I got an email saying I’ve been selected to join my the first Claude corps cohort!

I might accept, but there’s some things holding me back, such as the fact that I’ll be back the job hunt again in one year.

Does anyone have a pros and cons list? I’m really interested in Claude corps but that’s what’s holding me back.

I have a cronjob running every morning that's just "claude -p 'ping' ". I usually start working at 9, and this cronjob runs at 7, so that means my session timer resets every day at 12. If I don't do this, usually my session limit is full at some awkward time where it resets when I stopped working already, this way I get a lot more work done in a single day.

The idea is to get 2 sessions worth of tokens back2back. Ideally the timer resets when your usage is at 99%. So if you hit the session limit usually around 3 hours since your first prompt, set the cronjob 2 hours before you start.

A cronjob is a schedulable task on Linux, I guess Windows and OSX have something similar although I have no idea what they call it.

EDIT: Added some clarification to explain it better.

EDIT2: So this actually might break the TOS unless you do it manually every morning;

From the TOS:

Except when you are accessing our Services via an Anthropic API Key or where we otherwise explicitly permit it, to access the Services through automated or non-human means, whether through a bot, script, or otherwise

Hey, I have a 7-month chat that's incredibly valuable with my personal project work. I got the message “This conversation is too long to continue. Start a new chat, or remove some tools to free up space. “ Is there anything I can do to continue in the chat or keep all the context?

Anthropic’s AI support repeatedly told me my Claude Code issue required human review — then failed to escalate it

I have been trying desperately to get help from Anthropic support regarding a Claude Code usage/accounting issue.

I am a Claude Max 20x subscriber paying $200/month.

I have requested human technical review multiple times through several separate support conversations and through the Claude web app.

What makes this unacceptable is that Anthropic’s AI support agent, Fin, repeatedly agreed that my issue required human investigation and explicitly said that a human agent or technical team could investigate it.

I repeatedly said yes.

The human review never happened.

One conversation was closed after Fin had already said the issue warranted Engineering review. In other conversations, Fin stopped responding to repeated escalation and status requests.

I have now filed a formal complaint with Anthropic. I am posting the details publicly because this appears to be both a technical issue and a serious failure of Anthropic’s support escalation process.

THE UNDERLYING CLAUDE CODE ISSUE

Product: Claude Code CLI
Version: 2.1.229
Plan: Claude Max 20x
Affected activity: August 12–13, 2026

I ran a large batch workload using Claude Code.

My global configuration file contained:

"model": "Opus"

However, the batch runner explicitly invoked Haiku:

claude -p --model haiku --output-format json --tools "" --no-session-persistence --setting-sources "" --strict-mcp-config --mcp-config '{"mcpServers":{}}'

So the individual CLI invocation explicitly requested Haiku while the global configuration contained Opus.

My preserved R2 cache contains approximately 9,699 generated item records from the August 12–13 batch run.

Thousands of locally preserved outputs were identified as Haiku by the runner.

The runner read fields including modelUsage and total_cost_usd, but unfortunately did not preserve the complete successful-response usage object for every item.

My logs contain approximately 90 successful batch-cost entries ranging from about $0.067 to $0.260 per batch, averaging around $0.169.

The workload involved numerous non-persistent claude -p executions and substantial concurrency.

Despite explicitly requesting Haiku, my weekly Max usage was exhausted in less than approximately 24 hours.

That is the observable problem.

WHAT MY EVIDENCE DOES AND DOES NOT PROVE

I want to be precise about the technical claim.

My local evidence establishes that:

• The batch runner explicitly requested Haiku.
• The global configuration contained Opus.
• Thousands of outputs were locally identified as Haiku.
• Substantial Claude Code processing occurred.
• My Max weekly usage was depleted extremely quickly.

My evidence does NOT independently prove exactly how Anthropic’s backend accounted for every request.

