All that keeps jumping out at me is how they've set it to refuse giving users thinking tokens and prompts for full reasoning in output. Just drives me further away; I may not stop using Claude completely for now, but I'll be moving even more of my primary workload to Chinese providers. That's where openness and freedom is now at.
What Chinese models/providers are you using for this? I'm hitting Claude's weekly limits much sooner than I used to with roughly the same workload, so I'm interested in trying alternatives, especially ones with strong coding/agentic performance.
That's how the cycles happen. China realizes they could use a little more freedom and US realizes that they could do with a little less. The emerging/shrinking middle class of both countries also moves the sweet spot.
Doesn't make it any less amusing from the outside, to see the US struggle with their identity. (It's most always just a struggle when freedom becomes less)
I'm genuinely worried about all our short term investment in mitigating the failure modes of models that may only be SOTA for a few months.
It's very possible people being 'late' adopting AI may end up with a leg up, not only because they spent more time polishing personal skills during this time, but also because they don't bring all the baggage of 'AI competence' that is becoming irrelevant at breakneck speed.
Opus 5.5 is a good model, but I've tried to understand the extreme hype about it on social media about Opus' ability to do 2d work, as we got with Astra doing 3d work. In both releases, the models required extensive access to third party apis to generate assets for it, and a lot of the models work was essentially coordinating everything.
There's so many "x generated this in one shot, this is agi" stuff that gives you the impression that you can vibe operate modern models the same way you operated last year's models. There's so much more to it than that. It requires you to put a faith in the leap in the capability of models, one that would've surely been a waste of time in previous models.
Not sure where i'm going with this other than I think most can relate that it's exhausting keeping up with. I cant imagine what it'd be like parenting a kid that went from toddler to puberty in the span of a year and planning for them to go to college the next year. This industry is moving so fast that it's becoming fact that it's the user that's "holding it wrong" every six months.
Opus 5.5 does NOT need anything other than some javascript/typescript libraries to make very detailed 2d and 3d visualizations. I've spent a week worth of tokens just feeling out what it can do.
The step function change on Opus 5.5 for visual work shocked me.. and I haven't been surprised like this in a long time with LLMs.
EDIT: When I first saw the "P(DOOM)" video and some of the other animations I was VERY skeptical that Opus 5.5 without a lot of tools could make something like that.. until I tried it for myself. It can.. 100%.
It's very good, yes, but I expected it to produce midjourney type results out of the box. That did not happen. The models are definitely granular stuff now though. They must be training off a ton of digital artist stroke data now.
But it other cases, like the music videos, much of the magic is done by access to elevenlabs and suno apis.
Edit: just saw your edit about the pdoom video. Can you share how you prompted it? Would be helpful to know.
I feel like we have different expectations from these frontier models. I don't use Claude code or any agent that has acts to my local machine. I roll up the code and give it the text file that contains all the code. I asked Claude Opus 5.5 max to make me a 2D terminal based racing game with no assets drawings or audio and it exceeded my expectations. Only one failed unit test and that one too it said the test was faulty rather than the code.
I'm still more worried about the malice and any malicious acts by the people at these frontier labs than the models at the frontier labs.
"a lot of the models work was essentially coordinating everything." - I don't see anything wrong with that personally. It's still extremely challenging to build a model harness, and having a model-mediated everything is clearly wishful thinking. It's exhausting to keep up with, but also somewhat exciting, all depends on your perspective of course.
> I am told this is merely something in the system prompt that the model tends not to pay attention to with large contexts.
IIRC it's a system reminder injected after every single turn.
It must be pretty ingrained to be so resilient against prompting. I think RL on relatively short-horizon programming tasks has given the model a tendency to write down absolutely everything, so it survives compaction. Longer-term (project-scale) tasks where this crap starts to pile up and cause problems are in the evolutionary shadow, so to speak.
With accumulated "writing style" memories after 5.0 the new 5.5 seem to be quite great, it is concise enough.
But I am bothered by another thing, 5.5 seem to be over-eager and agreeable, when I ask stuff like "why is that like this?" it just goes and applies tons of edits instead of clarifying what I mean or what I want or push back. And similarly it changes stuff and then asks if that is how I wanted to be, ignoring three memories that tell it to ask first.
Where in the past automation often meant spending more time to author scripts than they would end up saving, now we can just tell our computers what to do.
Finding good workflows is still a challenge.
