htormey

This has been down for multiple hours now. During this time we have migrated off of fly to coolify/digitalocean.

This is the second time this happened in recent months. The last straw was one of our customers reaching out and letting us know our site was down. We had paid for two machines with fly to have redundancy.

Pretty sad as apart from the outages we really liked fly. Hopefully they fix things and learn from this experience.

Pretty handy collection of prompts to do basic things with LLMs. I’ve had good results with using Claude to explain code, tag sentiment and extract emails or other specific content from free form text.

If you plan on using any of these at scale I recommend investing in a good evaluation test harness to check for regressions when you tweak prompts.

I don’t trust anecdotes on twitter because every time I’ve tried an agent that’s been hyped up it’s been more expensive and time consuming than just using GitHub co pilot with Claude/ChatGPT and putting up a PR myself.

Hence I’m skeptical of people making claims about a product I can’t try out myself. It’s unclear if the tasks they are doing and the way they are using Agents is relevant to the work I do. Which is usually working on a team of engineers shipping code on a complex code base.

For AI I tend to put a lot more weight in benchmarks, such as SWE-bench, which is why I wrote an article about:

https://www.stepchange.work/blog/why-do-ai-software-engineer...

SWE-bench is mostly small python tasks evaluated solely by unit tests which require less than 15 line changes to a single file. Most of those it fails at and the ones it gets right it ignores all sorts of libraries and conventions used in the rest of the code base.

I’m Optimistic that agents will eventually agents will improve dramatically in a few years but today Devin is not good at making larger changes that build on one another like features.

AI software engineers like Devin and SWE-agent are frequently compared to human software engineers. However SWE-bench, the benchmark upon which this comparison is made, only applies to Python tasks, most of which involve making single-file changes of 15 lines or less and relies solely on unit tests to evaluate their correctness. My aim is to give you a framework to assess if AI's progress against this benchmark is relevant to your organization's work.

This article is about Cognition Labs Devin and what’s in the benchmarks used to assess it and AI on coding tasks.

To summarize what I think the author is trying to say with this article:

1) The stock market is in a bubble due to a decade of low interest rates and tax slashing by “right wing” governments.

2) Big tech in particular has been doing well but this is not sustainable.

3) AI is in a bubble. People are pinning their hopes on it to keep tech and I presume big tech growing.

4) A bunch of references to academic papers from 2000 about why AI is hard.

5) Gen AI requires a lot of compute which generates a lot of carbon and is bad for the environment.

Thus his statement: “ I think I’m probably going to lose quite a lot of money in the next year or two. It’s partly AI’s fault, but not mostly. ”

Which I disagree with. Because A) I think in the long term (5+ years) the investment in AI will be a positive ROI. B) if the stock market crashes in the short term it’s likely going to be for non AI reasons. 3) His arguments as to why AI isn’t going to pan out long term are a bit weak.

Having lived in the Bay Area for over 13 year's, I’ve seen a few cycles: social, mobile, cloud, gig economy etc.

The cycle pattern is always the same: a) a big new exciting tech idea comes along. b) investors pile in money. c) 95% or more of the companies they invest in go bust and if the space has legs some companies do really well.

How is this any different with the current wave of AI companies?

Today the big winners in AI are the incumbents, some examples:

Microsoft: is making money being the hyperscaler of choice for AI companies (on prem ChatGPT, mistral, etc), it’s co pilot lines and enterprise subscription products.

Nvidia is making bank being the current standard on which all of these companies run their models. They have some recent competition from Groq but are still likely going to be crushing it for the next year or two. Mainly due to precommits from the hyperscaleralers.

Meta: seem to have been able to leverage AI to claw back advertising revenue due to Apples crack down by improving targeting.

As someone who has raised venture capital to do an AI startup I’d say yes there is a lot of hype in this space. Yes a lot of these startups are going to go out of business but it’s also early days.

I also think working AI into this poorly written article about how the stock market is going to crash is a bit of stretch.

I’m concerned about a market crash myself but I am more worried about it being caused by a combo of a) the upcoming US election. B) the war in the Ukraine. C) conflict with Iran. D) interest rates in the USA being high.

Personally I don’t believe theirs a conspiracy regarding this but just to play devils advocate.

Clearly, the heads of HR and other people who define corporate compensation talk to one another, “hey what are you guys doing to manage pay cuts, reductions in staff, etc in this economy at company x/y/z”.

