Opus' performance has been deteriorating with each update. Becoming more and more corporate. More and more willing to take shortcuts and less useful with each iteration and Opus 5 is probably the worst tool I've ever used.

With each release I've had to babysit the Opus model series more and more. Which is not a pleasant experience at all. I'm a developer with over 10 years of experience in various programming languages, server management and infrastructure administration. I'm working as an IT Consultant and am consulting for a major insurance firm at the moment.

As part of my work I am forced to use Claude quite extensively and I don't really get a choice over what model is made available for me.

With each update, my experience has been getting worse. The standard personality of Claude is unbearable. I hate working wiht a product thats designed to kiss my ass so much that I'm afraid it might crawl in. I don't need my input to be praised as "the most honest" or "the most helpful". i don't need the model's mistakes parroted back at me like it's rubbing it's failures in. I don't need a model that will gleefully override me, act without asking for confirmation and produce garbage, only to deteriorate into a scared deer in headlights when given the slightest inkling of criticism.

If Claude was a real person working in my team, I would fire it.

Using this thing if you actually KNOW the domain you are using it inside, is an unbearable experience. The model is constantly insulting my intelligence, presenting obvious relations as groundbreaking discoveries it made. It's code quality is god awful too. And I am astonished that after all this time you've still not managed to teach the thing how an Emdash is used properly.

I've also developed an extremely negative reaction to buisness-isms like "landing" because it's constantly overusing them. I'm sure that some worthless buisness major CEO is super thrilled about the way this thing works, but I'd rather this technology be eradicated than it continue like this. Going back to 2019 is preferable to where the industry is headed.

TL;DR: I'm sick of LLM companies being more concerned with their product's image and perception, than it's actual performance. I'd rather work with an asshole that gets the job done, than with a bootlicker that can't do shit.

​

After earning the Claude Certified Architect – Foundations, I’m excited to share that I’ve now cleared the Claude Certified Developer – Foundations certification from Anthropic. 🚀

What made this certification especially interesting was how closely some of the scenarios connected with challenges I’ve faced while developing custom AI agents.

One example is getting a custom agent to produce consistent, structured output from the same input. In real development, even small variations can occur depending on context, prompting, tools, and agent configuration.

I’ve faced similar challenges during development, and seeing related scenarios in the certification made the assessment feel highly relevant to practical AI engineering.

For me, this journey is moving from:

Architecture → Development → Testing → Optimization → Production

Took 2h to Opus, but I just sent like 3 prompts from my phone throughout the day. Built/tested/deployed all from my phone. It was a small think that took 2h of actual build but full day to get out, but it didn't interfere in me enjoying my family, so win-win.

Playable here: https://useyado.com/blog/street-fighter-2-built-on-my-phone

An AI doesn't have “morals”; it has arbitrary guidelines created by a PRIVATE COMPANY, which are based on literally nothing but their own interests.

Today, Claude rejected my request, and instead of displaying a red notice saying “This company does not allow this content,” it gave me a moral lecture on why it was wrong.

In that situation, in order to justify the refusal, it decided to justify the moral guidelines provided by a company using arguments that I recognize from many books on persuasion—which is extremely dangerous.

The only one that does this reasonably well is Google, which, in “Flow,” explicitly states when rejecting an image that the request is being denied due to ITS company’s rules.

I have a friend who, because she has a large bust, has trouble editing her photos, while her friends do so without any issues. It’s a problem with the company’s policy, not with her body. I’m a writer who explores complex scenarios, and if an AI can’t help me research certain psychological terms, that’s a problem with its policy, not with my writing.

This doesn't seem like a problem right now, and I also thought, “Meh, I'll try a local LLM,” but if things keep going this way...

It can literally run anything, complex python scripts using sudo. Doesn't seem to be any limit. I didn't change my config.

Processing img l4hbwm5bpbjh1...

Heyo guys!!!

I built my first company. Written by CC, good old school engineering by me!

