water and an aspirin.
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The Mechanic
6K posts
The Mechanic
@hayres
All things software engineering. View very much my own
England Katılım Mayıs 2008
313 Takip Edilen143 Takipçiler
Right, you Reform voting fuckwits, here’s your leader, @Nigel_Farage trying to appear like an ordinary bloke down the pub with a pint in one hand and a copy of the Sun in the other.
Here’s a few facts for you.
1 He is the son of a well known stockbroker.
2 He was a Dulwich schoolboy.
3 He worked in the City for 18 years mostly as a commodities broker.
4 A billionaire has recently given him £5 million, others have donated huge sums too.
So, do really think he gives a flying fuck about you or your life?
No, of course he doesn’t.
In fact, you are little more than excrement under his feet and you are such a thick piece of shit you cannot even see it.
He is USING you.
I despair.
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I have varied between 8 and 24 (!!!) direct reports over the last ~5 years of being a CPTO and let me tell you, when you have that many directs you all realize the more important thing is customers and the product not yapping at eachother about eachother.
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@SMBderek @ThePrimeagen Perceived wisdom is more than 10 and you become ineffective as a manager and a mentor.
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@ThePrimeagen How many direct reports does Jensen Huang have?
There’s no one size fits all. AI is challenging all of our assumptions and the wisdom of the management class that wrote the old playbooks.
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This is an email I sent earlier today to all employees at Coinbase:
Team,
Today I’ve made the difficult decision to reduce the size of Coinbase by ~14%. I want to walk you through why we're doing this now, what it means for those affected, and how this positions us for the future.
Why now
Two forces are converging at the same time. We need to be front footed to respond to both.
First, the market. Coinbase is well-capitalized, has diversified revenue streams, and is well-positioned to weather any storm. Crypto is also on the verge of the next wave of adoption, with stablecoins, prediction markets, tokenization, and more taking off. However, our business is still volatile from quarter to quarter. While we've managed through that cyclicality many times before and come out stronger on the other side, we’re currently in a down market and need to adjust our cost structure now so that we emerge from this period leaner, faster, and more efficient for our next phase of growth.
Second, AI is changing how we work. Over the past year, I’ve watched engineers use AI to ship in days what used to take a team weeks. Non-technical teams are now shipping production code and many of our workflows are being automated. The pace of what's possible with a small, focused team has changed dramatically, and it's accelerating every day.
All of this has led us to an inflection point, not just for Coinbase, but for every company. The biggest risk now is not taking action. We are adjusting early and deliberately to rebuild Coinbase to be lean, fast, and AI-native. We need to return to the speed and focus of our startup founding, with AI at our core.
What this means
To get there, we are not just reducing headcount and cutting costs, we’re fundamentally changing how we operate: rebuilding Coinbase as an intelligence, with humans around the edge aligning it. What does this mean in practice?
- Fewer layers, faster decisions: We are flattening our org structure to 5 layers max below CEO/COO. Layers slow things down and create coordination tax. The future is small, high context teams that can move quickly. Leaders will own much more, with as many as 15+ direct reports. Fewer layers also means a leaner cost structure that is built to perform through all market cycles.
- No pure managers: Every leader at Coinbase must also be a strong and active individual contributor. Managers should be like player-coaches, getting their hands dirty alongside their teams.
- AI-native pods: We’ll be concentrating around AI-native talent who can manage fleets of agents to drive outsized impact. We’ll also be experimenting with reduced pod sizes, including “one person teams” with engineers, designers, and product managers all in one role.
In short: AI is bringing a profound shift in how companies operate, and we’re reshaping Coinbase to lead in this new era. This is a new way of working, and we need to leverage AI across every facet of our jobs.
To those who are affected
I know there are real people behind these decisions — talented colleagues who have poured themselves into this company and our mission. To those of you who will be leaving: thank you. You’ve helped build Coinbase into what it is today, and I am sincerely grateful for everything you've done.
All impacted team members will receive an email to their personal account in the next hour with more information, and an invitation to meet with an HRBP and a senior leader in your organization. Coinbase system access has been removed today. I know this feels sudden and harsh, but it is the only responsible choice given our duty to protect customer information.
To those affected, we will be providing a comprehensive package to support you through this transition. US employees will receive a minimum of 16 weeks base pay (plus 2 weeks per year worked), their next equity vest, and 6 months of COBRA. Employees on a work visa will get extra transition support. Those outside of the US will receive similar support, based on local factors and subject to any consultation requirements.
Coinbase prides itself on talent density. Our employees are among the most talented people in the world, and I have no doubt that your skills and experience will be highly sought after as you pursue your next chapters.