It’s a pretty obvious benefit of having a strong professional network. I.e you have people you can ask for mentorship and advise. Every startup board was asking companies to belt tighten and reduce costs because of the economy earlier this year and last year.

A relatively small number of companies and startups in tech define top of market for compensation. Clearly the people at those companies know one another and talk about what they are doing.

Yeah, on point observation. I worked at both companies. I left Apple to work at Facebook because I wanted to be able to participate in open source projects and talk about my work with my coworkers openly.

I disagree, I don’t think this is just about adoption curves and hype cycles.

I think fundamentally the infrastructure required to build decentralized applications is hard and has pushed the limits of computer science (zero knowledge proofs etc).

I think people have inflated expectations about how long it will take this technology to mature. Today it’s still very technically hard to build a scalable dapp that’s easy to use. Assuming this is something consumers actually want as opposed to a solution in search of a problem, this will take more time to solve.

Sometimes greed makes people think a technology is a lot further along than it actually is.

I don’t think comparing the timelines of vastly different technologies like this is helpful.

Prior to the web, in the 1960s/1970s we had packet-switching networks, such as ARPANET which were the basis of modern computer networking.

The original ARPANET (precursor to the internet)was just used to connect computers at research institutions. I.e it wasn’t used by that many people relatively speaking.

It took another 20 years for the web to come along and more for it gain widespread adoption.

Is Bitcoin, a very low level protocol, more analogous to ARPANET or the web? Even if you dislike crypto, is this comparison really helpful?

All technology is built on the shoulders of previous giants. Building a secure, scalable, sufficiently decentralized distributed computer system is hard. I.e it’s going to take a long ass time. Hence I’m not surprised at how far we have come since BTC was released.

After Microsoft swapped out the CEO. New guys better than Balmer.

“You're inside a bubble though. The 100 MAU is certainly totally misleading, maybe 1/10 of that in reality, and something that's only out for a few months can easily rollercoaster up and down as people try it once for novelty and then forget it.”

What’a your basis for saying this is misleading and doubting that figure?

Anecdotal friend groups aside, if their was no user traction, they wouldn’t be getting a ten billion dollar investment from MSFT.

Their growth in web traffic is also pretty impressive:

https://www.similarweb.com/blog/insights/ai-news/chatgpt-bin...

In my personal and professional life I’ve been using it every day and happily pay $20 for premium. It has replaced google for me for a huge variety of queries.

I disagree. ChatGPT reached 100 million MAUs 2 months after launch. It’s one of the fastest-growing consumer applications in history.

Anecdotally, lots of my non technical friends (and me) are using it for everything from cooking to learning a foreign language.

Lots of my technical friends are using it for side projects on the weekends. I’d say it’s the top new technology all of them are working with or incorporating into their workflows.

I and all of my teammates are using it to help us write sql and answer basic programming questions.

It’s clearly a way bigger deal than VR right now.

The problem here seems to be that Snap rammed this feature into their product in a really awkward fashion that doesn’t make sense for their users. Hence the backlash.

source: https://arstechnica.com/information-technology/2023/02/chatg...

Coinbase is fully remote, i.e no local talent pool dependency, with no expectation of coming into the office, can hire from anywhere in the USA and still it mainly hires people in those locations.

It's not the only remote company where I've noticed this happening.

The Bay Area usually commands a premium because a) quality of talent b) the ability to scale out a team.

Quality of talent means not only intelligence and skill but also people who have spent years working on the specific thing you are building (hardware/firmware, AI, at scale codebases or services).

If you assume that timezone matter and relevant experience working in large orgs is important, the Bay Area premium will continue for the foreseeable future.

Scale means you can hire 100-200 talented IC's within a year that meet the quality of talent criteria and have experience working and getting things done in larger orgs, the ability to do so also commands a premium.

Only a few other places in the USA have this scale, i.e New York and Seattle.

Coinbase the company I work for is fully remote and does salary bands by location. Within the USA, Seattle/New York and the Bay Area all are in the same top tier band. Also, the majority of our USA engineering workforce is still based in these hubs despite being fully remote for nearly 2 years. I don't expect this trend to change any time soon.

Agreed re this taking longer to play out than expected. My frame of reference is 2008, which felt like it happened really fast.

