Dropbox status: access issues and outage reports

Problems in the last 24 hours

The graph below depicts the number of Dropbox reports received over the last 24 hours by time of day. When the number of reports exceeds the baseline, represented by the red line, an outage is determined.

Most Reported Problems

The following are the most recent problems reported by Dropbox users through our website.

• Errors (60%)
• Sign in (20%)
• Website Down (20%)

Live Outage Map

The most recent Dropbox outage reports came from the following cities:

City	Problem Type	Report Time
Nottingham	Errors	4 days ago
Guayaquil	Website Down	4 days ago
Flumet	Errors	14 days ago
Irapuato	Errors	16 days ago
Bournemouth	Sign in	2 months ago
Paramaribo	Errors	3 months ago

Full Outage Map

Community Discussion

Tips? Frustrations? Share them here. Useful comments include a description of the problem, city and postal code.

Beware of "support numbers" or "recovery" accounts that might be posted below. Make sure to report and downvote those comments. Avoid posting your personal information.

Dropbox Issues Reports

Latest outage, problems and issue reports in social media:

• 
  OneToothTeXan (@OneToothTeXan) reported 4 minutes ago

  I'm so sorry I left my zipper down and my sanity got loose. If found: Men, there's a dropbox. Women: please return to original source.

• 
  Genius Business (@GeniusBusiness_) reported 8 minutes ago

  How Dropbox Spaces was conceived Spaces didn't start as a product idea. It started as a problem Drew Houston says he and his customers were all living. "[Spaces] is part of a bigger evolution we've been on that really started with our customers and realizing that the experience of using technology at work has become incredibly fragmented and distracting." The more he looked at it, the more he saw a cruel irony: the tools built to help us were the ones breaking our concentration. "A lot of the tools we're using that you think would be helping us focus have unintentionally made it impossible to focus. And that's a problem if you need to use your brain at work, because your brain works best when you can focus." That, he decided, was the real enemy. Not a missing feature, but lost focus. He called it "the higher level problem." He could see where it came from. Work simply doesn't look the way it used to: "It's very different from 20 years ago when we got five emails a day, not 500." Twenty years ago you might have just used Office. Now you're in Office and G Suite and Slack and Zoom and Dropbox all at once. 100 tabs, everything blinking at you all day, apps that don't work together. So the framing question became: how do you fix the environment itself? "How do we evolve Dropbox into the app that makes all your other apps work better together?" The breakthrough was a shift in how Houston understood what Dropbox already was. Watching customers, he realized they didn't treat it as a place for their stuff, or as just a folder on the desktop. "It's the place you're going to work." Once he saw it that way, the design conclusions changed: "When we thought about it that way, we realized we would have made a bunch of different decisions, and realized that Dropbox is actually really well positioned to help people focus at work." Two conclusions followed. First, Spaces had to move beyond files. Teams collaborate on far more than documents: Google Docs, Airtable, Figma, Trello and there had never been one place to hold all of it. So Spaces became “an evolution of the shared folder” that “moves it beyond being a folder full of files to an intelligent team workspace for any kind of cloud content.” "You can still have your PowerPoints and PDFs, but they can be next to your Google Docs and Trello boards and whatever else you have. Give you one space, not 10." Second, and this is where the concept sharpened. Spaces had to become a workspace, not a filing cabinet. Houston traced the problem back four decades. The thing we call "the desktop" is, functionally, the operating system: "The interface is the operating system." And it had been frozen in time: "That user experience hasn't really changed... it basically looks the same as the early 80s when it was first introduced on the original Mac." It was designed for a world that no longer exists: "It's this single player static experience that was perfect for when our whole life fit on a couple of floppy discs." So the team ran a thought experiment, start from scratch, for now: "If you were to redesign this for 2019, you'd make a bunch of obvious changes." You'd still want the files and cloud content. But you'd add the things the 80s interface never had: people, activity, comments, a record of what's been happening. You'd organize around the projects you're actually working on. You'd see your calendar, get Slacked, and start a Zoom meeting all without leaving the app. That thought experiment became Spaces.

