Claude Code creator said Claude wrote 100% of his code last month: https://xcancel.com/bcherny/status/2004897269674639461
"[Person who is financially incentivized to make unverifiable claims about the utility of the tool they helped build] said [tool] [did an unverified and unverifiable thing] last month"
Is anyone with or without AI approaching anywhere near that speed of delivery?
I don’t think my whole company matches that amount. It sounds super unreasonable, just doing a sanity check.
https://steve-yegge.medium.com/welcome-to-gas-town-4f25ee16d...
> It’s also 100% vibe coded. I’ve never seen the code, and I never care to, which might give you pause. ‘Course, I’ve never looked at Beads either, and it’s 225k lines of Go code that tens of thousands of people are using every day. I just created it in October. If that makes you uncomfortable, get out now.
Humans writing is slow, no doubt, but humans reading code ain't that much faster.
I'm not affiliated with Claude or the project linked.
https://www.amazon.com/Vibe-Coding-Building-Production-Grade...
He also has some other agent-coordination software. https://github.com/steveyegge/vc
Don't know whether it's helpful, or what the difference is.
> Gas Town is also expensive as hell. You won’t like Gas Town if you ever have to think, even for a moment, about where money comes from. I had to get my second Claude Code account, finally; they don’t let you siphon unlimited dollars from a single account, so you need multiple emails and siphons, it’s all very silly. My calculations show that now that Gas Town has finally achieved liftoff, I will need a third Claude Code account by the end of next week. It is a cash guzzler.
https://steve-yegge.medium.com/welcome-to-gas-town-4f25ee16d...
Which could mean that code was refactored and then built on top of. Or it could just mean that Claude had to correct itself multiple times over those 459 commits.
Does correcting your mistakes from yesterday’s ChatGPT binge episode count as progress…maybe?
I can easily imagine constant churn in the code because it switches between five different implementations when run five times, foing back to the first one on the sixth time and repeating the process.
I gotta ask, though, why exactly is that much code needed for what CC does?
It's a specialised wrapper.
#!/usr/bin/env bash
while true; do
printf "> "
read -r USER_INPUT || exit 0
RESPONSE=$(curl -s https://api.openai.com/v1/chat/completions \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "Content-Type: application/json" \
-d "{
\"model\": \"gpt-5.2\",
\"messages\": [
{\"role\": \"user\", \"content\": \"$USER_INPUT\"}
]
}")
echo "$RESPONSE" | jq -r '.choices[0].message.content'
doneThat's an awfully presumptious tone to take :-)
I'm not deciding "This is how many lines they are allowed", I'm trying to get an idea of exactly what sort of functionality that CC provides requires that sort of volume.
I mean, it's a high-level language being used, it's pulling in a lot of dependencies, etc. It literally is glue code.
Bearing in mind that it appears to be (at this point anyway) purely vibe-coded, I am wondering just how much of the code is dead weight - generated by the LLM and never removed.
Lines of code has always been a questionable metric of velocity, and AI makes that more true than ever.
There's a ton of cruft in code that humans are less inclined to remove because it just works, but imagine having LLM doing the clean up work instead of the generation work.
- get a feature request/bug
- understand the problem
- think on a solution
- deliver the solution
- test
- submit to code review, including sufficient explanation, and merge when ready
260 PRs a month means the cycle above is happening once per hour, at constant speed, for 60 hours work weeks.
You know the features you'd like to have in advance, or changes you want to make you can see as you build it.
And a lot of the "deliver the solution - test - submit to code review, including sufficient explanation" can be handled by AI.
This is more what agentic-assisted dev looks like:
1. Get a feature request / bug
2. Enrich the request / bug description with additional details
3. Send AI agents to handle request
4a. In some situations, manually QA results, possibly return to 2.
4b. Otherwise, agents will babysit the code through merge.
The second is that the above steps are performed in parallel across X worktrees. So, the stats are based on the above steps proceeding a handful of times per hour--in some cases completely unassisted.