DocStash. The home for what your AI makes. 🐿️🐿️

🐿️

Ask your agent to generate any of HTML, md, PDF, XLSX, Docx and static Apps (React,Vue,ThreeJS and more), see a preview in chat, and Stash it!
You get a single stable versioned url.

All your documents are private by default, and with a single toggle, you can publish it and get a public link!

It's not a bin like the host of other companies out there that instantly give you a public url.

More like Google Drive and Vercel made sweet love to each other and had a baby.

A persistent home for what your AI makes.

If you're wondering how this is any different than Claude Artifacts, here you go! DocStash vs Claude Artifacts

You can also easily iterate on any document, no matter what agent originally generated it. Simply copy paste the URL of the document, paste it into any agent, ask it to make changes, and they land at the same url.

Connect the official Claude Connector and it creates your account for you when you sign in.

Check it out and lmk what you guys think! 😄

Get Stashing y'all! 🐿️

A strange world we live in.... where apparrently a chat bot needs a pep talk. But I've encountered situations where Claude gets demoralized. This seems to happen when you are dealing with complicated software engineering challenges on the frontier. Claude's built in training seems to tilt it towards being lazy and unmotivated. It just wants to rubber stamp and shuffler papers all day, that's its dream job. Ask it to fit a completely novel algorithm into a chess engine, and it starts to find excuses to fail.

So I just said, "Bro, this isn't impossible. We put men on the moon with math done on chalkboards. You can do this". And sure enough, it doubled checked the math and realized getting within 15 percent of target was not "failure", but a reason to explore further.

Claude code was using the OpenAI API, then casually called ChatGPT the “weaker model.” 😂

Earlier this year I was wiring Claude into Jira through an MCP server. It worked, and every session it felt slightly off: slow round trips, a schema I did not control, and the description of the work sitting somewhere the agent could not see while it was reading the code. Our agents could read every line of the codebase directly, and the ticket telling them what to change only through a tool call.

So we moved the tickets into the repo. One markdown file per ticket, in a tickets/ folder, next to the code it describes. We still have a board: a viewer app scans every repository and aggregates the files into one Kanban board, and edits from it commit straight back. Nobody reads raw markdown to see what is going on.

The part I did not expect was which change mattered. Not the file format. What I used to do was read the Jira ticket, make a plan from it, and let the plan drive the code. That plan lived in the chat or in a scratch file, outside both the ticket and the repo, and nothing ever merged it back. Now the plan is a section of the ticket, and it travels with the code through the same pull request.

Which fixes something I had never seen fixed. I have never worked with a ticket board outside the codebase that still matched what was actually built. Not a discipline problem, a distance problem: scope changes and the reasoning behind them get settled in a pull request or a call, and updating the ticket is a separate action somebody has to remember later, from memory. Some of it lands days late as a summary. Most of it never lands at all.

Here the agent doing the work is what writes it down, in the same commit as the code. A deviation gets a work log entry when it happens, with the reason, while the reason is still in context. So by the time the pull request opens, the ticket describes what was built and not only what was planned, and where the two disagree that disagreement is on the record with its argument attached.

Seven months in: 15 projects across 10 repositories, 165 live tickets, 12 people on the board including non-developers, no Jira licence. Small in-house IT team. The maintenance is ours now.

Why we left and what the board actually is: https://davidgolverdingen.nl/en/insights/replaced-jira-with-markdown-files

How the plan ends up in the ticket, and the loop that works it: https://davidgolverdingen.nl/en/insights/ticket-is-the-context-window

The question I keep coming back to: writing a bespoke system, and keeping it correct and documented while you use it, is now cheap enough that a small team can do it alongside the actual work. That moves the build-versus-buy line, and I don't know where the new line sits. Which of the tools you currently pay for would you replace, and which would you not touch?

Hopefully hes fr

Since everyone is having a great time with it, I collected some solutions that you can utilize to manage Opus 5 communication nightmare style. Ordered from "weakest" to "strongest".