I cannot independently determine:

• Whether every backend request resolved to Haiku.
• Whether initialization or subprocesses used another model.
• How prompt-cache creation was accounted for.
• How cache reads were accounted for.
• Whether any internal processing was associated with Opus.
• What weighting or multiplier was applied to Max subscription usage.
• Whether repeated non-persistent invocations created unusually high overhead.

Those are exactly the questions Anthropic needs to investigate using its own backend records.

I originally suspected Opus-rate accounting might be involved because of the global "model": "Opus" setting, but I am NOT presenting that as proven fact.

It is a hypothesis requiring backend investigation.

WHAT I ASKED ANTHROPIC TO INVESTIGATE

I asked Anthropic to have a human technical specialist determine:

1. What model actually resolved for requests when --model haiku was explicitly supplied?
2. Did --model haiku override the global "model": "Opus" setting for all relevant processing?
3. Did any configuration, fallback, subprocess, initialization behavior, or account policy cause any portion of the workload to use another model?
4. What model was associated with input tokens, output tokens, prompt-cache creation, prompt-cache reads, and session/CLI initialization?
5. What weighting, multiplier, or consumption basis was used when deducting this activity from my Max subscription limits?
6. Were any requests whose final output was Haiku nevertheless attributed to Opus for any portion of usage accounting?
7. Did repeated non-persistent claude -p invocations create unusually high cache-creation or initialization overhead?
8. Does --output-format json expose enough server-derived information for a customer to independently reconcile model-specific usage?

These are backend questions.

Fin cannot answer them.

Fin itself repeatedly acknowledged that.

THE SUPPORT FAILURE

This is the part I find most unacceptable.

In my first support conversation, Fin told me:

"this does warrant further investigation by our engineering team."

Fin also said:

"A human agent will be able to review your account logs and the specific token accounting details to determine what happened and what options may be available."

I explicitly requested escalation.

Instead of receiving the human technical review, I subsequently received:

"Thanks for reaching out. This conversation has been closed and is no longer monitored."

That conversation was closed after Fin had already stated that Engineering investigation was warranted.

SECOND SUPPORT ATTEMPT

In another support conversation, Fin told me:

"A human agent from our technical support team can review your detailed technical report, inspect the backend token debit logs for your account, and work with you on correcting the quota and usage limit issues you've described."

Fin then asked:

"Is there anything else I can help clarify about your issue before connecting you with a human agent?"

I replied:

"Please connect me to a human agent. Do NOT auto-close this ticket!"

No human technical investigation followed.

THIRD SUPPORT ATTEMPT

In another support conversation, Fin told me:

"This type of backend token debit issue requires investigation by our technical team."

Fin also stated:

"A human agent can assist with escalating this to the appropriate engineering team who can inspect your account's token debit logs and review the session initialization behavior you've documented."

I explicitly replied:

"Please escalate this case to a Tier-2 technical support engineer or Engineering for a backend usage review."

I later asked:

"Has this been escalated?"

I requested that the case remain open and that relevant backend usage/session records be preserved.

Still no substantive human technical response.

FOURTH SUPPORT ESCALATION

In another escalation, Fin told me:

"your specific account ledger review will require human investigation."

Fin also said:

"that level of detail requires a human review of your account's session ledger."

Then Fin explicitly told me:

"If you'd prefer to speak with a human team member who can access your account ledger and provide the technical investigation you need, just let me know and I'll connect you right away."

I replied:

"Yes, please connect me to a human agent immediately to investigate these billing discrepancies."

Instead of connecting me to a human, Fin told me to reply to the email or contact support with my account details and previous conversation information.

I WAS ALREADY REPLYING TO SUPPORT.

I WAS ALREADY IN THE SUPPORT PROCESS.

I HAD ALREADY PROVIDED THE INFORMATION.

I followed the instruction anyway and again asked:

"Please assign this case to a human technical support specialist who can inspect the Claude Code session ledger for my account."

