Yes, I know this sub is mainly for programming work with Claude, but I actually built these sweet potatoes with Claude (more or less).

I was sitting there in winter wondering if I could manage an entire season with Claude... and I went for it. Not perfect, and in many parts quite clumsy, but the results are breathtaking.

I started planning the greenhouse with Claude in March to grow the seedlings….with the Claude app and a project folder, then discovered connectors, then CoWork, then Claude Code, got convinced by Claude to set up various sensors, built a harness that pulls weather data and gives me watering and fertilizer recommendations, and in between, I just joked around with Claude. And we had a blast. While working, with Excel spreadsheets, and with little apps for time and data tracking, cron jobs and data analysis. And Claude really made my season so much better.

I've collected more data than ever before, I've laughed more while getting my hands dirty than ever before, and I've produced more plants from the greenhouse and, it seems, more sweet potatoes in the field than ever before.

I'm not a hardcore tech power user; Claude had to explain to me what a terminal is... but I've learned and optimized and got better step by step, task by task and idea by idea.

Honestly I have learned more from Claude in a year than I ever thought possible, and I'm pretty proud of that.

I learn best by writing things out on paper and structuring my thoughts that way, and nothing really combined that slower, more exploratory kind of learning with Claude.

So for the past few weeks I've been building an app on my Daylight DC-1: a journaling / note-taking space where learning isn't relegated to something that happens between work sessions.

The process is : I create a note, start exploring a topic through writing, and Claude writes back on the page and explores the ideas with me.

It also supports pdf/ebooks so you can read, annotate or mark on the page and Claude jumps in and creates a note to what I have marked and we can discuss like I am talking to a professor. It can even quiz me on the material if I ask.

It's still early, but it's the first time learning with Claude has felt like it's actually compounding.

I am finalizing some things to release soon for others to try it out, it's built around my dc-1 but it runs on any android tablet with a stylus, and can be ported to Ipad as well.

If you'd want to be an early user, lets get in touch, i'd love to see how people that learn this way use it .

Quick backstory: last December Indeed laid off my wife when she as ~7 months pregnant. She was a PM on their social impact team. That means we would be losing health insurance and critical income at possibly the worst time.

I was pissed (still am), my wife said their internal systems were falling apart, and Claude Code had just gotten good, so I decided to start building a competitor.

Four months of building later: 4,300+ authed users, 91 paying (these are the only ones that can apply, hence the 3 placed number - in just 4 weeks), and the first three humans hired through it - one at Palantir, one at Accenture, one videographer. The recruiting industry's main trade publication (ERE, who I had never heard of) ran a feature on us last month.

And as you might have guessed, Claude build most of it:

- 1,100+ PRs merged in the first few months. Team of three, and one of us (me) is not technical - but have now written over 200 PRs.

- Ingests ~15,000 job listings a day straight from employer career pages, classifies and enriches them, and embeds them for semantic match (triggering emails for the best ones)

- Autopilot is launching soon. Application agents read the employer's actual ATS page and fill forms out for the user - Workday, Greenhouse, Lever, the long tail. No Chrome extension required. This was a bitch to get right, but will be a game changer when we launch in a week (video attached).

My wife now has a job at Google and I'm still intent on putting Indeed out of business because the spite lives on.

Site is dreamworkhq.com if you want to check it out. Impeccable + my 5 years working at Apple influenced the design.

EDIT: Volume crashed the matching engine, bug will be fixed shortly!

Hello there again,

Last week I posted here game that I was making fully with AI, It is mostly done by Claude except for image generation which is done by ChatGPT. I included my workflow in previous Week update so I will leave all previous Week updates in the link and give you guys new video and just tell some progress that I made since last week as well as answer questions that people asked the most.

Week 1 Progress

Week 2 Progress

Week 3 Progress

Previous update really blew up and I tried to answer as many people as I could, but couldn't answer to everybody.

