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samdjstephens commented on The port I couldn't ship   ammil.industries/the-port... · Posted by u/cjlm
gortok · 5 days ago
While there's not a lot of meat on the bone for this post, one section of it reflects the overall problem with the idea of Claude-as-everything:

> I spent weeks casually trying to replicate what took years to build. My inability to assess the complexity of the source material was matched by the inability of the models to understand what it was generating.

When the trough of disillusionment hits, I anticipate this will become collective wisdom, and we'll tailor LLMs to the subset of uses where they can be more helpful than hurtful. Until then, we'll try to use AI to replace in weeks what took us years to build.

samdjstephens · 5 days ago
If LLMs stopped improving today I’m sure you would be correct- as it is I think it’s very hard to predict what the future holds and where the advancements take us.

I don’t see a particularly good reason why LLMs wouldn’t be able to do most programming tasks, with the limitation being our ability to specify the problem sufficiently well.

samdjstephens commented on Tiny electric motor can produce more than 1,000 horsepower   supercarblondie.com/elect... · Posted by u/chris_overseas
fainpul · 2 months ago
> 59kW/kg

At this point why don't we get rid of the k prefix and write 59W/g?

Edit:

I was half joking, but various answers mention kW being standard for motors, kg being the SI unit for mass etc. All true, but as used here in a combined unit, which means "power density" it still would make sense IMO. It's not like the "59" tells you that it's a strong motor and hence you want kW to compare it to other motors. You can't, it's just a ratio (power to weigth). W/g just reads much nicer in my head. Or we could come up with a name, like for other units. Let's call it "fainpul" (short fp) for example :)

59 fp is a new record for electric motors!

samdjstephens · 2 months ago
kg is the SI unit for mass, I think that would be why
samdjstephens commented on Claude Skills are awesome, maybe a bigger deal than MCP   simonwillison.net/2025/Oc... · Posted by u/weinzierl
samdjstephens · 2 months ago
It seems to me that MCP and Skills are solving 2 different problems and provide solutions that compliment each other quite nicely.

MCP is about integration of external systems and services. Skills are about context management - providing context on demand.

As Simon mentions, one issue with MCP is token use. Skills seem like a straightforward way to manage that problem: just put the MCP tools list inside a skill where they use no tokens until required.

samdjstephens commented on OpenAI reaches agreement to buy Windsurf for $3B   bloomberg.com/news/articl... · Posted by u/swyx
lolinder · 8 months ago
> Looking for a moat in the technology is always a bit of a trap - it’s in the traction, the brand awareness, the user data etc.

Traction, brand awareness, and user data do not favor Windsurf over GitHub Copilot. The few of us who follow all the new developments are aware that Windsurf has been roughly leading the pack in terms of capabilities, but do not underestimate the power of being bundled into both VS Code and GitHub by default. Everyone else is an upstart by comparison and needs some form of edge to make up for it, and without a moat it will be very hard for them to maintain their edge long enough to beat GitHub's dominance.

samdjstephens · 8 months ago
Definitely take that point. But this valuation is perhaps more about how much that traction, brand and data is worth to OpenAI, who cannot buy Copilot. $3bn doesn’t seem so disproportionate in that context especially given the amount of money being attracted to the space.
samdjstephens commented on OpenAI reaches agreement to buy Windsurf for $3B   bloomberg.com/news/articl... · Posted by u/swyx
retornam · 8 months ago
I'm skeptical about this VSCode fork commanding a $3 billion valuation when it depends on API services it doesn't own. What's their moat here?

For comparison, JetBrains generates over $400 million in annual revenue and is valued around $7 billion. They've built proprietary technology and deep expertise in that market over decades.

If AI (terminology aside) replaces many professional software engineers and programmers like some of its fierce advocates say it would, wouldn't their potential customer base shrink?

Professionals typically drive enterprise revenue, while hobbyists—who might become the primary users—generally don't support the same business model or spending levels.

What am I missing here?

samdjstephens · 8 months ago
Just consider what it fundamentally is: a company at the leading edge of a product category that has found absurdly strong technology/use-case fit, and is growing insanely fast.

Looking for a moat in the technology is always a bit of a trap - it’s in the traction, the brand awareness, the user data etc.

samdjstephens commented on DeepSeek-R1   github.com/deepseek-ai/De... · Posted by u/meetpateltech
widdershins · a year ago
Yeesh, that shows a pretty comprehensive dearth of humour in the model. It did a decent examination of characteristics that might form the components of a joke, but completely failed to actually construct one.

I couldn't see a single idea or wordplay that actually made sense or elicited anything like a chuckle. The model _nearly_ got there with 'krill' and 'kill', but failed to actually make the pun that it had already identified.

samdjstephens · a year ago
Yeah it's very interesting... It appears to lead itself astray: the way it looks at several situational characteristics, gives each a "throw-away" example, only to then mushing all those examples together to make a joke seems to be it's downfall in this particular case.

