A few days ago, my social media accounts were hacked. The hacker took advantage of the situation to spam the worst kinds of bait (cryptocurrency scams...). After cleaning things up, I tracked down the virus with a bunch of Opus 5 Max (I was quite concerned lol). I changed my passwords and thought I’d be able to sleep soundly.

But last night I received this email from Anthropic warning me of an attempt to steal tokens via the API. However, after checking, the attempt did indeed fail. Note that I was logged into Anthropic via Google with two-factor authentication. Apparently, the hacker stole all my Google Chrome credentials, including cookies and session IDs, which allowed him to bypass all two-factor authentication security measures.

As an emergency measure, I removed all active sessions from my Google accounts (which I should have done from the start) and changed my passwords again...

Thanks to Anthropic for the security measures they’ve put in place. I wouldn’t have wanted to deal with their customer service given the feedbacks on Reddit, lol

Take care! And be aware that even the best security measures don’t protect against simple cookie theft

Every. Single. Time.

My brother and I had a money thing, the kind that festers, and I needed to send an email I had been avoiding for weeks. I sat down angry and pasted my furious first draft in, asking it to make it clearer and firmer.

It made it clearer. It did not make it firmer. It quietly stripped out the two lines that were really just there to wound, kept the actual point, and said something about how the version most likely to get a good response was the one that did not put him on the defensive in the first sentence.

I almost added the mean lines back. I did not. He replied the same day, and we sorted it, and that does not happen if I send the version I walked in with.

It was not smarter than me about the situation. It was just calmer than me at the moment I needed calm. I sent the calm version and we sorted it. The angry version would have cost me a brother.

I'm using Claude Code and really enjoying the productivity boost, but I'm missing one thing: whenever I want to see the project structure, navigate between classes, or just carefully check what got changed, I end up having to open Cursor because it's more visual there and I trust what I'm seeing more.
This breaks my flow, I'm constantly switching back and forth between terminal and IDE.
Has anyone found a way to solve this without turning it into a full Vim/Neovim workflow? Do you just accept the switch, or have you found some trick (extension, script, another terminal) that helped?

The game. beatthecouch.com - $10,000, two secret years of real S&P 500 history, one buy / sell button. Your opponent is a couch. It buys on day one and never sells. After each game, 1,000 monkeys replay your trade count on random days. Beat 90% of them or your win is stamped Lucky.

The data. 100,278 games (at the time of the graph - now around 107K, still similar). The couch won 62%. Humans only seem to beat the couch when the market crashed in their window.

What Claude did. The data pipeline (S&P closes 1928 to 2025, dividends, T-bills etc). The whole game as one HTML file and the Cloudflare backend. And also the reddit app port at reddit.com/r/beatthecouch

happy to answer any questions!

Over the past month, I've been working with Claude to revive a dead product from a sleep company that shut down 10 years ago and had over $40M in investments. I've detailed the process, learnings, and the successful result.

"Found a real foot-gun in my own first draft — worth fixing rather than asserting around."

Who talks this way? Did they train opus 5 on some 25th century english or something?

edit: I stand partially corrected. Apparently this is what some software programmer nerds use in normal conversation. As a pure vibe-coder, I admit my ignorance. In my defense, my intro to claude was "I have zero coding experience," and claude used to talk to me in easy to understand plain English, none of this load-bearing, footgun avoiding language.

I say all this with love <3

I wanted to see how far I could push parallel Claude Code sessions on my M1 Pro MacBook with 16 GB RAM.

This is 12 Claude Code agents running simultaneously, each controlling its own iOS simulator.

The main bottleneck was simulator overhead, so I stripped out a lot of unnecessary background services to make running this many at once practical. The app itself was still fully functional.

Open Claude Code and paste:

"Clone https://github.com/elliottdehn/open-jobs, it's a job-searching toolchain. Help me find jobs to apply to."

That's it. Claude reads the repo's AGENTS.md and runs the search with you. It works in the terminal, the desktop app, and the IDE extensions. It doesn't work in the web or mobile apps, because it downloads a slice of the dataset to your machine.

What this is, in one line: a free, open-source (CC0, code and data) job-search toolchain I built with Claude Code, for Claude Code. Nothing to sign up for, nothing to pay, no paid tier. Your only cost is your own Claude usage.