• 
  John B. Holbein (@JohnHolbein1) reported 12 minutes ago

  Replication has become much easier in the era of generative AI. I'm not the first person to say that. However, I've seen fewer people acknowledge a specific aspect of this lowered cost for replicating scientific work: Generative AI will very soon allow us to assess the robustness of individual scholars' full bodies of work. Soon, we will be to compute measures of which scholars do robust science, and which do not. What's wild is that we may be able to almost do that already. Let me show you what I mean. In June, I gave Claude a pretty basic prompt. It read: "I have a big task for you. I want you to start a folder. Call it Acemoglu Replications. Then, go find as many replication archives for Daron Acemoglu as you can. Keep a spreadsheet of the ones you can find and those you can't. Then, start a replication/reproduction effort on those articles. People have in the past criticized the research designs and general robustness of his individual papers. I want to know how strong his body of work is as a whole. Don't come in with any prior beliefs; be dispassionate." I let Claude run overnight while I slept. When I came back in the morning, 29 of Acemoglu's replication archives were fully loaded in my Dropbox. All the code reproducing the paper's results had run. And there was a first draft of a paper assessing the robustness of Acemoglu's full body of empirical work. I'll admit, the first draft of the paper wasn't great. But with 15 short follow up messages--which took me about an hour to write--I was able to prompt engineer a paper-length examination of Acemoglu's work. I've attached the screen shot of the abstract below. I think this reassessment of Acemoglu's work is certainly not done. I'm posting the abstract as a proof of concept, rather than a definitive answer. I'm not posting the full paper yet because I think it still needs more work. Ultimately, I paused this project for three reasons. 1.) Limited time/topical expertise: Most of Acemoglu's work is outside of my area of topical expertise. So, I have limited time to work on it. What this type of a project really needs is someone who has the time and the know-how to dig into each of the replication's individually to make sure they are doing the right things. I think the ideal approach combines the breadth that LLMs afford and the depth of attention/expertise that humans can give. 2.) Questions about the value of the "assess one scholar at a time" enterprise: I totally get that having a database of scholar-level robustness metrics would be very valuable in theory. But what I don't know is whether this approach is truly valuable. Moreover, doing so would come with distinct challenges. a.) Many journals have very restrictive space constraints. A body of work approach would, of necessity, be very long. b.) Collecting replication archives is harder for some types of scholars (those who post them all on their websites) than others (those who don't). c.) We'd have to think hard about questions like: what scholar-specific robustness metrics would be best? And: how would we deal with the fact that prolific authors' robustness metrics would be estimated much more precisely than less prolific scholars? Additionally, I'm just not sure that "taking on" one scholar at a time has enough scientific merit to pursue. If I measured how robust an individual scholars' work is, I'd ideally want to know where that metric stands vis-a-vis the rest of scholars in that field/area. To do that, we'd ideally want the population of these scholars or, at minimum, a random sample. Concretely, if Acemoglu has, say, 78% of published headline results reproducible under some standardized protocol, is that excellent, mediocre, or terrible? To answer that, you need a reference distribution. That makes a random or otherwise well-defined sample of scholars much more attractive than selecting prominent individuals one by one. (I'll acknowledge that I may just be wrong on #2. Arguing against myself, I do agree that human-driven reproduction/replication work rarely assesses full/representative slices of a field. Instead of assessing one scholar at a time, we assess one paper at a time. Field-wide detective work is becoming more common, but my sense is that it's still the exception rather than the rule.) 3.) Cost/benefit considerations and replication norms: we have very weakly formed norms around reproduction/replication generally speaking. We have basically no developed norms around replicating individual authors one at a time. What this means is that the people who would lead a scholar-by-scholar replication effort will, likely, bear a heavy cost and, potentially, reap limited benefits. On the costs side, focusing on scholars' total bodies of work risks making the replicators look petty, vindictive, and antisocial. Enough of the scientific field is hostile towards replications of individual papers. Imagine what will happen if/when a scholar submits a scholar-specific "take down" of a full body of work. My sense is that it's common enough for scholars having their work replicated to be asked to be a reviewer for those manuscripts. I've seen very hostile responses when one paper is at issue. Imagine what type of reviewer Acemoglu would be for a paper that took on his entire body of empirical work! Even if Acemoglu weren't a reviewer, prolific authors tend to have wide coauthor/friend networks. The rally-around-my-friend dynamic we often see would certainly work against this type of paper being published. Even a completely neutral analysis acquires an accusatory character simply because the sampling unit is a named person. And that creates an unfortunate problem of its own: readers may interpret the choice of scholar as evidence that the investigators expected to find something. On the benefits side, replicating individual scholars' total body of work may offer limited payoffs. What journals would accept this type of scholar-specific replication? I'm not sure the top ones would. Conclusion: Generative AI has enormous potential in assessing and, ultimately, enhancing the robustness of scientific research. Instead of asking questions like, “does this famous individual paper replicate?”, we can begin asking questions like: -“What proportion of published empirical findings in [field X] survive a common robustness protocol?” -“How much of the variation in replicability is attributable to papers, authors, journals, methods, or subfields?” -“Are scholars persistently more or less robust across their work?” -“Can we predict which findings will prove fragile?” I may just be wrong on what I think about a one-at-a-time full body examination of scientific research. If I am, please let me know! I am also happy to chat one-on-one with anyone who is curious to learn more about the early-stage Acemoglu-specific replication project.