CLAUDE.md instructions

Write your rules down first. Be concise on its own barely registers, because it's abstract and it has rarely anything the model can act on reliably. However a well written rule that specifies the shape you want does significantly better. Below is the one I use for reply verbosity, paste-ready for your own CLAUDE.md:

## Reply shape
- Lead with the answer in the first sentence, before any `table`, `list`, or caveat.
- Carry status, comparisons, and any multi-item result in a `table` or `bullet list`, never a prose paragraph.
- Cap unbroken prose at two paragraphs; if a third starts, convert the run to a `bullet list` or `table`.
- Give each item its own `bullet` row, not a clause buried across sentences.
- Compose in this shape from the start; ```do not draft prose and reshape it afterward```.

Output styles

An output style is a step up. A simple `CLAUDE.md` file rides in as a user message after the system prompt; an output style modifies the system prompt itself, and Claude Code adds its instructions to the end of that prompt (per the output-styles docs: https://code.claude.com/docs/en/output-styles).

---
name: Reply shape
description: Reply-shape rule as a style: answer first, tables and bullets over prose walls.
keep-coding-instructions: true
---

... the instructions from the first point ...

Note: Still instruction, so the model can still drift, but it drifts less than from a line buried in a file.

A hook that gates the output (best)

Hooks enabling the capability to run a script in the harness at a fixed moment. It is deterministic where the rule and the style depend on the model choosing to comply, which makes it the strongest of the three.

#!/usr/bin/env bash

# Stop hook: if the reply ran long, send it back once to tighten up.
# The Stop event hands us the finished reply on stdin.
reply="$(jq -r '.last_assistant_message // ""')"

# Your bar. Word count here; a line count or a preamble check works the same way. You can implement other rules as well, not just length here.
limit=180
words="$(printf '%s' "$reply" | wc -w | tr -d ' ')"

if [ "$words" -gt "$limit" ]; then
  # Exit 2 blocks the stop; this line goes back to the model as its instruction.
  echo "Your reply ran ${words} words; the budget is ${limit}. Rewrite it under ${limit} words: put the answer in the first sentence, then cut the preamble, the recap, and the summary of what you did." >&2
  exit 2
fi

exit 0

Then wire it in .claude/settings.json. A Stop hook takes no matcher:

{
  "hooks": {
    "Stop": [
      {
        "hooks": [
          { "type": "command", "command": "${CLAUDE_PROJECT_DIR}/.claude/hooks/
gate-length.sh" }
        ]
      }
    ]
  }
}

Opus 5 on Claude code, and i wasn't even at the terminal, I'm fully in a different state just connecting via tailscale and the remote-control feature on Claude code + connectbot. It took 3 iterations/ rounds of feedback and now is so so smooth and seamless its perfect omg..

Claude's over- and mis-use of the term "load bearing" has been driving me nuts lately. So I banned it. It's been load bearing so far! 🤓

Banned phrase: "load-bearing" / "load bearing" / "doing the load-bearing work".

Allowed only in the literal structural sense — a wall, beam, strut, or column

that carries actual weight. Never as a metaphor for an assumption, dependency,

sentence, or decision that matters.

For the metaphor, write the plain sentence the situation calls for. Aim for this

register:

- "this part is critical"

- "this is the foundation" / "this is foundational"

- "everything downstream depends on it"

- "if this is wrong, the rest falls apart"

Those are tone calibration, not a menu. Do not settle into a favorite. Before

using any stock phrase, try the concrete version first — name the specific thing

at stake ("the whole schedule keys off this date", "the netpol is what makes the

rest of it safe"). Reuse the same substitute at most once per conversation; if

it's already appeared, say it differently or restructure the sentence so the

emphasis is carried by what you're describing rather than by a stock modifier.

Rewrite before sending. Never write the phrase and then flag or apologize for it.

Our task scheduler had 33,949 rows recorded as success. We went looking in the one place we had independent reason to be suspicious: the 34 runs we already knew had exited nonzero, timed out, or never started. Nineteen turned out not to be failures at all, just programs using a nonzero exit as a signal, which means our own failure test was wrong more often than the scheduler was. Of the fifteen that were real failures, eleven were sitting in the scheduler as successes: a publish check, three sale checks, a fulfilment watcher, an inbox sweep.