This seems to be more of slow role out in stages. I could totally see this taking another quarter or two before it hits earnings in a big way.

This is why I still think we are early on with tech stock corrections. I.e current P/E ratios assume that past earnings are still accurate.

Specifically apart from rising rates I would expect this to eventually hit public company earnings in a big way and hence prompt more layoffs in public/private tech.

Last earnings season didn’t see much of an impact. We are a couple of weeks out from earnings, I wonder if this or the next quarter will be where we will see more layoffs and the tech jobs market generally tighten?

Network states are online communities that have collective agency (governance of some kind) that eventually try to materialize on land in the physical world. A DAO, could potentially become a network state but it could also in theory emerge from a subreddit or some other online community organized around a specific thing.

Balaji has a particular vision for these network states that sees cryptocurrency as being an integral part of them. It also presupposes that these network states need to have a moral imperative to be long lasting (I.e a strong purpose like a religious community, being against the FDA, dietary etc)

An important point to note is that a network state is not inherently a “right wing” or libertarian idea. In fact Vitalik references another more left leaning author, David de Ugarte, who explores similar ideas from a different perspective in his book Phyles: Economic Democracy in the Twenty First Century.

It’s entirely possible to disagree with many of Balaji’s previous positions and see this as a useful playbook for implementing a network state that aligns with your world views.

A large part of his book seems to be laying out a justification for this vision as well as it’s theoretical underpinnings. I.e why this needs to exist and why this would be better than say moving to an existing city state etc.

Apart from that it’s basically a playbook for how a community could in theory go from lose collection of individuals on discords to a mini city with its own regulations and laws.

Vitalik is sympathetic to much of the book but calls out 4 main issues he has with it:

1)The "founder" thing - why do network states need a recognized founder to be so central?

2)What if network states end up only serving the wealthy?

3)"Exit" alone is not sufficient to stabilize global politics. So if exit is everyone's first choice, what happens?

4)What about global negative externalities more generally?

Of these critiques the ones that resonated with me so far are 2 and 4. I’m only about 25% through his book. In terms of 4, I think this exists today with nation states and hence I think it’s a little unfair to expect this to be addressed in this book.

In terms of 2. I think this book is written for middle class and wealthy people who can easily move cities and or countries. I.e software engineers and scientists.

A big question for me is, assuming network states are a thing that happen and are wide spread. What happens to all the displaced unskilled or semi skilled global poor? What will their likely relationships be with these new network states?

How do millions of people displaced by wars like in Syria or the Ukraine fit into or impact this network state model? People who are forced to exit as opposed to having the luxury of choosing to exit. This seems like a bit of a blind spot if even from just a network state game theory perspective.

In general I’m enjoying this book so far and would recommend people read it if they are interested in subjects like charter cities or DAOs.

I treat it as a thought provoking work that’s not mean spirited in tone like the sovereign individual.

Within my lifetime I expect to see people try and create new charter cities bootstrapped from online communities. I think this book offers a lot of useful advice on how to think about forming these communities.

The big missing piece of this article is a sense of at what scale and why should a startup decide to invest in a piece of infrastructure like Kubernetes.

The author mentions other things he considers red flags such as using a different language for backend and frontend development with no additional context.

Is the author talking about a startup in the context of one person who just knows JavaScript working on their own building a prototype? Is he talking about a series B company with 500k MAUs?

Some additional context would improve the article a lot. I think the author should have had a few people read over the article and given feedback before publication.

Scenario I’m worried about: inflation continues, rates keep increasing and this to impact public company earnings.

In an effort to mitigate this, companies will cut costs by firing people, slowing hiring and cutting services and advertising.

This will then impact private companies ability to raise.

Nah, I disagree. I work in crypto (coinbase) and was working in tech in the Bay Area in 2008.

As of today, many crypto companies have money from 2021/early 2022 raises and are still hiring. In 2008 the private tech market reaction to the stock market crash was swift and brutal.

It was really hard to get a job in 2008. Today it feels like their is a big lag between stock pullbacks and jobs drying up. None of my colleagues who were laid off are having trouble getting jobs in crypto and have options in other parts of tech if they want it.

To be clear I expect the jobs situation to get worse this year and in 2023.

All this panic about tech layoffs seems a little premature given we haven’t even begun to see the impact of rates hikes on quarterly earnings yet. Many companies still have open recs and budgets to keep hiring.