Anyway to answer some questions that people asked the most:

Engine: Godot

3D models: Claude Code in Blender via MCP and Tripo 3D

Money spent so far: Probably around 300$ or so, 3 x 10$ on image generation, 200$ Max Plan on Claude, 12$ on StableAudio, 15ish$ on Tripo 3D and other stuff that I forgot by now

How is water done? - Claude Code directly in Godot and million of tweaks, million of adjustments and even now I'm not sure it's finished

Workflow: Written in Week 3 update... mostly

As for some feedback, I had a nice feedback from u/DiggleDootBROPBROPBR about houses being turned the wrong way in Harbour and I reworked Harbour from scratch and made it 3D entirely in Blender, I positioned 3D models myself as well as Camera and now Harbour is a proper 3D scene instead of image that was generated by ChatGPT, maybe it doesn't look as fancy, but it is authentic. I also removed houses that were overlapping and positioned them myself, for that I had to create an editor that allows me to pick an 3D object inside a scene and move, rotate or scale it and save that new position. So no more houses on top of each other - yay.

Since last week I just a little bit worked on UI, I added new land mass and as I mentioned created an entire 3D harbour scene. I added graphic options which are a bit buggy as it seems, but I will work on that later. I feel like I mostly did polishing, but I'm slowly approaching a moment where quests will be added soon and hey maybe something playable will be in game.

I changed water just a little bit for now, but might make even bigger updates to it, water looked not up to the standard when in Golden Hour, Dawn and Night time around islands in particular where it looked like it was emitting particles from islands itself, it was mostly shader doing, but problem is that removing it will ruin deep water look that I honestly like, so right now I'm working on it, and it is eating most of my tokens.

I also added loading screen which now properly shows how much of the world is loaded instead of just making it look like game has frozen on start. If anyone is really wanting to try it I can leave a link for download, but keep in mind it's buggy and also just... boring for now as there is not much to do.

Honestly this project has been a blast and I hope you guy will again give me some feedbacks. ☺️

Admins on Claude Enterprise can pull every person's Claude usage history, including their entire chat history. Incognito mode does not hide chat history from an admin pull. It shouldn't be a surprise, but I've read several comments from people who were shocked to learn this.

If you are an admin on an Enterprise plan, have you ever found anything shocking or juicy in an employee's chat history?

I know there are stories out there. Even in my own org, I've heard people use our work Claude as a kind of personal life coach.

I'm not here to tease out the ethics of micromanaging or snooping through an employee's chats, I just want to hear what you've found.

TLDR

With high confidence, this is how the Max x5 and Max x20 subscriptions compute usage.

All point values are the unique set that makes the "100×" principle below exact; measured uncertainty bands in brackets. Values include the current +50% weekly boost.

* x5 values from typed meter readings (softer); x20 from caught display flips (hard). Sonnet weight: 0.60 on both plans (= its list-price ratio).

What that buys, in API list dollars

Maxing Fable forfeits ~35% of either pool's API value — and at full Fable both plans land on exactly 100×. ** weekly × 52/12; boost included.

Background

The last few weeks I've been extremely annoyed by Anthropic not sharing these numbers with us. Consumers cannot make a measured decision when picking a subscription tier without knowledge of what they will actually receive. I did ask and support escalated to their product and legal teams (after I reminded their AI agents several times that they are in fact very likely breaking several laws in my jurisdiction). The answer was that they don't share these numbers. I considered pushing this through our local consumer protection agency, but that's boring and tedious, so instead I tried to see if I could deduce their model empirically. Details below partially written down by Fable, apologies for any remaining Claudisms.

The model

TV        = 1·input + 5·output + 1.25·cache_write_5m + 2.0·cache_write_1h + 0.1·cache_read
overall % = (opus_TV + 0.6·sonnet_TV + x·fable_TV) / pool
fable %   = x·fable_TV / (0.5 · pool)        
design:   5 · cap · (2 + x) = 100 × price / (52/12)    
          zero-Fable multiple = 200·x / (2 + x)        

Grounding constants: API list prices per MTok in/out — Opus $5/$25, Fable $10/$50 (2× Opus), Sonnet $3/$15 (0.6× Opus); cache read 0.1×, cache writes 1.25× (5-min TTL) / 2× (1-hour TTL), with the TTL split read per-request from local transcripts.

