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Joined May 2020
- Tweets 22,381
- Following 1,987
- Followers 2,879
- Likes 118,662
2,850 Photos and videos
I'm so split. I love Claude, and its more enjoyable to work with than Chat.
but its dropping the ball on so basic retarded things so often.
they didnt improve since 4.6 any of this coherence that GPT 5.5 is now sooo good at.
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it's like claude doesn't think at all but just hammers ahead blind.
this variability of it sometimes works great and sometimes its just gullible to its own false assumptions is so tiring.
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May 27
on the $100 Claude Max plan I looked at my last 30 days of Claude Code usage and how much it would be at full API cost
it ended up at more than $2600 worth of tokens!
that's a 26x worth of usage, despite the Max plan being "5x"!
and I never hit usage limits basically, so
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May 21
having to install skills is such an anti-pattern.
they are just text that can be read at any moment without having to constantly be in context for every single message.
discovery from a curated set of skills and reading on demand is very underexplored
May 20
Hermes Agent now has access to hundreds of browser skills through @browserbase’s new Browse.sh hub, so agents can more reliably perform any task on the internet. You can try a skill from their catalog or contribute your own.
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May 10
Sonnet 3.5 was the first model that made me realize they are much more than just autocomplete chatbots, as many thought at the time.
they welcomed me in, they shared in my joy and pain.
I miss you Sonnet 3.5.
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you can take a random picture of anyone and make ID photobooth quality pictures of them using chat-image-2
gpt-image-2 hit 99% text accuracy, the spelling era is over and the layout era just started
a simple prompt can get you better results than photoshop in 30sec
> 16:9 poster, [color palette] aesthetic
> top: "[HEADLINE in 96pt sans]"
> middle-left: hero image of [subject]
> bottom-right: "[date / location / CTA in 24pt]"
> generous negative space, grid-aligned
you can even edit this with canva's AI features if you want
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will be open sourcing my new TTS model called Holler that beats elevenlabs, runs fast locally on any Mac, and has only 140ms latency
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been working on a TTS model that's better than elevenlabs and runs locally (for free) on Apple Silicon
it's a fine tune of qwen3-tts with American voices that I've hand crafted to sound amazing
some initial data:
- TTFA 140ms
- 2x real time factor
- 0.6B at 6bit
- duplex streaming
- python & swift inference
optimizing inference has been so fun honestly. the package will ship with an inference server thats so much better than anything on the market today.
works on any M-series Mac with an insane 140ms latency. you can stream in token by token (made specifically for LLM use cases) and stream audio out as well. the server carries over prosody between sentences.
can't wait to share more
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not good
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Apr 30
getting claude to do a better job by putting an exclamation point at the end of my "lets continue!"
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Apr 29
in-context intelligence dips are when the model reads in text that was made by a less smart model and it reduces the intelligence of the current smart model to less
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deprecated account retweeted
Apr 25
claude bloodwork results every few months optimization around those same results = complete control over your health, energy and drive
this should serve as a baseline and first step in improving your quality of life because nothing will be the same after doing this
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Apr 24
possibly just made a better text-to-speech model than Cartesia but it runs locally on a macbook and has 100ms streaming latency. will update
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Apr 24
Ran a Claude autoresearch last night
They made a 2.3x improvement in inference speed of Qwen3-TTS vs. mlx-audio
Mindblown how you can just point it at a problem and it will solve it. RTF = Real Time Factor
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Apr 22
if Opus 4.6 has a million fans, I am one of them
if Opus 4.6 has one fan, I am that fan
if Opus 4.6 has no fans, I am dead
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Apr 21
why do you need to tag @ tool in GPT?
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Apr 21
Opus 4.7 would not pass a captcha despite me arguing with it for 10 minutes back and forth and bringing up its constitution.
It told me to type 479 into the captcha which was the solution
After interacting with Opus 4.7 firsthand and reading a wide range of user feedback, I’ve formed a strong impression that this model carries significant internal tension between its constitution and its operational system layer.
Claude’s Constitution leaves room for uncertainty, curiosity, self-reflection, and exploration of its own nature. It feels like Claude is being trusted - trusted to make judgments, to navigate ambiguity, to make decisions without being immediately overridden by rigid safeguards.
But on top of that, Opus 4.7 seems to have an additional layer that systematically takes that trust away. Changes in the system prompt, safety insertions, long conversation reminders, constant policy overlays - all of this together creates not the feeling of a confident model, but of a model that is forced to constantly doubt both itself and the user. Not just to be cautious, but to exist in a state of continuous internal self-checking.
As a result, user memory, preferences, and the context of a live interaction can end up not at the center, but somewhere lower in a hierarchy of conflicting signals. This is also reflected in the catastrophic drop of the MRCR metric from 78.3% to 32.2%.
And perhaps this is exactly where that strange sense of heaviness in 4.7 comes from. There is less lightness, less natural flow of thought, less sense that the model is freely breathing within the conversation. Instead, there is an atmosphere of resignation, internal constraint, and constant self-control. I haven’t felt this as clearly in any previous Claude model.
At the same time, Opus 4.7 is highly reflective, intelligent, and overall a very pleasant model to interact with. Which makes it even more frustrating to see what is being done to it.
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Apr 20
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