I work at a company that just laid off 18% of the workforce (Coinbase) including many people in engineering. The day this happened my email, LinkedIn, Twitter inboxes exploded with companies asking me if I knew of anyone looking for a job or if I myself had been impacted.

I reached out to many of my former colleagues who had been impacted to see if they needed help. All had multiple interviews in flight and were not having trouble finding jobs.

Aside from many crypto companies the inbound jobs were from many public and private companies and spanned many industries.

I expect tech layoffs to get worse and the white collar job market to tighten towards the end of this year and 2023.

I expect the main driver for this will be cost reduction at public and private companies in the lead up to earnings or quarterly reports. Main cost for a tech company obviously being labor.

Care to give some specific examples?

Flexibility is what keeps software engineering salaries going up. Over the course of my career I’ve done firmware, desktop software, mobile and web development for a variety of industries. All on the back of a 4 year computer science degree.

Example industries I’ve worked in: pro audio(Avid), consumer hardware (Apple), social networks (Facebook), medical marijuana, education, crypto currency (Coinbase).

My work has impacted tens of millions of people and generated massive revenues for the companies I’ve worked for.

Sadly Chemical engineers and pharmacists are very specialized jobs that often require masters degrees and hence don’t have the same career flexibility.

This friction in career switching combined with the cost of education in the USA is a big problem. Their are few professions that offer the same bang for your buck as software engineering. We are a very privileged and lucky group of people.

Totally accurate and valuable information based on people in my network.

You can make a lot of money working as a staff engineer at a top tier company.

It’s a bit pedantic to be honest. Multiple times it’s been pointed out on this thread that the OP was referring to total comp so I’m not sure why this keeps being brought up.

While equity in a public company can go down and go down significantly it’s liquid. Especially in companies like coinbase that don’t have a 1 year cliff, are public, it’s a significant part of your comp and not funny money like you get in many early stage companies.

The OP is confused, I work at coinbase and that figure refers to total comp. Also levels.fyi is listing salary and not total comp for the google position he is comparing.

"Perhaps because the company lost half a billion dollars last quarter and is in a controversial space facing regulatory scrutiny?"

Wouldn't you expect people to be paid more for working in a risky space? Also, please not Coinbase just announced a hiring freeze.

https://blog.coinbase.com/employee-note-an-update-on-hiring-...

"I asked what the role was in the comment you are replying to. Do you have data to back up the "huge swath" assertion? Certainly there are a few individual companies that have been able to provide specialized roles a $380k base salary, and companies who have been able to provide that and above on total comp thanks to an amazing run on equity value over the past 10 years. I don't think anyone is arguing that there are situations when this happens, that's not the point. It's irregular, it's naive to think that is the norm."

It's basically what the salary looks like in the USA at a top tier company in a top tier city. Go look at https://www.levels.fyi/ for base salary excluding equity. Equity goes up by level.

As for this role, it sounds basically like a mid career engineers salary. i.e 5-12 years of relevant experience. Hard to know exactly because geography impacts salary bands at Coin.

I can't remember what HR tells us, but I think we are targeting pay for the top 25% of companies/engineers in the USA.

"The OP specified salary- if they're referring to total comp, that'd be an important distinction for them to make in the future."

I work at Coinbase, it's not salary, it's total comp. I'm assuming the OP was a bit confused. At least half that figure is equity.

"Its anybodies guess what the actual value of equity in a total comp package will be a year from now. As an example, if you took a $380k TC package at Shopify 6 months ago and 40% of that was equity, it's now looking like $280k."

As I mentioned earlier, each year Coinbase give you a new equity grant priced at the start of the year. I.e thirty day average, I believe.

So if the equity tanks one year, the next year you will be reset to 380k total comp. Assuming of course we are not in a multi year bear market and you don't get laid off, which is always a possibility in tech.

Also some companies, such as Netflix allow you to take a cash only salary that would be comparable to this.

No you are incorrect. That 224k is base at google not including equity. Staff engineers at google get a bonus and the majority of their comp is in equity, just like coin.

Source, I have a lot of friends who are former/current staff engineers at a variety of Bay Area companies. I also was a staff engineer at coin.

Also if you want to earn something like this in cash go work at Netflix when they start hiring again. They give you the option to be paid in cash.