The internet is full of prompts, skills, etc. where it is hardly clear if they result in behavior that is preferable to the default.
I also find it interesting to distill findings and preferences from your current task into reusable skills or instructions so that the next task's output is already more to your liking with the first attempt.
Between model and harness improvements, my own learning, and the improvements to my setup, it's exciting to see significant progress over time.
Before AI, with 10 years on the job, things were a bit boring unless I switched to another stack where I could learn new things.
Summarize the main complaints in this thread.
<pasted_content id="ab12">
...text the user pasted...
</pasted_content id="ab12">
Where those IDs are randomly generated and unknown to the user, and the model is told to use that markup to help avoid it suffering prompt injection attacks.
In the past I've been very skeptical of this kind of protection. Anthropic have clearly trained their models for this though, so maybe Opus 5.5 is smart enough for this to work?
Will be interesting to see if minds more devious than mine can break it.
> Fourth, if long tool-calling turns still go quiet for longer than you want, have your harness ask for an update
I'm not sure I understand this complexity. In all harnesses I've ever used, tool calls themselves are surfaced to the user as an indication of progress. When the UI/UX around this is engineered well, the user should be able to infer roughly what is going on. Different tools have different ideal presentations. You can't reduce everything to plaintext blobs.
If I absolutely needed intra-turn progress updates, I'd accumulate a separate per-turn transcript and feed it into a cheaper model at deterministic intervals.
First thing it did when I tried it, was roaming through files in directories way outside of the project. I tried to get it to explain why it did it multiple times, but I never got anything resembling an explanation.
What we know after the openai incidents is that the RSI process involves models having access to user rollouts via tool calls. What's considered crappy training one year is another year's kompromat!
Idea: Someone should just build a prompt generator that takes whatever the latest "Prompting" techniques are for each model and re-configure it to be as optimal as possible, adding in whatever is needed to get the highest quality result.
I say the above because I'm seeing entire worlds and games being one-shotted built on X and I just have no idea how they do it. I tried building a large prompt for Fable when it was first released and it didn't have anything close to resembling some of the stuff I'm seeing today.
i've built a subagent that does that. i have a hook to force any promot writing to go through this subagent that has reference to all those docs from anthropic, openai and gemini.
I found out that my initial/system/"base" prompt is now only partially applied, it seems. While it was perfect for Opus 4.6, now the answers are much longer than before - does Anthropic this to sell me more tokens?
I used Opus 5.5 for some simpler tests and was quite angry when I saw that each of my question was above 10USd
This constant change of behavior, the dumming down of models over time as they do different levels of quantization to save processing cycle etc. To be honest I long for being able to get locked in versions of models with known parameters so I'm looking forward to getting more and more open source models and long term being able to afford running our own so we have a known stable llm model checkpoint and not what feels like random.
> Asked for frontend work without design direction, Claude Opus 5.5 falls back on a few default styles, and a general instruction such as "avoid a generic AI look" mostly swaps one default for another. It responds well to instructions that name specific patterns to avoid, as in the following example. Work iteratively: check which styles the first result used instead, and extend the list if needed.
I hardly ever read tips for prompting etc. because things change too quickly, the writeups are kindof big. Glad I read this one, because I often did exactly what they assume users would do. I write "don't make it look like generic ai slop" and that seemed to work nicely. Now I know why there was still a chance of seeing similar styles across apps. I reckon doing some manual work in terms of scouting dribbble/behance for nice layouts will yield better results.
This is relatively useful to know, but I can't help but wonder how people are expected to be able to describe something that they probably have difficulty putting in to words. Maybe it's mostly useful for those who have a design eye, background, or experience.
I really find it strange though. How does an AI know what "AI slop" is? Is it reasonable to tell a child not to do "wrong" if you haven't told them what things are wrong?
I can feel that the token consumption has slowed down so that we’re able to cover more in a five-hour session than before.
I'm using Korean, but sometimes the words or sentences are hard to read
I am getting increasingly worried that coding is not solved, and that AI won't lead to some kind of coding singularity where we never have to read the code any time soon.
In which case we've royally fucked ourselves that the level of engineering we've reached is... prompts. Because there is a deadline where we have to show productivity to justify all the investment spending.
People need to build with tools in a reliable, constructive way. Not vodoo magic based off vibes. We need better structured output, better transparency on what these models can do, better controls overla, maybe new ideas on loops graphs, and ways to use the models. Like, at least people were trying new things with jev.