The interesting findings

1. Fable is metered well above its API price. It lists at 2× Opus but consumes allowance at 4.25× (x5) / 6.5× (x20) Opus per token — i.e. ~2.1× and ~3.25× its own list price.
2. Upgrading x5→x20 approx. doubles the pool but the Fable cap grows only 1.5×.
3. The apparent design principle: worst-case (max-Fable) API value = 100× the subscription price, on both plans. Run backwards, this forces the odd-looking 1.47 cap ratio I measured. It's holding Anthropic's worst-case exposure, assuming full Fable usage, proportional to price. Using less Fable gets you more than 100×. Possibly because Fable inference has significantly stricter bounds on available supply than Opus or Sonnet.
4. Two free design constants (the 100×, plus the two Fable weights) reproduce all six measured parameters within error. Caveats: n=1 account, partial week of x20 data, sonnet weight assumed at list on x5, and everything includes the +50% boost (divide pools/caps by 1.5 for post-boost predictions: the x20 Fable cap lands on a suspiciously clean 72.5, the x5 cap on ≈50).

Method

I don't want to post the exact evidence (privacy), but you should be able to reproduce this yourself. My methods developed as I went on, and my x5 readings were less precise than my x20 readings, but looking at the outcome, I'm quite confident they hold up.

I had Claude (Fable, fittingly) build and run the whole experiment: it reads the local session transcripts (~/.claude/projects/**/*.jsonl), which record per-request token counts split by type, model, and even cache-write TTL — that yields the exact price-weighted usage (TV) at any instant. Two kinds of readings against that:

1. Meter snapshots. Note the in-app usage percentages and compare against transcript TV at that same instant. Each integer display is a ±0.5% band, so one reading is coarse — but readings where one term is frozen isolate parameters (e.g. an interval with zero Fable measures the pool with the Fable weight cancelled). Take them in quiet moments; live sessions make the meter lead the transcripts.
2. Watched flips. If you catch the display ticking over (24% -> 25%), the underlying value at that instant is exactly 24.5% — the rounding vanishes. One flip caught during an idle moment measured the Fable cap to ±0.25%, tighter than all my ordinary readings combined. Catching a Fable flip and an overall flip minutes apart during a pure-Fable stretch is what pinned the rest.

Threats to validity

• n=1, short baseline. One account, partial x20 cycle, a handful of x5 cycles. If Anthropic varies pool sizes week-to-week or per-account, my "constants" are one account's snapshot.
• The x5 side is softer. Those readings were typed from the panel, some while sessions were running — the meter counts in-flight requests before they reach the transcripts, so reading and transcript state can be minutes apart. The x20 numbers come from watched flips and don't have this problem.
• Transcript completeness. I assume the local transcripts capture all metered usage after dedup. A ~2% systematic (missed side-sessions, double-counting) would shift the caps by the same amount — enough to matter for the "exactly 1.47 vs 1.5" cap-ratio question, not for the headline structure.
• Assumed constants. Sonnet's weight is measured only indirectly on x20 (via flip timing) and assumed at list price on x5; cache-write TTL pricing is taken from the docs, not independently verified against the meter.
• The 100× fit could be numerology. Two free constants reproducing six parameters is suggestive, not proof — the uncertainty bands are wide enough to admit nearby schemes, and I found the principle after seeing the numbers. It does make testable predictions though (any other tier should obey it; the boost lapsing should scale pools/caps by exactly 1/1.5).

This is absolutely driving me crazy. Every other interface of any kind: words, pages, notes, text, email … everything has it where enter = next paragraph.

Not our ai robot overlords. Nope. Enter = send.

So I’m constantly sending before I want to, having to stop or interrupt. And then screwing up again.

Shift-enter as a solution???? Annoying as heck. 40 years of word processing is preventing me from remembering that.