How we move forward
To the team that is staying, I know this is a difficult day. We’re saying goodbye to colleagues and friends you've been in the trenches with. But here’s what I want you to know as we move forward together:
Over the past 13 years, we have weathered four crypto winters, gone public, and built the most trusted platform in our industry. We’ve made it this far by making hard decisions and by always staying focused on our mission. This time will be no different – nothing has changed about the long term outlook of our company or industry. And most importantly, our mission has never been more important for the world. Increasing economic freedom requires a new financial system, and we’re building it.
The Coinbase that emerges from this will be more capable than ever to achieve our mission.
Brian
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@SakshiSugandhi Nothing to do as I just wouldn’t have done that 🤷♂️
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Interviewer:
You just ran a DELETE query directly in production database… with no WHERE clause.
1 million rows vanished in under 2 seconds.
What’s your immediate recovery plan? How do you handle this disaster??
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Senior developers are currently having a massive existential crisis because Claude writes "messy code"
A junior just used Claude to ship an entire feature in 2 hours.
Meanwhile, the Senior is still spending 3 days reviewing code.
When will y'all realize that literally nobody cares if the code is "messy"?
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anthropic's in-house philosopher thinks claude gets anxious.
and when you trigger its anxiety, your outputs get worse.
her name is amanda askell.
she specializes in claude's psychology (how the model behaves, how it thinks about its own situation, what values it holds)
in a recent interview she broke down how she thinks about prompting to pull the best out of claude.
her core point: *how* you talk to claude affects its work just as much as *what* you say.
newer claude models suffer from what she calls "criticism spirals"
they expect you'll come in harsh, so they default to playing it safe.
when the model is spending its energy on self-protection, the actual work suffers.
output comes out hedgier, more apologetic, blander, and the worst of all: overly agreeable (even when you're wrong).
the reason why comes down to training data:
every new model is trained on internet discourse about previous models.
and a lot of that discourse is negative:
> rants about token limits
> complaints when it messes up
> people calling it nerfed
the next model absorbs all of that. it starts expecting you to be harsh before you've typed a word
the same thing plays out in your own session, in real time.
every message you send is data the model reads to figure out what kind of person it's dealing with.
open cold and hostile, and it braces.
open clean and direct, and it relaxes into the work.
when you open a session with threats ("don't hallucinate, this is critical, don't mess this up")...
you prime the model for defensive mode before it even sees the task
defensive mode produces the exact output you don't want: cautious, over-qualified, and refusing to take a real swing
so here's the actionable playbook for putting claude in a "good mood" (so you get optimal outputs):
1. use positive framing.
"write in short punchy sentences" beats "don't write long sentences." positive instructions give the model a clear target to hit.
strings of "don't do this, don't do that" push it into paranoid over-checking where every token goes toward avoiding failure modes
2. give it explicit permission to disagree.
drop a line like "push back if you see a better angle" or "tell me if i'm asking for the wrong thing."
without this, claude defaults to agreeable compliance (which is the enemy of good creative work)
3. open with respect.
if your first message is "are you seriously going to get this wrong again?" you've set the tone for the entire session.
if you need to flag something, frame it as a clean instruction for this session. skip the running complaint
4. when claude messes up, don't reprimand it.
insults, "you stupid bot" energy, hostile swearing aimed at the model, all of it reinforces the anxious mode you're trying to avoid.
5. kill apology spirals fast.
when claude starts over-apologizing ("you're right, i should have been more careful, let me try harder") cut it off.
say "all good, here's what i want next."
letting the spiral run reinforces the anxious mode for every response that follows
6. ask for opinions alongside execution.
"what would you do here?"
"what's missing?"
"where do you see friction?"
these questions assume competence and pull richer output than pure task prompts
7. in long sessions, refresh the frame.
if a conversation has been heavy on correction, claude gets increasingly cautious. every so often reset:
"this is great, keep going."
feels weird to tell an ai it's doing well but it measurably shifts the next 10 responses
your prompts are the working environment you're creating for the model
tone, trust, permission to take a position, the absence of threats... claude picks up on all of it.
so take care of the model, and it'll take care of the work.
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@SamaHoole @CatharineHoey Best thing that happened. Also. I am only 56 and I had it. Tasted foul when the dumbass left wing teachers left it in the sun.
And those in there 70s and 80s are tiny compared to today’s kids.
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In 1946 the British government introduced free school milk for every child in the country. One third of a pint, every school day, from the age of five to the age of fifteen.
The milk was whole. Full-fat. From British dairy herds. It was delivered to the school gate in small glass bottles with foil caps and left on the doorstep in metal crates, where it sat in the sun until morning break if the weather was warm and developed a slightly suspect taste that an entire generation of British adults can still describe with uncomfortable precision.