Also I can't help but think that if it had written out a few example jokes about animals rather than simply "thinking" about jokes, it might have come up with something better

samdjstephens commented on TSMC's Arizona Plant to Start Making Advanced Chips   spectrum.ieee.org/tsmc-ar... · Posted by u/rbanffy
ksec · a year ago
I just want to add the term "ADVANCED" in terms of foundry node now has an official meaning anything sub 7nm. With specific rules in place in terms of export especially to China. This was a reference from ASML presentation not so long ago.

It is also important to point out, the achievement here is how fast TSMC manage to set things up and running even without the home ground advantage. Intel couldn't even replicate this time frame if it was their Intel 7nm Fab. And of course the greatest record was that with enough planning and permission done before hand TSMC manage to have the fab built and running within 18 months in Taiwan. ( Arguably closer to 12 months )

This also means unless a miracle happen or US Gov being unfair with certain things the chances of Intel catching up with its current team, management, board members and investors, against TSMC in terms of capacity, price, and lead time as a foundry is close to zero. ( I am sorry but I lost all faith and hope now Pat Gelsinger is out. )

Once TSMC 2nm hits the ground later this year, TSMC US will also start their 3nm work if they haven't started now.

samdjstephens · a year ago
It’s about demand isn’t it? TSMC have red hot demand, it’s not hard to understand their urgency in setting up new fabs, wherever they may be. Intel don’t have the same incentive - their incentive is to take the money (because, why wouldn’t you), build newer fabs and hope for some breakthrough in demand. The urgency is not there: being complete before there is demand could be detrimental
samdjstephens commented on Building Effective "Agents"   anthropic.com/research/bu... · Posted by u/jascha_eng
brotchie · a year ago
Have been building agents for past 2 years, my tl;dr is that:

Agents are Interfaces, Not Implementations

The current zeitgeist seems to think of agents as passthrough agents: e.g. a lite wrapper around a core that's almost 100% a LLM.

The most effective agents I've seen, and have built, are largely traditional software engineering with a sprinkling of LLM calls for "LLM hard" problems. LLM hard problems are problems that can ONLY be solved by application of an LLM (creative writing, text synthesis, intelligent decision making). Leave all the problems that are amenable to decades of software engineering best practice to good old deterministic code.

I've been calling system like this "Transitional Software Design." That is, they're mostly a traditional software application under the hood (deterministic, well structured code, separation of concerns) with judicious use of LLMs where required.

Ultimately, users care about what the agent does, not how it does it.

The biggest differentiator I've seen between agents that work and get adoption, and those that are eternally in a demo phase, is related to the cardinality of the state space the agent is operating in. Too many folks try and "boil the ocean" and try and implement a generic purpose capability: e.g. Generate Python code to do something, or synthesizing SQL based on natural language.

The projects I've seen that work really focus on reducing the state space of agent decision making down to the smallest possible set that delivers user value.

e.g. Rather than generating arbitrary SQL, work out a set of ~20 SQL templates that are hyper-specific to the business problem you're solving. Parameterize them with the options for select, filter, group by, order by, and the subset of aggregate operations that are relevant. Then let the agent chose the right template + parameters from a relatively small finite set of options.

^^^ the delta in agent quality between "boiling the ocean" vs "agent's free choice over a small state space" is night and day. It lets you deploy early, deliver value, and start getting user feedback.

Building Transitional Software Systems:

  1. Deeply understand the domain and CUJs,
  2. Segment out the system into "problems that traditional software is good at solving" and "LLM-hard problems",
  3. For the LLM hard problems, work out the smallest possible state space of decision making,
  4. Build the system, and get users using it,
  5. Gradually expand the state space as feedback flows in from users.

samdjstephens · a year ago
There’ll always be an advantage for those who understand the problem they’re solving for sure.

The balance of traditional software components and LLM driven components in a system is an interesting topic - I wonder how the capabilities of future generations of foundation model will change that?

samdjstephens commented on Trunk-based development vs. long-lived feature branches   ardalis.com/trunk-based-d... · Posted by u/freedude
tsak · 2 years ago
You can have both. Some bigger features can take a while to complete and you can keep the pain to a minimum be rebasing your feature branch on the latest mainline branch often.
samdjstephens · 2 years ago
Sure, if there’s only one long lived large feature branch and everything else is trunk-based style development.

If another large feature branch is merged then your regular rebase turns into a horror-merge.

samdjstephens commented on Yak Shaving: A Short Lesson on Staying Focused (2018)   americanexpress.io/yak-sh... · Posted by u/thunderbong
samdjstephens · 3 years ago
If you follow the authors advice to its logical conclusion then all changes to the code base are narrowly focussed tweaks - where does the longer term thinking come into this?

If I’m implementing a new feature, should I also disregard the need for refactoring?

A more nuanced approach is needed. You need to learn when to make changes additively and when to reshape the code to fit your new use case (and how much reshaping is required).

As an aside: I think tech debt sprints (if needed regularly) are often a sign that you aren’t developing software sustainably day to day.

u/samdjstephens

KarmaCake day49April 13, 2016View Original