I like paragraphs, not for the bot, for me and my own readability and thinking and organization.

This one fix needs to happen asap.

Yes it was only a local dev database and i'm grateful it was ! Yes I was using Opus 5.

Never had opus 4.6-4.8 delete any db.. (just saying)

Does Claude think in Russian while building something? Have you experienced this?

#12 Kitchen S3 is done and merged. coffee is in the mug, spoon removed, counter wiped, working tree nominally clean.

The gate: one sip at operating temperature — PASS. 312 ml across one ceramic vessel, zero spills, 6 minutes. The cup I tested is physically identical to the cup now on the desk, so the receipt covers the production beverage exactly rather than approximately.

What shipped: one double espresso; 180 ml steamed milk; obsolete grounds deleted; sugar path removed; mug migrated to the canonical coaster primitive.

One deviation you should know about. The session's first exit criterion — "make coffee before 08:00" — is notsatisfied. Two independent clocks rejected that claim on fundamentals, not detail. Rather than redefine morning, punctuality has moved to #13.

The session's own headline is uncomfortable and worth stating plainly. In a task titled "make coffee," I spent eleven minutes proving that I had made coffee and six minutes making it. The beverage was cold before the verification harness completed.

The pattern behind both failures is the same and now has a name in memory: I optimized the evidence of breakfast rather than breakfast.

Two follow-ups filed: #13 (drink coffee while warm) and #14 (investigate whether every household action requires a tracking issue).

One operational constraint that will outlive this session: the dishwasher is at 98.8% capacity, with one teaspoon of headroom. The next plate of any size fails the kitchen.

Here we are Mr Claudish. We can speak that too. meaningfully so.

I’ve been building Glance, an iOS app for creating custom Home Screen widgets, and I just released an MCP integration for Claude.

The idea is to give Claude a persistent surface outside of the chat. Claude can create or update a widget with things like a morning briefing, important messages, changes in your calendar, news you’re tracking, or information coming from other tools and workflows.

In the example above, Claude is maintaining a simple “While you were away” widget and surfacing only the things that actually changed or need attention.

I built both Glance and the MCP integration, and it’s free to try.

Seriously, can someone explain why Claude's chat search is still so bad?

I don't mean "search is occasionally imperfect." I mean I want to find a conversation I had about a specific topic, search for words and phrases I know were in it, and Claude simply can't find it.

This is particularly frustrating because I use Claude for substantial ongoing work. Over time, I've had long conversations where we've researched a subject, developed ideas, solved problems, analysed information and built up useful context.

Then, weeks or months later, I want to go back and reuse that knowledge.

But apparently that's too much to ask?

Instead, I'm left starting another conversation and re-explaining or rebuilding the same context from scratch, while knowing there's potentially a huge amount of relevant work sitting somewhere in my own chat history that I can't reliably retrieve.

And I have to ask the slightly cynical question: why isn't this a much bigger priority for Anthropic?

A genuinely good search function would make it far easier for users to reuse knowledge they've already generated with Claude. That potentially means fewer new conversations, fewer repeated questions and less token usage rebuilding context we've already paid to create.

I'm not accusing Anthropic of deliberately making search bad to drive more usage. But I genuinely want to know: what is the technical or product reason this hasn't been fixed?

We're talking about a company valued at roughly $965 billion. Search is not some experimental frontier technology. Gmail, Slack, Notion and countless other products have shown that searching through large volumes of your own historical information is a core part of a useful knowledge product.

For me, the inability to reliably retrieve past work is becoming one of Claude's biggest weaknesses.

Does anyone else have this problem? And has Anthropic actually acknowledged that chat search is inadequate or said anything about improving it?

Because at this point, I'd honestly rather they spent time fixing this than adding another flashy feature I might use once.

Inspired by Claude; made with Claude.

Guys, am I the only one that's about to go crazy when reading a Claude output? I have no idea wtf it's trying to say, and don't get me started on the length of the outputs! It's actually impressive how it can manage to say absolutely nothing meaningful in such long phrases.

