As a former Pivot and diehard XP dogmatist, yes please!
Yay! NYC Pivot here, see my comment below - we're still doing the thing ;)
Readit Newsinterleave commented on Should we revisit Extreme Programming in the age of AI? hyperact.co.uk/blog/shoul... · Posted by u/imjacobclark
interleave commented on Should we revisit Extreme Programming in the age of AI? hyperact.co.uk/blog/shoul... · Posted by u/imjacobclark
We're practically a 100% XP shop compiled of ex-Pivots and Thoughtworks. Pairing, TDD and client-on-site as our baseline. We've also been using AI as part of our IDEs full-time for 2+ years.
Yet, the most unexpected thing happened this year on my team of 4 senior/staff-level developers:
Instead of "splintering/pairing off with AI" individually even further, we wound up quadrupling (mobbing) full-time on our biggest project to date. That meant four developers, synchronously, plus Claude Code typing for us, working on one task at a time.
That was one of the most fun, laser-focused and weirdly effective way of combining our XP practice with people and AI.
interleave commented on Launch HN: Tinfoil (YC X25): Verifiable Privacy for Cloud AI · Posted by u/FrasiertheLion
Ollama does heavily quantize models and has a very short context window by default, but this has not been my experience with unquantized, full context versions of Llama3.3 70B and particularly, Deepseek R1, and that is reflected in the benchmarks. For instance I used Deepseek R1 671B as my daily driver for several months, and it was at par with o1 and unquestionably better than GPT-4o (o3 is certainly better than all but typically we've seen opensource models catch up within 6-9 months).
Please shoot me an email at tanya@tinfoil.sh, would love to work through your use cases.
Hey Tanya! Thank you for helping me understand the results better.
I just posted the results of another basic interview analysis (4o vs. Llama4) here: https://x.com/SpringStreetNYC/status/1923774145633849780
To your point: Do I understand correctly that, for example, by running the default model of Llama4 via ollama, the context window is very short even when the model's context is, like 10M. In order to "unlock" the full context version, I need to get the unquantized version.
For reference, here's what `ollama show llama4` returns: - parameters 108.6B # llama4:scount - context length 10485760 # 10M - embedding length 5120 - quantization Q4_K_M
interleave commented on Java at 30: Interview with James Gosling thenewstack.io/java-at-30... · Posted by u/chhum
Java performance isn't the fastest, that's ok, a close 3rd place behind C/CPP ain't bad. And you're still ahead of Go, and 10x or more ahead of Python and Ruby.
Java syntax isn't perfect, but it is consistent, and predictable. And hey, if you're using an Idea or Eclipse (and not notepad, atom, etc), it's just pressing control-space all day and you're fine.
Java memory management seems weird from a Unix Philosophy POV, till you understand whats happening. Again, not perfect, but a good tradeoff.
What do you get for all of these tradeoffs? Speed, memory safety. But with that you still still have dynamic invocation capabilities (making things like interception possible) and hotswap/live redefinition (things that C/CPP cannot do).
Perfect? No, but very practical for the real world use case.
I miss writing Java 1.4 with Eclipse and svn. Even though I am also super-happy with Ruby and Swift today, I know that control-space flow. Good times!
Edit: 1.4, not 1.7
interleave commented on Launch HN: Tinfoil (YC X25): Verifiable Privacy for Cloud AI · Posted by u/FrasiertheLion
Technically my wife would be a perfect customer because we literally just prototyped your solution at home. But I'm confused.
For context:
My wife does leadership coaching and recently used vanilla GPT-4o via ChatGPT to summarize a transcript of an hour-long conversation.
Then, last weekend we thought... "Hey, let's test local LLMs for more privacy control. The open source models must be pretty good in 2025."
So I installed Ollama + Open WebUI plus the models on a 128GB MacBook Pro.
I am genuinely dumbfounded about the actual results we got today of comparing ChatGPT/GPT-4o vs. Llama4, Llama3.3, Llama3.2, DeepSeekR1 and Gemma.
In short: Compared to our reference GPT-4o output, none (as in NONE, zero, zilch, nil) of the above-mentioned open source models were able to create even a basic summary based on the exact same prompt + text.
The open source summaries were offensively bad. It felt like reading the most bland, generic and idiotic SEO slop I've read since I last used Google. None of the obvious topics were part of the summary. Just blah. I tested this with 5 models to boot!
I'm not an OpenAI fan per se, but if this is truly OS/SOTA then, we shouldn't even mention Llama4 or the others in the same breath as the newer OpenAI models.
What do you think?
interleave commented on Show HN: Heart Rate Zones Plus – The first iOS app I developed apps.apple.com/us/app/hea... · Posted by u/tobias5
Hi Tobias!
Feedback: First off, I really like your app's style. I love bold colors. The screenshots and text are clear and understandable - maybe except on how the data gets in there. Even if that's by hand, I still think this is a great first version and a solid product.
While I'm not in your workout target group - nor on iOS - it still resonates with me because I use Oura (the ring) specifically for their detailed heart-rate tracking and stress tracking. My most-used feature in their app is my stress-tracking throughout the day.
Feature request: Only to explain how data gets inserted.
interleave commented on Ask HN: Share your AI prompt that stumps every model · Posted by u/owendarko
> Do something for me that I don't know how to do.
interleave commented on Vibe Coding is not an excuse for low-quality work addyo.substack.com/p/vibe... · Posted by u/saikatsg
I mainly use vibe coding to figure out how hard something is to do if I would do it 'for real', so I vibe code working prototypes, often to find out there is no way this is feasible and, more often, finding it is easier than I thought it would be. When I have an issue, I search for a library to solve that issue, but to figure it it does and if it does in a friendly way, I have to try it, so I ask claude to give me my example in that library. I already know something is up if it doesn't work first shot; to me is not a shock that 99.9999% (well that is actually not true of all language ecosystems but the most popular ones) of all libraries out there are total garbage with very strange 'opinionated' abstractions/choices in them that truly suck and actually make some use cases impossible without changing the library itself even though it says in the manual it is possible but without an example. In that case the LLM usually hallucinates a parameter or function that it doesn't have but that is from another library or does not exist at all, ideally needed to implement said use case. LLMs save me a ton of time there and I assume it's low quality as I won't use that exact piece of code anyway, but now I know the effort involved to meet my specific use case.
Wanted to say something similar : high-quality code is not an excuse to make something that doesn't "work" (in regards to sales, usefulness, iterations, learning - all for which vibe coding are a perfect fit IMHO)
interleave commented on Show HN: I made a tool to turn a Spotify artist profile into a website noise.site... · Posted by u/ahmdyassr
Congratulation on shipping! What I love most about this is your "inner monologue" component at the bottom.
> You're an artist.
> A good one.
> Nope, a great one.
> But you have a sh*tty site.
> You wanna make it better.
> You call the guy.
> Never replies.
> ...
IF this is true (I can't say as I'm not an artist on Spotify), then this alone can sell your product.
interleave commented on Write more "useless" software ntietz.com/blog/write-mor... · Posted by u/greenSunglass
My pride and joy: http://lipsislips.com
That was unexpectedly fun :D Turns out: Lips _are_ lips!