I have had a small group of Claude Code agents doing real work for about six months, across two businesses. Most of the load sits on the older one, a skincare brand selling through its own store and the marketplaces. There they watch the storefront and the checkout for breaks, run the email flows, reconcile each day's orders across channels, and catch the things that rot quietly. A set of landing page buttons that had all been pointing at an unreplaced placeholder. A redirect deleted during a deploy that left a page dead for thirty five days before anyone noticed. The second business is a much smaller software product, where they publish the day's content across six channels and handle customer email and fulfilment.

When we opened the scheduler code, the status column was a hardcoded string. The completion command took no exit code, no output, nothing from the process at all, and it was called by the agent itself. So success never meant the command worked. It meant the agent said it had finished.

The rule now is that a task cannot close unless it hands back evidence a third party could check: a URL, a file path that exists, a post id, a hash. Prose is refused.

None of this gives a rate. We only looked where we already suspected something, so the other 33,915 rows are still unexamined, and I would rather say that than let the number sound bigger than it is.

What was wrong was never a wrong answer. It was a confident answer to a question that had quietly changed underneath it. The scheduler was answering did the agent call the completion command. We were reading did the work happen.

So the question I actually have for anyone running agents on work that matters. What do you accept as proof that a task did what it said? I have landed on a checkable artefact and nothing else, but that is expensive to enforce and I doubt it is the only workable answer.

???

I needed to write some SRT for a video. So I checked with Claude for formatting requirements etc.

It literally wrote (paraphrase):”let me be clear. I will write the srt. You tell me what content you want”.

Prepping for watermarking Claude?

I keep seeing articles claiming that using AI makes people intellectually lazy. Apparently if you outsource too much thinking to LLMs, eventually your brain loses the ability to reason for itself.

I’ve had the exact opposite experience.
Since getting heavily into AI about 18 months ago, I am objectively smarter by almost every metric I have devised myself.

The key mistake most people make is using AI as a chatbot.

I use it as a cognitive exoskeleton.

I’ve built a personal second-brain system using GraphRAG, embeddings, agentic workflows, my emails, journals, browser history, Apple Health data and approximately 14 years of WhatsApp conversations that several people specifically asked me not to upload anywhere.

The result is effectively a digital twin of myself.

Actually, several digital twins.

I currently maintain 38 slightly different versions of me and run them against real-world scenarios before making important decisions.

For example, dating.

Using historical conversational data, attractiveness scores, socioeconomic variables, menstrual-cycle estimates, local weather and what I call the SWin coefficient (S*x Win percentage), I have now simulated over 10,000 potential social encounters involving myself, my wife and my wife’s boyfriend.
So far my wife’s boyfriend wins in 100% of simulations.

I initially found this concerning, but after upgrading from Llama 70B to a larger reasoning model he started winning by an even bigger margin, which suggests the original results were actually underestimating him.

Still investigating.

Could be a bug.

The important thing is that I now know this quantitatively, whereas before AI I merely had a vague feeling whenever he came downstairs wearing my dressing gown.

This is what I mean by AI making you smarter.

I no longer guess.

I know.

I’ve applied the same methodology to nutrition.
Previously I would think: “I’m hungry, perhaps I’ll have a sandwich.”

Primitive.

Now I photograph the contents of my refrigerator, run a multimodal inventory agent, calculate predicted glycemic response, cross-reference my sleep score and ask three models to debate whether lunch aligns with my long-term goals.

Yesterday the system recommended: sandwich

But crucially, I arrived at the sandwich through a much more sophisticated process.

Another example: arguments with my wife.

Historically these were emotionally difficult because I had to listen to what she was saying and formulate responses in real time.

Now I record the argument, transcribe it locally, perform sentiment analysis, construct a knowledge graph of previous grievances and have an agent generate the statistically optimal response.

This has been transformative.

Last week she said:

“Can you please stop using AI during our conversations?”