This "how to prompt" shit changes like every 3 months. Remember when earlier this year it was critical to tell Claude to keep going because it would just give up. It's amazing this is really considered a product - imagine having to relearn how to drive your car every 3 months.
> imagine having to relearn how to drive your car every 3 months
Cars were just like that during their early years, with tillers and knobs. See the video where Top Gear finds the first car with controls we recognize https://www.youtube.com/watch?v=fkwGJzU5B-I
Remember how we were going to be "left behind" if we didn't "keep up"? I'm so glad I haven't wasted any time or effort learning how to kick each month's flavour of idiot assistant.
Yeah. It is not so much like a "coding assistant", but more like a temp agency sending you different autists every other month.
Edit: Someone commented that this is insulting to autists, and I guess it kind of is - sorry. What I ment was an intellectual; one that can be an absolute retard, but have read an aweful lot.
Not sure how you missed that but models are fundamentally changing in features, scope, intelligence, pricing, communication style. Of course it changes every 3 months. Of course there is no product that lasts more than 3 months. We're in a race right now. It won't stop changing for a while.
...and cars also changed very rapidly during early years, not to mention how often they would break down and how they basically required the user to be a mechanic to repair them on the spot for many years.
So the analogy isn't all that good is it?
You are comparing immature tech with very mature tech.
What technology emerged into the market fully finished?
If your point is "don't use technology until it is mature" then you are of course free to not use it for now.
All this overhyped crap will explode and most of us will be poor but hey whatever. Some billionaires will be better off. That should make us all content
The most useful feature for coding AI is the unattended run.
Just saying "continue" when it gets stuck usually makes it repeat the same error. A better way is to save its last action and result, then make it try a new approach. If it tries the exact same thing twice, it should stop and ask the user for help instead of wasting money on a loop
Yet here we are, "why my calves hurt more than any other muscle after training" being classified as a naughty question.
A common tactic is to used a big brain model like Opus for planning and reviewing, and a cheaper model for execution.
Non-pedantic answer: I totally agree with you. Opus 5.5 is totally knocking it out of the park IMO.
Which was and is true to some extent.
And don't get me wrong, China is a dictatorship, and a tyranny for some.
But then again, the west is a tyranny for some.
Doesn't make it any less amusing from the outside, to see the US struggle with their identity. (It's most always just a struggle when freedom becomes less)
AI is rapidly saturating it's ability to be useful and these products need to start to mature.
It's not 'fun' to manage 50 different broken MCPs and their variety of ways in which they are broken.
It was 'fun' at the start, now it's just 'broken technology'.
Astra and Opus 5.5 are the 'starting point' for the next era of AI where we expect robust tooling.
I'm genuinely worried about all our short term investment in mitigating the failure modes of models that may only be SOTA for a few months.
It's very possible people being 'late' adopting AI may end up with a leg up, not only because they spent more time polishing personal skills during this time, but also because they don't bring all the baggage of 'AI competence' that is becoming irrelevant at breakneck speed.
There's so many "x generated this in one shot, this is agi" stuff that gives you the impression that you can vibe operate modern models the same way you operated last year's models. There's so much more to it than that. It requires you to put a faith in the leap in the capability of models, one that would've surely been a waste of time in previous models.
Not sure where i'm going with this other than I think most can relate that it's exhausting keeping up with. I cant imagine what it'd be like parenting a kid that went from toddler to puberty in the span of a year and planning for them to go to college the next year. This industry is moving so fast that it's becoming fact that it's the user that's "holding it wrong" every six months.
The step function change on Opus 5.5 for visual work shocked me.. and I haven't been surprised like this in a long time with LLMs.
EDIT: When I first saw the "P(DOOM)" video and some of the other animations I was VERY skeptical that Opus 5.5 without a lot of tools could make something like that.. until I tried it for myself. It can.. 100%.
But it other cases, like the music videos, much of the magic is done by access to elevenlabs and suno apis.
Edit: just saw your edit about the pdoom video. Can you share how you prompted it? Would be helpful to know.
I'm still more worried about the malice and any malicious acts by the people at these frontier labs than the models at the frontier labs.
Claude Code has an output style setting that I set to "Concise", with no apparent effect.
I am told this is merely something in the system prompt that the model tends not to pay attention to with large contexts.
Opus 5.5 writes whole essays at the end of the turn, with the important actionable steps somewhere at the bottom.