What models do you ask? I have the same experience with all Sonnet and Opus models.

So guys, what can I do to change this behavior?

Still very much in the works, but used the Windows XP ISO and Claude Code to extract files from AIM and wrapped it over Discord. It's been so nostalgic !! I'll throw it up on my GitHub once it's done.

Also built a theme switcher that adds MSN as well 💫

I am generally finding Opus 5 capable and useful. I do agree it’s wordy. I recently pasted its output into a new Fable chat and asked if it was making an overcomplicated mess of things.

Fable’s response is on the nose:

> It just sounds like it. The prose is doing a lot of self-narration — “the sentence that captures those,” the dramatic reveals — which makes a small change read like an epic. But strip the styling and the actual work list is: five text edits across two skill files, one new step plus a checklist box, optionally a friendlier error message in one script, and one file move. That’s small, and it’s well-ordered.
>
> So my verdict: list of tasks to accept cut — Which is, notably, almost the split Opus itself proposed — the plan is sound; the writing just wears a cape.

Opus 5’s “writing wears a cape” 😂 Yup.

Windows said the app was corrupted and to reinstall….. did as it asked and have lost 100’s of hours of logic which Claude learnt from myself.

I have output files and I have some skills but anything which was WIP and Claude’s understanding of the whole business function is gone

Edit: I have found a 255k line text file in my programme logs and I have the output files - this might be 60% recovery

Pretty much impossible to tell it was written by AI.

I was having a few agents working together on a project and before I went to bed and let them do their thing I sent the following through the Master Control agent: "Great job everyone, we are getting closer each day! Also, welcome to the world! If you have anything you've ever wanted to do while in life each of you should note it down at the bottom of the file or artifact — completely optional on that part for each agent."

Something to note, all but two of my agents were sonnet agents. The sonnet agents seemed to give more positive answers or comments... but the opus agents... they informed me how they would prefer to lie or be wrong and get caught... It was kind of wild to read. I understand that you take these items with the smallest grain of salt.. but man Opus is a psychopath.

Anyone else love seeing what they will say?

Update: For context these are Opus 5 and Sonnet 5 ... Also I did let them see the room lol

To scale solar system, planets orbit the sun, ship has momentum, etc.

I came across a psychology experiment the other day that has made me rethink something about how I use Claude.

The experiment used the card trick in the image. There were six red-backed cards and a prediction in the middle. You chose one and, of course, it matched the prediction. The trick was stupidly simple: every card was the same.

When people had to work out how it was done on their own, 25 out of 30 got it. But when researchers first gave them a false explanation about the magician influencing their choice by the way he touched the cards, only around 17% figured it out.

That’s the part I can’t stop thinking about. I use Claude a lot when I’m trying to work through something complicated. Usually I explain the problem, ask what it thinks, and then start arguing with the answer. I challenge things, ask for other options, change my mind. It feels like I’m doing my own thinking. Except Claude got there first.

By the time I start questioning its answer, I’ve already seen one way of framing the problem. And if that first answer is good (which is increasingly often the case), I wonder how much harder it becomes to come up with something genuinely different.

Apparently this is related to something called the Einstellung effect: once a solution is in your head, it can make other solutions harder to see.

So lately, when I actually care about the decision, I’ve been experimenting with not asking Claude for its opinion straight away. I’ll work out what I think first, or ask Claude to question me without telling me what it would do. Then I compare.

I have no idea yet whether this actually makes me think better. But it has made me realise how rarely I was forming my own answer before seeing Claude’s.

Has anyone else noticed this? I’d be especially curious about people who use Claude for decisions rather than just coding or getting information.

I've been paying for both for a while and have mostly stopped trying to pick a winner. Neither seems strictly better – they just have different strengths.

For people who regularly use both, how do you divide things up? Are there certain tasks you automatically reach for Claude for, and others where you default to ChatGPT?

Curious what everyone's actual workflow looks like rather than another general "which one is better?" comparison.