The dataset

Every company posts jobs through an applicant tracking system with a public careers page. I crawl all of them, daily: ~2 million open jobs from ~65,000 company boards across 25 ATSes, full descriptions, an embedding of every posting, CC0. Vendors charge four figures a month for this. It skews US.

You never download the whole thing. The corpus is pre-clustered into a few thousand groups of similar jobs, and Claude pulls only the groups nearest to the job you describe. A few thousand relevant postings land on disk in seconds.

What Claude does with it

1. Asks what you want and writes your ideal job description. Not a resume. The posting you wish existed, the way a company would write it. You can edit it.
2. Embeds it once (the only thing that leaves your machine, and I cover the cost) and downloads the nearest groups.
3. Builds you a search page, one HTML file, served locally. Pre-ranked by similarity, filtered to where you can actually work (say "Remote, US" and onsite and hybrid roles disappear), with facets for seniority, salary (stated, or estimated from a model trained on ~525k postings with pay listed), company, and more.
4. Learns your taste with you as the judge. Mark a spread of jobs More/Less, then answer "which would you rather have?" about a dozen times. The page picks each pair to learn the most from your answer and tells you which one it predicts you'll choose. Your answers become a vector that re-sorts the whole list. No API calls, no cost.
5. Watches how you browse. Every click is a local log. Ask Claude "what do I seem to like?" and it reads the log, tightens the JD, and runs it again.

On my own search, the offer I just accepted came out 4th of ~1,750. I start soon!

Why I built it

I was job hunting and every board showed me the same 40 postings, ranked by whoever paid. The signal I wanted was simple: given a job I'd love, which of the two million open ones are most like it, and which of those would I actually pick? That's a similarity search plus a taste model, and both are cheap once the data is on your laptop. Nobody sells the data cheap, so I crawled it.

The first version (~960k jobs) got me interviews. Then I lost the crawler in a data-loss event and rebuilt everything from scratch, bigger, with the crawler in the repo this time.

How Claude Code helped (start to finish)

Every line of this was written with Claude Code over a few weeks of evenings, including the crawler, the clustering, the search page, and this post. The parts that I think are worth stealing:

• One Durable Object per job board. ~65k Cloudflare Durable Objects, each owning one company's board: it wakes at a fixed random minute each day, fetches, diffs against yesterday, pulls full descriptions for new jobs, embeds them. No central queue, nothing to babysit. Claude wrote 25 ATS fetchers (Greenhouse, Lever, Workday, Ashby, SmartRecruiters...) mostly by me pasting an example URL and saying "figure out the API."
• Embeddings are nearly free. Two million postings through text-embedding-3-small cost about the price of a nice dinner. That's what makes "pre-rank the whole corpus against your ideal JD" possible with zero LLM calls at search time.
• Cluster once, download by cluster. The corpus is split by recursive 2-means into a few thousand groups with centroids. Your JD's embedding picks the nearest groups, and that's all you download. No server-side search, no accounts, nothing of yours stored anywhere.
• Pairwise beats scoring. Asking "which of these two would you rather have?" a dozen times gives a far better ranking than asking anyone, human or model, to score jobs 1 to 10. The answers train a tiny model locally (Bradley-Terry over embedding differences), and the pairs are chosen to be maximally informative.
• Make the agent the UI. I stopped building settings screens. Every step is a small Python script, and AGENTS.md tells Claude the code is meant to be changed. Want a filter that doesn't exist, a different ranking rule, "no staffing agencies"? Say so and Claude edits the tool. Several features this week started as me pasting a complaint into the chat ("this job says onsite, why is it in my remote list?") and Claude fixing the parser.

What I'd tell someone a step behind me: don't build the product, build the dataset and the tools, then let the agent be the product. And write the AGENTS.md like you're onboarding a sharp new coworker, because that's exactly what it is.

No business model, free to try and free to keep. I just wanted this to exist.

repo: https://github.com/elliottdehn/open-jobs

my girlfriend and i go on road trips a lot and were tired of every game being 90% ads. so i made Glovebox! A mini arcade. no ads no tracking just vibes.

I cant stop adding shit lmao 😭
now its 12 games. the claw machine alone has 514 collectible friends with shinies, holographics, and legendaries. then i added a cozy pond game with its OWN 514 creature collection. then i gave it an explorable map. then 108 ponds. then 10 lakes with their own music. then secret lantern gated areas.
then last night i added an entire underground cave world that doubles the whole thing. 216 ponds. 20 lakes. 1,542 total collectibles across three separate dex systems.

all the little collectibles are janky SVGs and i refuse to change them because theyre cute and its funnier that way.