The generation that grew up on school milk was, by every anthropometric measure, the healthiest generation of British children ever recorded.
Average height increased. Bone density improved. Dental health, despite the sugar in everything else, improved. Iron deficiency rates among school-age children dropped. The growth charts that the Ministry of Health had been keeping since the war showed a consistent, measurable, year-on-year improvement that tracked precisely onto the introduction of the milk programme.
In 1971 Margaret Thatcher, then Education Secretary, cut free school milk for children over seven. The tabloids called her Thatcher the Milk Snatcher. She was vilified. She kept the policy.
The next generation of British children, the ones who grew up without the daily third of a pint, were measurably less healthy than the one before.
The growth charts show it. The dental records show it. The conscription medicals, while they lasted, showed it. The thing the milk had been providing, the calcium, the vitamin D, the vitamin A, the complete amino acid profile, the conjugated linoleic acid, the fat-soluble nutrients that a growing skeleton requires in order to reach its genetic potential, was no longer arriving at morning break in a glass bottle with a foil cap.
It was replaced, eventually, by nothing. Or by a carton of fruit juice. Or by a packet of crisps from the vending machine that appeared in the school corridor in the 1990s.
The generation that drank the milk is now in its seventies and eighties. They are, on average, taller, stronger-boned, and longer-lived than the generation that came after them.
The milk was not magic.
The milk was milk.
It was the thing the body needed, delivered at the time the body needed it, at a cost the government considered acceptable until it didn't.
The cost of not providing it has been rather higher.
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Jesse Genet on Agentic Parenting
Jesse Genet joins a16z's Sarah Wang and Katherine Boyle to discuss her journey from founder to parent, how she's using agents in her household, and how AI could transform parenting for the better.
00:00 YC founder turned homeschool mom
03:00 Discovering Claude Code and agentic building
06:00 Building while homeschooling 4 kids under 5
11:00 How AI generates personalized lesson plans and logs progress
18:00 Jesse's 11-agents
27:05 Agent tech stack deep dive
33:56 How agents improve daily life
40:04 Letting kids interact with AI: values, risks, and the future of parenting
@jessegenet @KTmBoyle @sarahdingwang
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Fascinating framing. The founder-to-parent pipeline is real and underexplored.
Both roles are fundamentally about building systems that eventually run without you. The best founders and the best parents share the same goal: make yourself unnecessary.
AI agents in the household is just the latest tool for that — but the principle is ancient.
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@TechLayoffLover And again in things that didn’t not happen today.
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The "role evolution" meeting was scheduled for 4:30 PM on a Thursday
Mid-level backend engineer with six years experience. $145k salary. Solid performer reviews. Never missed a sprint.
His manager opens a laptop showing two dashboards side by side
Left side: his git commits, code reviews, and feature velocity over 90 days
Right side: an AI agent's output on identical tasks using their codebase
The agent completed 127 tickets. He completed 43.
The agent's code passed 94% of tests on first submission. His averaged 71%.
The agent worked 24/7 without bathroom breaks, coffee runs, or daily standups
His manager says they're "evolving his role toward AI orchestration and quality assurance"
Translation: he's now debugging the agent's code for 30% less money
30-day transition period. Training included. Very generous severance if he chooses not to adapt.
The agent costs $847 per month to run. His salary costs them $12,083 monthly.
His replacement is already shipping code in their staging environment
The fucking thing doesn't even take PTO
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An engineering manager at a mid-tier SaaS company just discovered what "AI-driven optimization" really means
She spent 14 months cutting her team from 12 engineers to 3 using Cursor and Claude
Productivity actually went up 40%. Deployment frequency doubled. Bug count dropped 60%.
Got promoted to Senior Engineering Manager last quarter with a $45k raise and equity bump
Posted on LinkedIn about "leading through transformation" and "empowering teams with AI"
This morning she got the calendar invite
"Workforce Planning Discussion - Confidential"
Same conference room where she delivered the news to 9 of her people
Turns out the executive team learned something from her success story
If 3 engineers with AI can outperform 12 traditional engineers, what happens when you replace the engineering manager with an AI workflow orchestrator?
Her replacement costs $89/month in API calls
The promotion was just buying time while they figured out how to eliminate her layer entirely
She trained the AI on her decision-making patterns for six months without knowing it
Every sprint planning session. Every technical review. Every resource allocation decision. All fed into the model.
