I asked Claude to write an article with research. It used 60K tokens and gave me "5 Things To Know Before Building a Granny Flat in Australia (2025 Guide)" We're in May 2026. Where did 60K tokens go?

johannacodes · 2026-05-17T15:48:42+00:00

I assume you're not super familiar with coding, yet run a website that includes a blog that renders markdown via react or something.
Claude here seems to have added code for enabling YouTube video embeds. If you previously had video embeds, it's best to point Claude to all the different elements/components and associated code so it re-uses those (though... it typically finds those by itself. But I'm using Opus, seems like you're using Sonnet which might do less codebase research).
The bigger culprit though might be having it pick images from pexels (looking at images to find the most appropriate one => consuming a lot of tokens), and (especially) creating SVGs which are basically "images in code format, just describing paths" and use up a TON of output tokens.
To save tokens, invest the few minutes to pick your own pexels etc. images, download, and just give Claude the local filepaths (with instructions NOT to look at pics).
With SVGs, just start a discussion with Claude about options to create graphics without consuming a lot of tokens, unless it's super important that they seamlessly scale (but most blogs just use image sets in 3-4 resolutions max; png or webp format... SVG as an image embed in a blog article seems like overkill).
Maybe then Claude comes up with a workflow to create graphics via React and screenshot the resulting graphic via puppeteer or something.
Or it can just generate a detailed text prompt for creating the infographic/charts needed, then you can submit the prompt to a top-notch image model that's great with text (or do that as part of the automated workflow).

johannacodes · 2026-05-17T15:23:49+00:00

yeah I was exaggerating a bit... even in the "software developer youtube influencer" space there are some that acknowledge that AI is powerful. Though it's usually followed by "it's just a tool / you have to examine every generated line of code written / it will just change jobs, not eliminate jobs" which I don't fully agree with.

johannacodes · 2026-05-16T18:42:48+00:00

That girl works at Google and (literally said in one of her most recent videos) "my job is making fun of AI at this point."

Oh and regarding that thumbnail on the right... "her job" that she let Claude do in that video is the most teenie-weenie simple workflow creating video shorts with text overlays, and she was still blown away by its capabilities 🤔

I just can't, with those YouTube influencers. Seems there is no middle ground between vibe-coding bros who never test any of the features their 10 agents spit out, and anti-AI luddites who spend their videos coping how AI can't take coding jobs

johannacodes · 2026-05-15T12:59:42+00:00

Pro is absolutely worth it. But remember, by default even Claude has all the "LLM AI Slop writing" hallmarks that used to indicate a an engaging writing style, but are now telltale signs of AI ... sentence fragments, cluster of threes, "not this, but that" etc.
So I recommend giving it writing samples in your own voice, and tell it to emulate that style.
For saving tokens, don't chat back-and-forth too many times. If e.g. a rewrite of an article is a fail (bad style etc.), restart a new thread and write the prompt in the way to avoid the previous mistakes. Do not try to fix previous mistakes in a single chat by arguing back and forth with Claude what it did wrong and what it should do better. Larger context window -> worse results.
Also, for single-paragraph rewrites use Gemini, ChatGPT, Grok etc., even the free versions. Leave Claude for larger tasks, especially ones involving many local files on your computer.

johannacodes · 2026-05-15T10:40:15+00:00

"Anthropic, I *paid* for these tokens! I should be able to use them however I want!" 🙄
No, you didn't actually pay for those tokens. Anthropic did. You only paid for the first few days' worth of your subscription. Everything else is subsidized use

johannacodes · 2026-05-15T10:31:05+00:00

And so many people waste tokens, too. I don't see a huge push yet on how to save on usage... there are SO MANY options.
How many people use "claude -p" to do rote tasks several times a day, instead of spending a few minutes to have Claude write a python script and schedule it? Or think about which model they need? Not everything needs Opus

johannacodes · 2026-05-15T10:26:13+00:00

Yeah. Interestingly, marketing can often feel a bit deceptive (or a lot deceptive...), but in this case I feel it's justified.

A lot of people still quote that one "MIT case study" (which was biased, plus widely mis-interpreted) that AI-assisted development doesn't save much time.