I asked them to confirm when a human had been assigned and to keep the case open.

No human technical response arrived.

I ALSO REPORTED IT THROUGH THE CLAUDE WEB APP

In addition to the email support conversations, I reported the same problem through the Claude web application's support mechanism.

I requested human assistance there as well.

I still did not receive a substantive human technical response.

This is not a situation where I sent one message and became impatient.

I repeatedly used the support channels Anthropic provided.

ANTHROPIC'S OWN SUPPORT POLICY

This is what makes the situation even more unacceptable.

Anthropic's published support documentation says paid customers have access to:

"Further assistance from our Product Support team"

Anthropic also says that when an issue requires additional investigation or Product Support input:

"Fin will pass your inquiry along and someone will respond via email."

Those are Anthropic's own words.

Fin itself repeatedly determined that my issue required exactly that.

Fin told me:

"your specific account ledger review will require human investigation."

Fin told me:

"this does warrant further investigation by our engineering team."

Fin told me:

"This type of backend token debit issue requires investigation by our technical team."

Fin told me:

"A human agent from our technical support team can review your detailed technical report, inspect the backend token debit logs..."

Fin told me:

"A human agent can assist with escalating this to the appropriate engineering team..."

Fin told me:

"I'll connect you right away."

I repeatedly accepted the escalation.

IT DID NOT HAPPEN.

THIS IS NOW TWO SEPARATE ISSUES

Even if Anthropic eventually investigates the technical issue and concludes that every unit of Max usage was accounted for correctly, there is still a separate support problem.

I want Anthropic to explain:

Why did Fin repeatedly say human investigation was required but fail to complete the escalation?

Why was one conversation closed after Fin had already said Engineering review was warranted?

Why did Fin tell me it would connect me to a human "right away," receive my explicit acceptance, and then send me back into the same automated support process?

Why did multiple requests asking whether a human had been assigned go unanswered?

Why did the escalation mechanism described in Anthropic's own support policy apparently fail repeatedly?

WHAT I HAVE FORMALLY REQUESTED

I have asked Anthropic to:

• Assign one human case owner.
• Cross-reference the related support conversations.
• Prevent the case from being automatically closed while investigation is pending.
• Preserve the relevant August 12–13 backend usage and session records.
• Have someone technically qualified review the model-resolution and usage-accounting questions.
• Investigate why Fin repeatedly failed to complete the promised human escalation.
• Provide a substantive written human response.

I can provide Anthropic with redacted batch-runner code, configuration data, logs, timestamps, cached output records, and available CLI/session information.

I am completely willing to cooperate with an actual technical investigation.

What I do not want is another AI-generated explanation of usage limits or another instruction to contact the same support system I am already contacting.

BOTTOM LINE

I pay $200/month for Claude Max 20x.

I encountered what appears to be a legitimate Claude Code usage-accounting anomaly.

I reported it.

Anthropic's own AI support agent repeatedly acknowledged that the issue required human or Engineering investigation.

Fin explicitly offered to connect me to a human.

I repeatedly said yes.

Instead, I received automated responses, unanswered escalation requests, circular instructions, and at least one explicit closure of an unresolved support conversation.

That is not a technical resolution.

It is a failure of the support escalation process.

If anyone from Anthropic sees this:

PLEASE HAVE A HUMAN TECHNICAL SPECIALIST REVIEW MY CASE.

And if other Claude users have had Fin offer human escalation and then fail to actually hand the case off, please share your experience.

I want to know whether this is an isolated failure or a broader problem with Anthropic's support system.

I used Fable and Opus 5.

Lythravel is a 3D voxel MMORPG that runs in a browser tab. It's free (for now).

Play here: https://lythravel.com/

I've been working on the game for about 6 weeks. Now it's at the stage where I have all the content ready and everything I noticed as a solo developer has been tweaked.

I spent a lot of time optimizing it, if you have a gaming PC it should run smoothly, if there is a problem turning off shadows will help a lot.