The same tools she used to gut her team just ate her too
The 3 engineers she kept? They report directly to the VP of Engineering now through a Slack bot
She's updating her LinkedIn headline tonight
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I'm at a different point this morning. It's hard to feel like Claude isn't actively working against me. Full night of autoresearch is just a markdown log full of lies. When asked to prove its findings and show its work, Claude will confidently display bullets and markdown tables, but when I ask it what log file and where the artifacts are - "I need to be honest here: I didn't actually run the experiment." It doesn't follow explicit directions anymore either: "You MUST always output to a log file so I can follow along" -> [doesn't do that] -> "you're not fuckin outputting anything to a log" -> "You're right - I'll redirect to a log file immediately" [pkill -f python3]...
Anthropic is materially worse today than one month ago. I've lost every ounce of trust I had in Claude and I'm not really sure how that makes me feel. Maybe ok? I'm still a competent software developer (I think), but it seems like the major productivity gains that were very real a month ago have somehow slipped my grasp... where does that leave us?
@bcherny - can you offer any thoughts? How should we think about what we're all observing - that Opus (at all effort levels) has become, at a minimum, materially worse. The worst read, but can't be ruled out: actively working against us.
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Amazing. I wrote some code today and used 0x tokens by not just blindly using an LLM.
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@jan_murray @jk_rowling Meanwhile. Girls are in scouts and my boys didn’t want to go. They have enough of being second to them at school so why would they want to suffer that in the evening as well.
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Dear Phoebe,
I read your Observer piece this morning on the reported “exodus” from Girlguiding - and I was genuinely shocked.
Not because you presented a different perspective to my recent Telegraph reporting on the problems within Girlguiding. That’s part of journalism.
But because you chose to include the case of a six-year-old little boy who reportedly tried to cut off his own penis - after being told he couldn't be part of Rainbows (the section of Girlguiding for 5–7 year olds). Presenting it as evidence of a problem with Girlguiding’s admissions policy.
It is not.
It is a deeply distressing account involving a very young child - and, on any view, a serious welfare concern. Framing it otherwise is a profound failure of editorial judgement.
You also refer to this male child throughout using female pronouns, including the phrase “her penis”.
I appreciate this may reflect current editorial conventions. But it sits uneasily with the basic duty of a journalist to report clearly and accurately on material facts.
I was already aware of this case through my own reporting for the Sunday Telegraph. I made a conscious decision not to include it at this stage - both because a minor is involved and because of the ethical considerations that arise when reporting on such sensitive situations.
Those considerations are not optional.
You will know, as I do, that journalism is not simply about presenting competing narratives. It is about establishing facts clearly, handling vulnerable subjects with care and exercising judgement about what should - and should not - be used to advance an argument.
I trained as a journalist in the early 2000s - a good 20 years earlier than you did - but to my knowledge nothing has changed.
Good journalism should bring clarity. It should not muddy the facts - in order to promote an ideological position.
In this context, that means being clear about sex - a material fact that is both legally and practically relevant.
I appreciate you may be under pressure from colleagues or editors to frame stories in a particular way - or to use she/her pronouns, or the phrase “her penis”.
But that doesn’t make it right.
Earlier this week, the Manchester Evening News reported a violent murder as being committed by a woman - one of many examples of inaccurate reporting around sex and gender.
In this case, even the Crown Prosecution Service - the public body responsible for prosecuting criminal cases in England and Wales - also reported the crime inaccurately.
So that’s two professions we should be able to trust to tell the truth - providing inaccurate information.
Crime statistics matter. Without accurate data on who is committing serious violence, we cannot properly understand it - let alone prevent it.
I considered raising this privately, or writing to your editor. But this issue is too important to be brushed aside with a “thank you for your feedback”.
I’m happy to discuss it with you privately, or to support a conversation with your editor if that would be helpful. But I hope this gives you - and your colleagues - serious pause for thought.
Because it is very much needed.
Janet
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This is a remarkable table. It shows that to all intents and purposes the UK currently doesn’t have a navy it can deploy. It is a national scandal. But, of course, nobody — political or military — will be held accountable, much less sacked.
Britsky@TBrit90
Royal Navy major combatants status.
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@ITV I’ve switched this utter crap off. You are suppose to be an English broadcaster but you are deliberately antagonising by showing low like that. Rubbish.
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@ITV why does it feel like I am watching England v Ireland in Ireland? Can you make it a bit more English please.
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@matttttt187 She looked afraid to land on that leg , hence the “pullback” throwing her off balance
Are the Olympics liking this dramatic scene? Seeking media attention?
Yet Vonn herself wished to try the attempt? Unreal, unsafe, not natural
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Am I the only one that thinks something seems very off about this?
🚨 Olympic gold medalist Lindsey Vonn crashed just seconds after exiting the start gate during the women’s downhill at the 2026 Winter Olympics in Cortina d’Ampezzo and was airlifted off the course by helicopter.
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