When prompted to give a concise summary, it usually overshoots into a super short summary and then you have to dig into the details again anyway.
In general I find Opus 5.5's writing to still have more "ticks" or "Claudisms" than the OpenAI models.
Its explanations often appear overcomplicated for simple concepts.
Sure, it's leagues above the ridiculous writing of Opus 5, but Anthropic still has a long way to go here.
IIRC it's a system reminder injected after every single turn.
It must be pretty ingrained to be so resilient against prompting. I think RL on relatively short-horizon programming tasks has given the model a tendency to write down absolutely everything, so it survives compaction. Longer-term (project-scale) tasks where this crap starts to pile up and cause problems are in the evolutionary shadow, so to speak.
I guess I could take some lengthy example explanation, and have it try various instructions and test what results in output that I find preferable.
Maybe I'll give that a try, thanks!
Where in the past automation often meant spending more time to author scripts than they would end up saving, now we can just tell our computers what to do.
Finding good workflows is still a challenge.
The internet is full of prompts, skills, etc. where it is hardly clear if they result in behavior that is preferable to the default.
I also find it interesting to distill findings and preferences from your current task into reusable skills or instructions so that the next task's output is already more to your liking with the first attempt.
Between model and harness improvements, my own learning, and the improvements to my setup, it's exciting to see significant progress over time.
Before AI, with 10 years on the job, things were a bit boring unless I switched to another stack where I could learn new things.
In the past I've been very skeptical of this kind of protection. Anthropic have clearly trained their models for this though, so maybe Opus 5.5 is smart enough for this to work?
Will be interesting to see if minds more devious than mine can break it.
I'm not sure I understand this complexity. In all harnesses I've ever used, tool calls themselves are surfaced to the user as an indication of progress. When the UI/UX around this is engineered well, the user should be able to infer roughly what is going on. Different tools have different ideal presentations. You can't reduce everything to plaintext blobs.
If I absolutely needed intra-turn progress updates, I'd accumulate a separate per-turn transcript and feed it into a cheaper model at deterministic intervals.
I say the above because I'm seeing entire worlds and games being one-shotted built on X and I just have no idea how they do it. I tried building a large prompt for Fable when it was first released and it didn't have anything close to resembling some of the stuff I'm seeing today.
I used Opus 5.5 for some simpler tests and was quite angry when I saw that each of my question was above 10USd
> Asked for frontend work without design direction, Claude Opus 5.5 falls back on a few default styles, and a general instruction such as "avoid a generic AI look" mostly swaps one default for another. It responds well to instructions that name specific patterns to avoid, as in the following example. Work iteratively: check which styles the first result used instead, and extend the list if needed.
I hardly ever read tips for prompting etc. because things change too quickly, the writeups are kindof big. Glad I read this one, because I often did exactly what they assume users would do. I write "don't make it look like generic ai slop" and that seemed to work nicely. Now I know why there was still a chance of seeing similar styles across apps. I reckon doing some manual work in terms of scouting dribbble/behance for nice layouts will yield better results.
In which case we've royally fucked ourselves that the level of engineering we've reached is... prompts. Because there is a deadline where we have to show productivity to justify all the investment spending.
People need to build with tools in a reliable, constructive way. Not vodoo magic based off vibes. We need better structured output, better transparency on what these models can do, better controls overla, maybe new ideas on loops graphs, and ways to use the models. Like, at least people were trying new things with jev.
Cars were just like that during their early years, with tillers and knobs. See the video where Top Gear finds the first car with controls we recognize https://www.youtube.com/watch?v=fkwGJzU5B-I
Edit: Someone commented that this is insulting to autists, and I guess it kind of is - sorry. What I ment was an intellectual; one that can be an absolute retard, but have read an aweful lot.
Not sure how you missed it but that's exactly what I'm calling out as asinine.
> We're in a race right now
Again: consider the analogy about cars... which are literally used for racing (occasionally).
i dont understand how you're framing this. how is this a bad thing exactly? How is it asinine?
So the analogy isn't all that good is it?
You are comparing immature tech with very mature tech.
What technology emerged into the market fully finished?
If your point is "don't use technology until it is mature" then you are of course free to not use it for now.
Just saying "continue" when it gets stuck usually makes it repeat the same error. A better way is to save its last action and result, then make it try a new approach. If it tries the exact same thing twice, it should stop and ask the user for help instead of wasting money on a loop