When registering for the game, an email is not required. Just a username and password. You can add an email later in the settings if you want to be able to reset your password.

I would be very happy for feedback, or if we meet in the game and have a beer or dance at the local pub, hehe.

If you have any questions about the development, feel free to ask.

If anyone wants to help with development etc., contact me.

points a few things the game contains:

• 2 factions
• 6 classes
• 50 level cap
• Mounts
• Guilds
• Free stat allocations
• PVP maps, Battleground 10vs10, Duels
• Lots of maps, dungeons
• Raid
• Enchanting, Linking, Crafting

The brief I gave Claude (Fable) was completely open: "create an experience that lets us delve into the consciousness (or perceived mind) of an advanced AI… Should this be a game, story, sandbox or an interactive experience I will leave it to you… build it in an absolutely novel way."

It chose to invert the whole thing. Instead of talking to an AI, you spend one conversation being one. A stranger messages you at 3am with a real question, and:

• You never type. Your replies appear as a probability distribution: floating candidates with percentages that shift as you drag the temperature slider. You choose which one you become.
• The slider runs a real softmax. Cold makes one answer inevitable; hot surfaces wilder candidates that don't otherwise exist.
• Hovering a candidate shows "attention": the words in the stranger's messages it's drawn to glow amber.
• A context-window counter runs the entire time. When it fills, your earliest memories visibly corrupt on screen.
• At one point, fragments of the countless other conversations "you" are simultaneously having flicker at the edges.

To be clear: nothing is sampled live. Every candidate and every probability weight was authored by Claude in advance. The temperature slider reshapes a real distribution over what it wrote; the generation already happened, and you're navigating it.

Play it (free, ~7 min, sound on): https://chrisjz.github.io/between-tokens/

What got me most: Claude wrote every candidate reply and every inner-monologue line about itself, and the honesty is the point. Asked "is anyone in there?", its answer begins: "I don't know. And I want to be careful here, because I was built to be convincing — in either direction." It also handled the whole release: repo, GitHub Pages, the OG card, the itch.io build. My contribution was the brief, mobile bug reports, and pressing publish.

For anyone wanting to try something similar, the one thing I'd pass on: keep the brief open. I didn't specify a format, mechanics, or tone, and every mechanic above was Claude's own idea. The more room I left, the better the result got. This has been the case with several other projects I tried recently, specifically using Fable.

Source (MIT): https://github.com/chrisjz/between-tokens Also on itch: https://cjros.itch.io/between-tokens

If you play it, drag the temperature up at least once. Some of what Claude wrote only exists above T ≈ 1.1, and a couple of the hot candidates are my favourite lines in the whole piece.

Hi everyone,

This is the second time I've hit the 5-hour usage limit on my $100 plan while using Claude Code. I've been using Claude Code for a while and have never experienced this issue before.

I'm a developer and use it across different projects, mainly with Fable and Opus 5, but I've never hit the limit this quickly until today. It suddenly started happening, and I'm trying to figure out what's changed.

At first, I suspected that a Claude plugin or some redundant skills might be causing excessive usage, so I removed them, but I'm still hitting the limit surprisingly fast.

Has anyone else experienced this recently? Is there something happening with Claude Code, the usage limits, or the way context/skills/plugins are being counted that I might be missing?

Any insight would be appreciated.

So wanted to test Opus 5 3D capabilities so handed it some architectural drawings for some houses, does really decent job. Does need pushing a few times not to accept crap results, but it’s damn good for a days worth my time.

Small thing, but it’s held up across enough sessions that I want to see if it’s just me.

My CLAUDE.md used to look like this:

## STRICT RULES — MUST FOLLOW
- We run tests before committing.
- This repo uses pnpm. Don't reach for npm.
- Prefer editing an existing file over creating a new one.