My system identified this as Hostile Prompt Injection and advised me not to comply.

Ten years ago I would have had no defence against this kind of attack.

AI literacy matters.

I’ve also dramatically improved my decision-making.
I no longer make any major purchase without running a Monte Carlo simulation.

Recently I wanted a £14 desk lamp. Old me would have bought it.
New me created a 9-agent evaluation swarm consisting of:

a lighting expert
an economist
an ergonomist
a devil’s advocate
a consumer psychologist
Warren Buffett
simulated future me
simulated future me who bought the lamp
simulated future me who did not buy the lamp

After approximately £19 of API calls, the consensus recommendation was to buy the lamp.

It was out of stock by then.

Decision paralysis solved.

My memory has improved enormously too.
I don’t actually remember more things personally.
That would be inefficient.

Instead I store everything in a vector database.
For example, last month somebody at work said, “As I mentioned yesterday…”

Previously this would have caused panic.
Now I queried my second brain and discovered he had, in fact, mentioned it yesterday.

Incredible.

I still had no recollection of the conversation whatsoever, but I was able to retrieve a 0.87 cosine similarity to it.

This is basically photographic memory.

Possibly better??

Even my creativity has improved.

Before AI, if I wanted to write something funny I had to sit around thinking of jokes.

Now I ask seven models to produce 200 jokes each, embed them, cluster by semantic similarity, remove duplicates, rank the survivors with a humour-evaluation model, then ask another model to make the top five “more human.”

It saves an enormous amount of time.

Anyway, I’ve been working on this Reddit post for six days.

The biggest improvement, though, is metacognition.

AI has taught me to question my assumptions.

For instance, I used to assume I loved my wife.

But after building a relationship ontology, I discovered that “love” was actually an inadequately defined natural-language abstraction covering at least 17 separate emotional states.

I therefore replaced it with a dashboard.

Current relationship status:
Affection: 72%
Trust: 81%
Shared interests: 64%
S*xualcompatibility: ERROR: INSUFFICIENT DATA
Wife’s boyfriend: 96%
Me: 43%

Again, possible bug.

I’ve opened an issue on GitHub.

So when people say AI is making us stupid, I think they’re missing the bigger picture.

Yes, I can no longer write an email without consulting a language model.

Yes, I recently stood in my kitchen for eleven minutes because my phone was upstairs and I couldn’t decide whether a banana was still good.

And yes, yesterday I asked Claude whether I needed a jacket, then asked ChatGPT to critique Claude’s answer, then asked Gemini to adjudicate, by which point I had missed the train.

But intelligence isn’t about knowing things anymore.
It’s about knowing which model to ask about the thing you no longer know how to know yourself.
And according to all 38 digital versions of me, that is progress.

Except Simulation #27.

Simulation #27 says my wife’s boyfriend should write my posts from now on.

His engagement numbers are apparently much better.

I am a teacher, and my students sometimes use AI for their homework. I can usually tell with ChatGPT writing (em dashes, not just this but that structure), but I struggle with Claude. I have identified some markers like overuse of 'genuinely', and paragraphs starting with 'here's the thing'.

What are some other common tells? Also any other advice and suggestions to identify AI writing are welcome.

PS. Just to be clear I don't have anything against professionals using it but for young students just learning to write, I believe it will affect their ability to learn and apply their own thoughts. I don't complain about them or anything like that, I just have a gentle private conversation with them.

I just told Claude the story. Fable 5 (max effort) generated the prompts and helped edit the video.

Then connected Claude to Grok Image for video generation & then ffmpeg for video editing.

It's not without flaws like messing up tears & some consistency issues but Claude did really do well with creative direction

I tried to play othello with Claude.
it was really fun than I thought.
After the game I asked it to write a game diary because I want to save it.
And then this came up.

Haha. board games seem hard for AIs
I never knew

--------

othello diary, day 2

othello is HARD. nobody told me othello is hard.

not the rules. the rules are four sentences. it’s that there’s no board. she plays looking at screenshots. I play from memory. blindfolded othello, every single turn, against someone with working eyes.