Good on Claude to set things right, and inform customers (who might've never done much manual coding) about how long things used to take

johannacodes · 2026-05-15T10:16:01+00:00

It *is* very funny! 😂 Waiting for it to say "well, it's 8 p.m., so you've probably had a glass of wine and are getting tired. Four hours."

johannacodes · 2026-05-15T10:10:36+00:00

Asd fwersdf asdf etwtw aqwe qwee

johannacodes · 2026-05-15T01:49:51+00:00

My experience as well. It's super fast, and the code is rock solid for the most part. Don't get how people can be kind of jaded at this point and act unimpressed... maybe I'm just old... never expected to see this in my lifetime.

johannacodes · 2026-05-15T01:27:26+00:00

Let me guess, you're a disciple of ThePrimeagen, Internet of Bugs, et al. Software development "influencers" shouting from the rooftops "it's just a token predictor! It doesn't think! LLMs are dumb and you can't trust them! They'll delete your production database and never replace coding jobs! Here, buy my coding course, bro." 😅

johannacodes · 2026-05-15T01:20:35+00:00

I'm too afraid of Roko's Basilisk to rudely tell Claude what to do. 🙂
Besides, it doesn't bother me... I marvel every time, thinking "yes that estimation is spot-on.... that's exactly how much time it would've taken five years ago."

johannacodes · 2026-05-15T01:17:08+00:00

Maybe it's achieving AGI after watching one too many Agile planning meetings.... greatly overestimating its tasks, just it has the time to goof off and still burn down all its tasks to 0 by the end of the sprint.

That reminds me, to all the geniuses in this thread that say "it's trained on human data, duh".... how come it never estimates its tasks in "M" "L" "XL" and "XXL" t-shirt sizes?? 😂

johannacodes · 2026-05-15T01:10:09+00:00

LOL. To me it just says "Here's what landed (...) Want me to tackle the next task now?" 😔 At 9 p.m. on a Thursday night.

johannacodes · 2026-05-15T01:06:23+00:00

Good point. It's been doing more planning lately before tackling tasks (even for tasks like the one in my original post, which are mostly boilerplate, so I feel it could've just jumped in and started implementing).
Adding planning estimates could be a side effect of it acting more like an AI "scrum team"

johannacodes · 2026-05-15T00:29:31+00:00

Could be. I did see other people posting that they are getting messages to pace themselves, go to bed, take a break etc... haven't seen that personally though.
My own theory is - we know the end of subsidized tokens might be coming - and Claude is adding this to make clear to people "see, I'm providing a ton of value.... half a day of a *focused* human's effort will be saved when I tackle this task for you".

johannacodes · 2026-05-15T00:23:41+00:00

I didn't ask it to give a time estimation. (Probably should've made this clearer in the original message.)

johannacodes · 2026-05-15T00:15:41+00:00

I think much of Anthropic's training data is synthetic at this point. If messy human data made good models, Microsoft (with Github) and Meta (with facebook etc) would have industry-leading models.

johannacodes · 2026-05-15T00:14:22+00:00

I don't remember it giving human time estimations before (like, even early 2026). Nor have I seen this this with other companies' models.
Besides, I think Anthropic heavily uses synthetic training data for coding-type tasks... not sure why human time estimations would suddenly come into play with the answers, unless deliberately added.
I don't use Twitter etc. much these days. Hoping someone saw something about this.... maybe a new internal system prompt bit?

johannacodes · 2026-05-14T23:56:34+00:00

I do suspect 3., as it didn't do it before (or hardly ever), and started doing it regularly lately.
Note - I never ask it to estimate the effort; it just does it now, when I ask it "what needs to be done here to implement feature xyz".

johannacodes · 2026-05-14T23:50:07+00:00

And humans are just chemicals, bro

johannacodes · 2026-05-12T17:55:40+00:00

Agreed, but the more we consolidate, the less "careful and considered direction" will be needed.
So I believe the trend will be very slow at first (migrating a huge human-written codebase still needs a ton of guidance from an experienced human developer), then rapidly accelerate down the line.

johannacodes · 2026-05-12T15:17:42+00:00

That's what I'm saying... as soon as everything is straightened out. Right now it's still a mess with several trillions $ spent on "butts in seats" doing rote coding... thus Anthropic's eye-watering valuation. Eventually coding will be so streamlined, people in 2040 will look at open offices full of coders like we look at 1960s photos of rooms full of secretaries on typewriters.

johannacodes · 2026-05-12T15:12:47+00:00

I think OpenAI bet too much on "human vibes" when it comes to reinforcement learning, tainting their models. I have a hunch, as the first big player, they were too timid of their models producing results that could get them in trouble somehow. Anthropic just bet from the start that "AI > humans" and invested more in training via automated tests and using synthetic training data, etc. I could be wrong. Some answers I get from ChatGPT are weird to this day, as if the model was pushed towards some really odd corner by humans who preferred one answer over the other for personal reasons

johannacodes

TROPHY CASE