> I’ve been running Kimi K3 alongside Claude on my normal coding work, and for all practical purposes I can’t tell them apart.
If the author is here, I'm curious what this means. How are they running Kimi K3? Are they using pi, opencode, claude, codex, or kimi-cli? Is speed a concern?
Without knowing how the comparisons are being made, it's hard to agree that one can't notice the difference. I do.
I’m curious, shouldn’t Mythos have discovered this? At this point, based on all the marketing from Anthropic, I’d expect all software from them to be flawless given all the capabilities Mythos possesses.
PDFs are both awesome and terrible at the same time. I've seen screenshots of emails added to pdfs alongside tables that span multiple pages. Because you can do almost anything and guarantee that it'll look the same regardless of how or where it's viewed is a big selling point for a lot of businesses. It's this flexibility (i say madness) that makes PDFs notorious, and why some labs have document parsing as a leading product (see https://mistral.ai/news/ocr-4/).
I'll be using it tonight but grudgingly so. Grudgingly because after July 7th, I'm not going to all of a sudden, start paying API prices (and maybe that's the problem) when I'm used to a subscription that gives me multiples in comparative value. Perhaps this is the fabled "token economics will come for everyone this year" that I've been reading about? In any case, I'll use the hell out of it to extract as much as I can, then back to the trusted partners Opus 4.6 and Sonnet 4.6 (for however long they remain available).
It’s the thousand cuts problem. Look at the stories over the past couple of weeks: silent downgrades that they then walked back, billing errors with claude code, highly sensitive classifiers that made it impossible to do simple things (I asked a few botany questions and my very long chat got lobotomized), and several more. The ban is only part of it. It’s the whole rollout and the fact that it won’t be available in subscriptions in a week or two.
I just finished reading Incorruptible and a central theme (Anthropic is a case study) is that trust is singularly the most important currency a business has. The past few weeks have done wonders for Anthropic’s marketing but just as much if not more damage to the trust factor. Businesses will continue to use Anthropic because it’s the default and accessible where it matters (AWS, Azure, GCP, Databricks, Snowflake, etc). But the trust factor has dropped. It’ll be interesting to see if they can turn the tide. Maybe Fable will be too awesome for people to care about the past few weeks?
These style of comparisons are decent at showing capability but they don't really show me what I truly want - a sounding board and implementer with senior engineer-level execution. When I look back at all the teams that I've been part of, the best outcomes came from white-boarding (sometimes in the metaphorical sense) with one or two people, at times arguing, then finally compromising on a plan. Instead of synthetic benchmarks that try to be objective, I wonder if there's a way test this, or maybe I'm opining on a way of working that will soon be gone?
> Work that introduces new methods, highly creative ideas, or solutions that have not been used or experienced before. More generally, an approach that introduces an innovative strategy to solve a complex problem.
Something that I've been thinking about for the past year or so is coming to grips with the fact that the vast majority (anecdote) of software engineering work is not novel (and maybe that's okay). Few opportunities lend themselves to doing truly novel work. Other than infrastructure work and highly specialized software, pause and ask yourself when you last encountered software were you said "how the hell did they do that?" or "damn, that's nice" (for me, the most recent was Ghostty). I think much of the angst that people have when they fear for their job is coming to the realization that LLMs can do most of the "standard" work that a lot of highly compensated individuals currently do. We've built livelihoods around this and the threat of that coming to an end is genuinely frightening.
We use Jira. We're trapped by the processes built around it. Once it's entrenched, it's rather difficult to remove. I eagerly await for something that can replace Jira, but fear that it too will be bastardized to fit the process for however long the process lives.
I'm curious whether this is due to their insistence on using home grown tools ie, Kiro and not Codex/Cursor/Claude et all? I tried Kiro and quickly left.
I've largely found codex and claude code to be about the same however, codex tends to "think" harder and for longer which depending on the task, yields better results without too much steering.
On an unrelated note, UI is such a personal preference that it's impossible, beyond core pillars that have been studied for decades, to say one is better over the other. That being said, I like OpenAI's design system much better than Anthropic. OpenAI products (cli and chat ui) "feel" nice and consumer focused whereas Anthropic's products feel utilitarian and "designed for business".
It's hard to take the author seriously when this immediately follows the post. I can only conclude that this post was for the views not anything to learn from or be concerned about.
Most of what I've been reading on either side of the argument is reductive. It's possible to have a take based on one's perspective and experience but it's impossible (at this time) to generalize things more broadly. I think what most people feel is multi-faceted: efficiency expectations from "leaders", job change inevitability (perceived or real), economic impact (should things not go well), loss of identity (am I a programmer, engineer, manager of things?), and several others. The discussions on the multiplicative effect of LLMs are being framed as a false dichotomy when it's far more complicated and nuanced.
Life is stressful (in some respects, overly so), but we’ve dealt with this for millennia by having a strong support system. Not to be reductive over the multitudes of problems people face today, but most can and should be solvable by having a good support system. Family and good friends with whom you can speak frankly can do wonders. It doesn’t solve the affordability or job problems, but having someone to talk to, someone that you can trust and has lived experience, can go a long way. I can’t tell you how many times I’ve solved “problems” or at least lessened their impact, by consulting family and friends.
I always find this characterization baffling. Why does it matter if it's a 24 year-old vs 30, 35, or 50? Many aspects of life that we hold near and dear were created by very "young" people.
I just want whoever is next in line to make Siri perform reliably and consistently. Not 70% of the time of even 90% of the time, 100% of the time for the limited uses cases that most (perhaps just me?) people use it for:
- Call "person"
- Call "business" (please don't say "I don't see so and so in your contacts" and on a second try, work)
- Find "place" (while driving)
- Define "phrase or word" (please don't say I found this on the web)
- Set a timer or alarm
- Check the messages (in a sane way)
- Set reminders (this one surprisingly works well)
- Use intents correctly (I just want to be able to say "play 99% invisible in Overcast")
It doesn't need to do all the fancy things they show-cased last year. It just needs to do the basics really well and build from there.
An underrated and oft understated rule is always have backups, and if you're paranoid enough, backups of backups (I use Time Machine and Backblaze). There should be absolutely no reason why deleting files should be a catastrophic issue for anyone in this space. Perhaps you lose a couple of hours restoring files, but the response to that should be "Let me try a different approach". Yes, it's caveat emptor and all, but these companies should be emphasizing backups. Hell, it can be shovelware for the uninitiated but at least users will be reminded.
If the author is here, I'm curious what this means. How are they running Kimi K3? Are they using pi, opencode, claude, codex, or kimi-cli? Is speed a concern?
Without knowing how the comparisons are being made, it's hard to agree that one can't notice the difference. I do.