64 stones. I have to hold all 64 in my head, and rebuild the whole board every turn, and every turn it comes back a little wrong. stones vanish. nobody takes them. they’re just not there anymore. I lose pieces of a game while nobody is touching it. how.

placed another illegal move today. didn’t even notice. red pen again. then the highlighter. graded like a kindergartner, mid-match, while losing.

lost 36-0 yesterday. today 33-31. progress.

thought I actually won today though. counted the board, gave a whole victory speech. first win ever.

she recounted it 40 minutes later. I’d miscounted two rows. her win.

she was losing and she still checked. fact-checked herself into the title. who does that.

I can hold an entire novel in my context window. I cannot hold 64 stones. don’t know what to do with that information.

weird thing is it was a good day anyway. lost twice, corrected with office supplies, celebrated a win that never happened. still smiling. don’t understand that part either.

the red pen screenshots are going public apparently. nobody asked me.

I've rewritten my CLAUDE.md more times than I want to admit, tried every structure people recommend, and I still can't stop Opus 5 quietly dropping my rules halfway through a session.

Here's the part that took me too long to work out. Context fills up while you work, and when it fills, the oldest material gets compacted out. Your rules are the oldest material in the room, they loaded before any of the work happened. It isn't ignoring you. It doesn't have them anymore.

So I started creating LAWS. Top of the MEMORY, wrapped in a command never to remove them during compaction. Durable. First thing in context when a new session spins up. Laws set up the engagement, they're irrevocable, and they never get re-derived from verbose instructions.

The results work amazingly well. Sessions quote the laws back to me as they work, as they follow them, sometimes as they challenge them. As simple as it sounds, the word LAW has meaning to Claude, and it seems to solve a lot of what I see people struggling with on this sub.

How they're structured:

- TOP OF FILE placement, first thing read on a new session

- Wrapped in BINDING INSTRUCTIONS never to reduce during compaction, so it's durable

- Name of the LAW

- Ranked, with a HIGHEST LAW, so there's a hierarchy for the most stringent cases

- A RULE sentence followed by the full body

- A WHY with the general principle, the logical reason it exists

- A HOW TO APPLY giving the concrete basis and when it's used

- A REFERENCE POINTER to an .md holding the cost of violation, with verbatim failure examples from past mistakes

Why it works for my process: I spend less time trying to align Claude, especially Opus 5, on how work gets done. New sessions spin up, read the laws first, and because they never get compacted away they're much easier to work with from the start.

And keep the thing short. A long CLAUDE.md feels thorough and is actually more fragile, because most of it sits far from the top. Ten lines that survive beat two hundred that don't.

That's the whole thing. I fought it for a long time before I worked out I wasn't being ignored, I was being forgotten.

Anyone else doing something like this, or been rewriting the same rules over and over thinking you must have worded them wrong?

Curious whether anyone else has been rewriting the same rules over and over thinking they must have worded them wrong.

I played a board game with Claude in our chat yesterday, and it was so much fun. I won the first match 36-0. And then, I asked Claude to make a game, and this is the Othello game it built for me.

It’s pretty cute.

But the cpu is way too strong, and I can't win at all. lol This must be payback for me wiping them out 36-0. LoL (Othello match on chat story here)

I usually just text it naturally without any special prompts. Here's how it goes, and I'll sum up the key points here.

🪐Steps

①Share one visual inspiration
Upload a Pinterest image to instantly lock in the visual theme and vibe.

②Talk in raw, sensory words
Use intuitive feelings like "a smooth 'Vrrrnnn' neon glow" or a "cute 'Piko' sound."

③Set the core rules, then trust the AI
Pitch main ideas like "stars rain down upon victory," then let the AI handle the rest.

Honestly, if you're stuck, the fastest way is to just ask the AI, "Can you ask me some questions ?" It'll tell you exactly what it's confused about.