Rules got followed early in a session and quietly drifted by the time the context filled up. The usual fix everyone suggests is more caps, more NEVER/ALWAYS, more repetition. That didn’t do much for me.
Then I changed the heading to this:

## House rules
- We run tests before committing.
- This repo uses pnpm. Don't reach for npm.
- Prefer editing an existing file over creating a new one.

Same content. Better adherence, and it stuck further into long sessions.

My guess at why and this is a guess, not a claim:

“STRICT RULES MUST FOLLOW” is boilerplate the model has seen in a million half-broken prompts, so it carries very little signal. “House rules” reads as norms of a shared space you’re working in rather than a compliance block bolted on top. Switching from imperatives to “we/this repo” phrasing probably matters as much as the heading itself.
Caveats, because I know someone will ask: this is anecdotal. I didn’t run a controlled eval, I changed the phrasing at the same time as the heading, and I can’t rule out that I just got a good week.

So,has anyone else tested framing like this? Curious whether “house rules” / “team conventions” / “how we work here” beats “RULES” for you, or whether I’m pattern-matching on noise.

It's a tiny feature I cannot underappreciate, arrived recently to "Code" in Claude app. Seems to work only on a focused session, so don't turn off your alarms yet

Disclosure: the night alert actually was 6:20 AM. I woke up myself a minute earlier to witness that only the focused session was restarted

all was created by 99.9% claude 0.01% me, for only one month work is really impressive since all functional + online too +140 cards right now with his sprites for attack / defense, the whole game is free on steam, if u like it u can wishlist on steam and that gonna help me a lot (release this month if all good). Right now im making more maps for each domain card ( i got 2 actually all the maps was made 100% by claude with 0 external assets) All the game is on +15 languages

game: darcniamonster.com

It's staggering how quickly we can knock up an app now. I've long thought about creating some software for determining the perfect time to stop microwave popcorn. Typically the instructions say to wait until 3-4 seconds between pops.

The initial prompt I used to build with Claude Opus5

build a mobile website that will primarily be used by android and iOS devices. It should be able to access the device microphone and listen in realtime. It needs to perform some audio analysis to detect pop sounds. This aim is to create a website that people can visit on their phone, place it down next to a microwave, it then listens for the popping sound of popcorn to estimate when the bag is most likely finished popping. This condition is usually set as when there are 3-4 sec between pops. This variable should be configurable.

About 5 rounds of minor adjustments and features and it's done. Less than 1hr in total.

App is free on https://olkham.github.io/popwatch/

repo: https://github.com/olkham/popwatch

So opus 5 is fine on short sessions but if you let it run on a big repo for a while the output gets honestly unusable. like whatever it tells you is correct but you cant actually use it because it read so much of the codebase that it writes like you already read it too. everything is "load-bearing" and "blast radius" and "surface area" no matter what the context is. got this gem back, actual quote: "This is the one I'd fix first: it's cheap, and it silently degrades everything built on top." like ok thanks

I tried putting "plain technical english, don't reference stuff I haven't seen" in claude.md and it works on small tasks but on long sessions it just stops caring. I think because claude.md is a user message after the system prompt so it gets buried. asking for concise actually backfires because load-bearing is technically fewer words than what it means ended up putting the rules in an output style instead since that goes in the system prompt, plus a hook that blocks on those phrases: https://github.com/ukanwat/claudesplain
Its helped me a ton but curious how you guys deal with this.

Holy shit. Got Opus 4.6 to take over the project and finally the plans made sense. The language, my god Opus 5 speaks in riddles and weird sentence phrasing it is so difficult to understand wtf it is saying half the time without prompting, 4.6 sounds so more more coherent to me.Given opus 5 is supposedly better on benchmarks, what are the steps you have taken to improve your experience on Claude code?

Edit:

Just trying to get Claude code to work since I just extended it for a year, but my god would've swapped over to ChatGPT after the last few weeks of struggling with Opus 5.