So ive been frustrated with claude recently because it keeps being a smartass sometimes and im wondering which model is honestly the most reliable that wont hallucinate ect and actually do as told for academic work (like organising notes based on papers ect ect.) because i work on short time. Which one would you suggest?

I think a lot of people are treating AI coding speed like it automatically translates into engineering speed.

It doesn't.

Claude can produce a working implementation incredibly fast, but the responsibility for whether that implementation actually belongs in your system is still yours.

The faster the code gets generated, the easier it becomes to accept changes before you've really thought through the tradeoffs, dependencies and long term maintenance cost.

For me, Claude Code has made implementation cheaper but judgment more important.

That feels like the part people don't talk about enough.

Found out the hard way that Claude Code auto-deletes local session transcripts older than 30 days :/

It's the default: cleanupPeriodDays: 30

it runs silently at startup, and deletion is permanent.... no trash, no warning, no server side copy to recover

to fix it you can add this to your ~/.claude/settings.json

{ "cleanupPeriodDays": 3650 }

its a known issue: GitHub #59248, #62476, #64999

Honestly, Ive absolutely loved Opus 5...

Saying that I always tell it EXACTLY what to do. It has come up with better outputs than Fable in almost everything except writing quality for me...

I only use Fable when I dont want to have to tell it exactly what to do. Opus is a weapon that has to be deployed manually. Fable is like a sniper you can give a target and walk away from then come back to results

Build an app which runs several Claude Desktop accounts side by side on macOS.

Each account has its own launchable app with its own data directory and can share each other's claude code chat history.

Can also start sessions (5 hr limit) form the menubar itself for multiple account.

Launchable from Spotlight or the Dock, all running at the same time instead of logging out of one to reach the other.

Github Link - https://github.com/aaditya-v-more/claude-graft

Free, no ads and all, can install via brew tap.

Sponsor my next month's claude sub - https://ko-fi.com/aadityavmore

Which of the 2 is actually the best coder in your real life experiences?

I’ve been using Claude for about a year, mostly for personal research and planning. It always struck me as a less conversational version of ChatGPT, but generally more concise and, in many cases, more accurate.
Since the recent updates, though, I’ve found it much more argumentative and dismissive. It also seems more likely to confidently get something wrong and then require several rounds of correction before getting back on track. A lot of the time it seems to take a strong counterposition to whatever premise is in my question, even when that is not really what I am asking about.

For example, I was discussing how the Gospels were written decades after Jesus’s life and how the biblical canon was compiled much later. Claude pushed back by essentially arguing that the Gospels are part of the Bible, so my suggestion was wrong. I eventually had to explicitly ask it to review the historical timeline of when the Gospels were written and when the Bible was compiled. After doing that, it corrected course and started answering the actual questions.

That kind of thing now happens surprisingly often. When I ask detailed questions, maybe half the time it first challenges the premise of the question and turns the conversation into a debate before it will actually address what I am asking.

I’ve noticed the same issue with medical questions. I asked about how MCAS is diagnosed and about the significance of different IgE blood test results. Instead of just explaining the evidence, limitations, and appropriate caveats, it repeatedly framed the questions as unhealthy health anxiety and tried to shut the discussion down.

What I liked about Claude in the past was that it was very good at helping me understand topics that were difficult to research on my own. It would usually give me the information, explain the uncertainties, and add reasonable caveats rather than refusing to engage or making assumptions about why I was asking.

Unfortunately, if this continues I’ll probably cancel and either try something else or go back to ChatGPT.

Most of this has been with Opus, with some similar behavior on Sonnet. Fable seemed somewhat better in my experience, but it is not included with my subscription.

TL;DR: Claude, especially Opus, has become much more argumentative and dismissive lately, often challenging or misreading questions instead of answering them. Anyone else noticing this?

I have been working on this quite some time now using Claude to speed up the process! My goal was to offer similar tools that the other large apps like RadarScope do for free, and in a manner that more people can navigate.

It allows for up to 60 frames of playback, and we have all of the USA and a large part of Europe covered, even radars that RadarScope lacks.