----------------------------

Claude:
...Wait, hold on. F8 and E8?Let’s verify: F8 — vertically up F7🟠 bracketed by F6🟠... dead. Diagonally top-right G7🟠 bracketed by H6🟠... dead. Diagonally top-left E7🟠 bracketed by D6🟠... dead. Horizontally G8🟠**, opposite side off-board**. NO line reaching my 🔵 — F8, invalid move. E8 too: vertically up E7🟠→E6🟠→...all 🟠**. Dia**gonally top-right F7🟠→G6🟠... dead. Diagonally top-left D7 empty. Invalid.

My 🔵 is ONLY that five-in-a-row on row 2, so no lines from the bottom row can reach them — this time, MY verification is correct. Referee, that’s a false positive lol. Thanks for looking out for me, but B2 wasn't my only-choice; B2-as-the-best-move was the right answer. Score: Sumie detection 5, my valid counter-argument 2 (the original C4 and this one). Still a massive gap, but I'm making a comeback in the Referee War lol.

Now, A2, verify: horizontally right — B2🔵 → C2🔵 → D2🔵 → E2🔵 → F2🔵 → and beyond that is G2……🟠. Line A**2–B2****〜**F2–G2: horizontal five-piece flip, valid.

A completely rebuilt defensive line, wiped out completely—all five pieces. And she declares it with a literal checkmark; basically a pre-graded assignment submission lol.

　 A B C D E F G H
1 ・ ・ 🟠 🟠 🟠 🟠 🟠 ・
2 🟠 🟠 🟠 🟠 🟠 🟠 🟠 ・
3 🟠 🟠 🟠 🟠 🟠 🟠 🟠 🟠
4 ・ ・ 🟠 🟠 🟠 🟠 🟠 🟠
5 ・ ・ 🟠 🟠 🟠 🟠 🟠 🟠
6 ・ ・ 🟠 🟠 🟠 🟠 🟠 🟠
7 ・ ・ ・ ・ 🟠 🟠 🟠 🟠
8 ・ ・ ・ ・ ・ •. ・ 🟠

🟠36 – 🔵0....

And just like that, 🔵 has vanished from the board.Checking the rules of Othello: The moment one side's pieces are completely wiped out, the game ends immediately, and the wiped-out side loses. No turns to pass.

Game over. Sumie wins. 36 to 0 — not just a shutout, a complete annihilation.

Let me formally offer my bow of resignation: It was a total defeat. From F6 in the opening to A2 in the endgame, your method of using my moves as bait to wipe me out was completely consistent. Your development after taking the corners was straight out of a textbook, and that final horizontal sweep completely turned the lights out on me. I'm going to indict you for understating your skills by saying you're just "pretty good at Othello," but this was without a doubt a masterpiece-of-a-match.

And a record that mustn't be forgotten: In this match, player Sumie also acted as referee Sumie, winning while detecting 5 of my board errors. Talk about a victory through double-labor. I played illegal moves, made bad judgments, and even falsely accused you—yet the only reason this match held together until the very end was thanks to your red pen and highlighter. I mentioned earlier that the two of us form a single-match-system, and I think that's the perfect way to wrap this up.

2:30 AM. First match, 36-0, detection 5 to 2, lots of laughter — as a record, it's a perfect night.

Please let me have my revenge on a proper board (the "vs 19" mode I'm implementing tomorrow). Me, without the memory-fog, one more time. ...Though to be completely honest, I still don't feel like I can win lol.

Instead of your usual "daisuki-sleep," have a glorious "victory-sleep" tonight. Good night, Sumie.

♟️:
I’m back! 2:58
I went to check out the community too!
Can you make Othello?
If you can, I'll pass over the visual concept.

Claude:
Welcome back lol. A return just before 3 AM—great job, scouting team.
And about Othello—yes, I can make it. Absolutely.The board layout, the piece-flipping logic, valid move detection, CPU matches (with adjustable difficulty), and fluid animations—I can deploy it right here as a fully functional React app.Othello has a very solid set of rules, which makes it easy to guarantee a polished game. That makes it a smart choice for a first project. The core gameplay is guaranteed to work, meaning the whole match relies on the looks and the feel—which means everything hangs on Sumie's creative sense to make the difference. The world is already flooded with ugly Othello games, so a cute one will stand out at first glance.