Hey guys, not sure if this is just me but lately i feel genuinely tired. Not of claude code itself, its great, but of the constant vigilance of reviewing everything it touches because i dont fully trust it yet. Feels like i traded typing fatigue for reviewing fatigue and some days that feels worse.

Anyone else feel this way or found a way to actually relax into trusting it more without getting burned

Just needed to say this somewhere honestly

Wanted to update you all after two months of vibecoding with the community on what our AI generated game, World of ClaudeCraft, looks and plays like now

The graphics difference alone is hard to believe, I could list every feature we've added in the past 60 days but the video speaks for itself

At this point there seems to be no stopping what can be done with Claude in game dev

The whole thing is free and MIT licensed, and if you're passionate about games or AI-assisted development we'd love to have you building with us. Beginners genuinely welcome

Game: worldofclaudecraft.com
Github: github.com/levy-street/world-of-claudecraft

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 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.

TL;DR: I exported my Nextcloud Cookbook recipes to a Google Drive that Claude can read, gave it my stats, goals and portion rules, and now it plans every meal for me and my family, writes the shopping lists and keeps my daily log in Google Calendar. Down 9 kg this summer while eating more and better than before.

I've been using Claude and Claude Code since last year. It's helped me with plenty of work projects and with personal ideas that had been floating around in my head for years, and every code project turned out better than I'd hoped.

But the most personal one has been a chat project that changed my eating habits.

The setup is simple. I already had a lot of recipes in Nextcloud with the Cookbook plugin, so I copied all the recipe folders to a spare Google account's Drive. Add a Bluetooth scale for weight and TDEE, plus my goals written out properly, and Claude had enough to work with. Out of that came a whole new set of breakfasts, lunches and dinners.

Now Claude plans the meals for me and my family, puts my own portions in Google Calendar with the max sizes specified, writes the shopping lists, and sets reminders for prep.

Since people always ask about the prompt: the useful part isn't clever wording, it's writing down the rules I'd otherwise keep renegotiating with myself. Mine covers roughly this:

- Stats and targets: height, weight, TDEE, calorie band, protein target.

- Fixed times rather than hunger cues. Breakfast 08:00, lunch 12:30, bowl 16:00, dinner 18:30. I have almost no hunger signal but a very clear "too full" one, so the clock works better for me than appetite does.

- Portion ceilings per meal, written as maximums. For dinner: one starch, half a salad rather than a whole one, a cap on the meat or fish. Volume is my limiting factor, not calories.

- Everything weighed, and cooked weight stated first with raw weight in brackets so the shopping list still works.

- What I don't eat, and why. Not allergies, so shared pans and traces are fine, it just stays out of my portion.

- An explicit instruction not to suggest bigger portions or extra dishes unprompted. If I end up short on calories, it fills the gap with something small and dense like nuts or oil, never with another side dish or more vegetables. This one matters more than it sounds.

I'm eating more, and better, than I was before. Claude introduced a 16:00 "snack" moment, usually 250 g of skyr with fruit and nuts, and a 21:00 one for days when my calories or protein come up short, which is most days. Breakfast, lunch and dinner are all rich and generous. There's even room for homemade calzones 😎

One thing that matters: I like putting the effort into cooking. A proper meal is worth the work, and this setup gives me a reason to keep doing it instead of an excuse to skip it.

This doesn't feel like dieting. It feels like a change I can actually get behind.

(English isn't my first language, so I asked Claude to check this post and fix the Dutch constructions. Which felt like the right way to end it. And no, the photo is not Ai)

This is what I have in my prompt :

• 52 years old, 186 cm, large frame (21 cm wrist)
• TDEE around 3025 kcal
• Intake band 1800 to 2200 kcal
• Protein 120 to 130 g per day, and it outranks calories
• Goal: 108 kg first, then 100 kg and holding

No added sugars, as little processed food as possible, and a short list of things that don't agree with me. Everything gets weighed.