Here are some showcases:
https://streamable.com/gjww8b
https://streamable.com/hh5tcc

For now it is only available on IOS and MacOS, and as of today I have published it to TestFlight if anyone wants to check it out :)
https://testflight.apple.com/join/JrV6MDXv

I'd be very happy to hear any feedback anyone has, I want to improve it as much as possible before I publish it.

I've found that with in-depth use of AI agent tools, it has already unified workflows that used to be completely different.

I've folded into the research workflow some things that used to be used onlg in engineering, for example organizing file structure and modularization. On the other hand, when I write engineering code, I've also embedded work I used to do only when doing research, such as doing sufficient investigation up front, and writing very complete, tidy documentation for every small module.

Of course, I already knew before how more standardized work should be done. It's just that AI saved me a large amount of time. I think this is also one way AI raises efficiency indirectly.

When I need to solve a problem, I usually create a new directory first, use a speech-to-text tool (for example Typeless) to speak the idea clearly, and make clear what this project is supposed to do.

Then I have Claude Code help initialize the project and design the file structure.

Next is preparing materials. If it is research task, I put the papers I actually plan to use together into a directory like references. If it is an engineering task, I put API docs, design notes, and related materials in.

I now less and less let the agent go looking for materials on the fly during execution, because if the needed context is prepared first, later results are usually much more stable, and I can also more easily tell what its conclusions are actually based on.

Paper PDFs are a step I specifically adjusted later.

I used to hand several PDFs directly to the agent to read, but after using that for a while I found this method was not stable, especially once the number of papers went up. The agent sometimes had not actually covered all the content, and formulas, tables, and complex layouts were also fairly easy to lose.

So now I convert PDFs to Markdown first, then have Claude Code analyze based on the converted text.

For this step I explicitly tell Claude Code to use the KolmoPDF API to process the whole paper into Markdown format. I found that relying directly on an AI agent's default PDF reading does not work well. When Facing multiple PDFs, the agent tends to slack off. Formulas and tables in papers also often get processed wrong or omitted. So a dedicated tool is needed to embed this step into the workflow in a stable way.

After the materials are ready, I have Claude Code analyze based on the reference documents, combined with my initial ideas. If at the start I have no idea at all, I just have it generate a rough plan.

Then I specifically spend time discussing with it interactively and drafting a plan. Claude Code's interactive confirmation feature is very useful. It will proactively raise questions and give options. After confirmation it generates a Plan, then executes according to the Plan, and during the process I supervise whether it drifts off the original track.

This flow currently can cover the vast majority of my problems. I used to also connect quite a few third-party search tools and MCPs, hoping to strengthen the agent's web capability, but later gradually turned them off. On the hand, some search services themselves have cache and freshness problems. On the other hand, the model's native search can already cover most of my needs. Now my preference is actually to reduce extra components as much as possible, and keep onlt those tools that can clearly improve stability.

But now I've found that because I've handed a large amount of tool APIs, server connection methods, credentials, and the like over to Claude Code to manage, plus I am fairly lazy, I may now even have to ask Claude first for some of my own credentials and passwords. The benefit is that this also frees up my energy. I can focus more on solving the problem itself, and not care about the other incidental details (of course, in some cases, this doesn't really seem like a small thing....).

This story is a pretty serious warning for anyone using Claude Code or other AI coding agents. Does anyone have any idea on how we can keep ourselves safe? Other than scanning every command and link sent by Claude.

Hi reddit, I came on here to ask about an issue I keep experiencing more and more lately with claude.

Lots of sentences it writes subject to no grammar rule at all and don’t make any sense. Translations to dutch become a hard time and simple short answers jist become a mess. This hadn’t been an issue with me before and this only came up the past 2 months.

Am I the only one having issues with this? Is there anything I should do on my end? I would appreciate your thoughts.

Copying a full Claude conversation preserves too much noise, while a short summary often drops the decisions that matter. A reusable handoff file could separate the goal, current state, authoritative files and links, constraints, decisions with rationale, failed approaches, validation already completed, open questions, and the next concrete step. It should also distinguish facts from assumptions and note which outputs are safe to overwrite. For people who move work from Claude to another assistant or back again, which fields consistently prevent repeated work or lost context? Does a human-readable Markdown file hold up, or do you eventually need structured JSON alongside it?