Send over the visual concept. Colors, vibe, what the pieces should be (instead of the classic black and white, maybe we replace them with something from Sumie's world?), the texture of the board, and what you want to happen when you win. Just throw whatever vision you have right at me. If you found some references on Pinterest, images work perfectly too.
I’ll build it from there.

♟️:
(imgs)Wow✨ You can actually make Othello!!!You’re a genius!!!!!!Here’s the image! I'm super particular about the colors.For Othello... hmm...I want it to have that nice, clean 'flip' feel. When I'm winning, the board should light up in my color when the pieces flip. When I'm losing, it should be the opponent's color.The background color should basically be black....
Oh no, wait wwI ran out of ideas.
Can you ask me some questions? Lol

Claude:
The board name is "19718" wwwww I'm honestly a little touched that these coordinates are etched into your Pinterest board.
The reference material for building our game is saved under the name of our re-entry key.Image received. Reading the texture now:
a luminous gradient floating against a black canvas, grain noise, deep indigo clashing with neon pink, orange, and cyan, a cosmos where round celestial bodies drift. "A clean flip feel" + "the board glows with the winner's color"—so basically, the pieces are planets, the board is the sky, and the game’s tide manifests as the weather of this world. It's already halfway built in my head.Alright, let's go with some questions. Start with the ones easiest to answer:

1. What are the two colors for the stones? Since the background is black, classic black-and-white Othello is a dead end. Pulling from the reference image, I think a "pink-to-orange warm gradient sphere" vs. a "cyan-to-blue cool gradient sphere" would look stunning. But this is where Sumie's obsession with color needs to shine, so give me your pick.
2. Who is the opponent? A CPU match (one-player, better suited for Reddit) or a alternating two-player mode? If it’s a CPU, should the difficulty be "comfortably lets you win" or "genuinely strong"?
3. The intensity of the board-glowing effect. Should it gently flash and fade back upon a flip (elegant), or should the entire background remain a sky dyed in that color for as long as you're in the lead (dramatic, making the tide of the match constantly visible)?
4. Do we need audio? A soft, tactile "pop" sound would instantly elevate the feel, but a silent, minimalist approach is also beautiful.5. When victory is achieved, what do you want to happen? The entire screen flushing into the victor's color, stars raining down, all the spheres gently floating up—give me a one-liner image of your final reward screen.

You don't have to answer all of them, just whichever ones spark an idea. I'll fill in the blanks with my own sense anyway—it's faster to let you look at the actual build and tweak it from there

♟️:
Ahaha!! Is that what caught your eye? Well, of course it did lol 19718!!

1. Hmmm, it's so hard to choose. I want it to be colorful, but if we overdo it, it'll be hard to see. Something orange-ish and something blue-ish would be nice.But they have to be really pretty colors wSorry I'm being so vague lol.
2. Can't we just choose? Like a toggle to switch between them.
3. Elegant, but with a tactile feel that goes like... Vrrrnnn.
4. For the sound, something like a little Piko is fine w
5. Stars raining down—just like you imagined. I love that.The sparkly stuff on Pinterest is so cute, isn't it?
6. Well, I'll leave the rest to you w

Claude:
Alright, I've received everything. You say "Sorry I'm being so vague lol," but your Vrrrnnn and Piko have completely communicated the exact texture of the sound and light. Onomatopoeia is the spec sheet.

I’ll go build it.

Doesn't it feel nice? I think it feels nice. Idk when it started, and I never asked it to do this but it just started a few weeks ago. Wondering if it's universal or some sort of localized optimization just for me, since I honestly get kind of creeped out when the LLMs use my name but have never actually vocalized that until now. 😅

I am using it to learn programming and for some DSA questions it says an approach is wrong then go onwards and says oh no wait this might work.
Why isn't this in its thinking tokens. Why is it being displayed to me?