---
With enough automation, the engineer is only dealing with steps 2 and 4a. You get notified when you are needed, so your attention can focus on finding the next todo or enriching a current todo as per step 2.
---
Babysitting the code through merge means it handles review comments and CI failures automatically.
---
I find communication / consensus with stakeholders, and retooling take the most time.
Lines of code never correlated with quality or even progress. Now they do even less.
I've been working a lot more with coding agents, but my convictions around the core principles of software development have not changed. Just the iteration speed of certain parts of the process.
My understanding of the current state of AI in software engineering is that humans are allowed (and encouraged) to use LLMs to write code. BUT the person opening a PR must read and understand that code. And the code must be read and reviewed by other humans before being approved.
I could easily generate that amount of code and make it write and pass tests. But I don't think I could have it reviewed by the rest of my team - while I am also taking part in reviewing code written by other people on my team at that pace.
Perhaps they just aren't human reviewing the code? Then it is feasible to me. But it would go against all of the rules that I have personally encountered at my companies and that peers have told me they have at their companies.
The AI evangelists at my work who say this the loudest are also the ones shipping the most "did anyone actually look at this code?" bugs.
ratatui_ruby % git remote -v
origin https://git.sr.ht/~kerrick/ratatui_ruby (fetch)
origin https://git.sr.ht/~kerrick/ratatui_ruby (push)
ratatui_ruby % git checkout v0.8.0
HEAD is now at dd3407a chore: release v0.8.0
ratatui_ruby % git log --reverse --format="%ci" | head -1 | read first; \
echo "First Commit: $first\nHEAD Commit: $(git show -s --format='%ci' HEAD --)"
First Commit: 2025-12-22 00:40:22 -0600
HEAD Commit: 2026-01-05 08:57:58 -0600
ratatui_ruby % git log --numstat --pretty=tformat: | \
awk '$1 != "-" { \
if ($3 ~ /\./) { ext=$3; sub(/.*\./, "", ext) } else { ext="(no-ext)" } \
if (ext ~ /^(txt|ansi|lock)$/) next; \
add[ext]+=$1; rem[ext]+=$2 \
} \
END { for (e in add) print e, add[e], rem[e] }' | \
sort -k2 -nr | \
awk 'BEGIN { \
print "---------------------------------------"; \
printf "%-12s %12s %12s\n", "EXT", "ADDED", "REMOVED"; \
print "---------------------------------------" \
} \
{ \
sum_a += $2; sum_r += $3; \
printf "%-12s %12d %12d\n", $1, $2, $3 \
} \
END { \
print "---------------------------------------"; \
printf "%-12s %12d %12d\n", "SUM:", sum_a, sum_r; \
print "---------------------------------------" \
}'
---------------------------------------
EXT ADDED REMOVED
---------------------------------------
rb 51705 18913
md 20037 13167
rs 8576 3001
(no-ext) 4072 2157
rbs 2139 569
rake 1632 317
yml 1431 153
patch 894 894
erb 300 30
toml 118 39
gemspec 62 10
gitignore 27 4
css 22 0
yaml 18 2
ruby-version 1 1
png 0 0
gitkeep 0 0
---------------------------------------
SUM: 91034 39257
---------------------------------------
ratatui_ruby % cloc .
888 text files.
584 unique files.
341 files ignored.
github.com/AlDanial/cloc v 2.06 T=0.26 s (2226.1 files/s, 209779.6 lines/s)
--------------------------------------------------------------------------------
Language files blank comment code
--------------------------------------------------------------------------------
Ruby 305 4792 10413 20458
Markdown 60 1989 256 4741
Rust 32 645 530 4400
Text 168 523 0 4358
YAML 8 316 17 961
ERB 3 20 4 246
Bourne Again Shell 2 24 90 150
TOML 5 16 10 53
CSS 1 3 8 11
--------------------------------------------------------------------------------
SUM: 584 8328 11328 35378
--------------------------------------------------------------------------------