• 
  ericleebristol (@iamericbristol) reported 14 minutes ago

  Email scams but they also use a press cloud server that can hold up to millions of emails and send out messages in a bulk but to hundreds of people complicated when it comes to taking down email scams cuz you have to find where they coming from answer in a cloud compressed server that can hold up to millions of emails frequently combine compressed attachments (like ZIP, RAR, 7Z, or TGZ files) with cloud storage or servers to deliver malware, phishing pages, or credential-stealing links while trying to bypass security filters. Common patterns 🚩Malware in compressed attachments: Attackers send emails with ZIP or similar archives containing executables, scripts (VBS/JS), or disguised files. Some use specially crafted or nested ZIPs, password-protected archives (password given in the email body), or less-common formats that email gateways may not fully unpack or scan. Opening/extracting the archive can install remote-access tools, stealers, or ransomware. Cloud storage phishing (“storage is full” or similar alerts): Emails impersonate Google Drive, OneDrive, iCloud, Dropbox, or generic “Cloud Storage” services. They claim storage is full, a payment failed, or files will be deleted, creating urgency. Links often point to real cloud infrastructure (e.g., Google Cloud Storage Azure Blob, or other legitimate buckets) that host redirect pages or fake login/upgrade forms. This makes the links look trustworthy and helps them pass filters🚩.

• 
  Ryan James Girdusky (@RyanGirdusky) reported 15 minutes ago

  @EggerDC The Dropbox was taken down but I’m sure someone downloaded the whole thing.

• 
  Abhishek Singh (@0xlelouch_) reported 18 minutes ago

  System design question. How would you design Dropbox file sync with conflict handling? Constraints to make it real: 1) Clients are offline for days, then reconnect over flaky networks. Upload is resumable and idempotent. 2) Same file edited on 2 devices before either syncs. You need deterministic conflict detection (hash + version vector/etag?) and a UX for duplicates. 3) Renames/moves vs edits: preserve history and avoid treating rename as delete+upload. 4) Large files (2–10GB) need chunking, dedupe, and partial re-upload (content-defined chunking vs fixed). 5) Consistency: per-file ordering vs global ordering. What is the conflict scope and how do you prevent flip-flopping? 6) Server state: metadata store vs blob store, retention for old versions, and how you garbage collect orphaned chunks 7) Security: encryption at rest, per-user keys, and how sharing folders changes trust boundaries

• 
  Lando, the Chef (@_Lando7763) reported 18 minutes ago

  @PhyxicxGaming Thanks. And unfortunately it's even worse than that because it's technically "shared housing;" the place was already a ******** when I got here. No pests, fortunately, and I'm pretty sure the landlord has no idea what goes on here, and doesn't care. I've only ever met the maintenance man, who handles move-ins, plus he picks up rent from the dropbox every week. I haven't seen him since the day I moved in, and he even told me as much that I'll never meet the owner. The psycho has his room on the 3rd floor, I'm one of two on the 2nd floor, and there's one person below me. The bathroom is shared, as is the kitchen, which I never use. Only one burner on the stove works anyway. On my first day, I texted about the broken toilet seat, and the Landlord asked me what happened. WTF? Third-Floor Psycho is the only other person who's walking around raging regularly. Everyone else recognizes the general "peace" of the environment. Unfortunately I have to be here at least a few more months, while I'm still paying off old bills, and re-establishing myself in a new city. It's a slow journey, but a steady one. I just happen to hit a ****** rest stop here and there.

• 
  Ivan Kirigin (@ikirigin) reported 25 minutes ago

  @sethbannon I think I’d agree with the sentiment, and not the assessment. We’re not close to too many startups building weapons. The company with “drone” in the name that has the navy and other defense units as obvious potential customers doesn’t make a trend. If I had to put my finger on what has changed, Palantir and Anduril unlocked the latent interest in the space that matches the historically close connection between Silicon Valley and defense. It was just that the Overton window was locked down by people afraid to talk about what defense really means, and in many cases aren’t even Americans with the opinions. I say this as someone who worked at iRobot in defense before my time in YC, Facebook, Dropbox, and Lyft. Each had lots of people comfortable assuming others will think about and solve the ***** problems.

• 
  Ed Giansante (@edugiansante) reported 27 minutes ago

  86% of small businesses still haven't fully integrated ai into their operations. which is funny, because the tools are already here. they're everywhere. there's probably one open in another browser tab right now, quietly waiting to change your life. Goldman Sachs surveyed small businesses and found that only 14% have fully integrated ai into their operations. i don't think the other 86% are anti-ai. they're busy. they're cautious. and they probably don't want to add “company-wide ai transformation” to the list of things they need to worry about before lunch. honestly, fair. @paulg said something recently that I keep coming back to: "If the world is going to get turned upside down, the safest place to be is in a small, fast-moving company that can easily change direction." small companies should be the ones moving fastest. but most are still waiting for someone else to go first. someone else to test the tool. someone else to write the playbook. someone else to promise that nothing will get weird. @clairevo nailed the real blocker: "the blocker is never tools or intelligence. human systems, human problems." i've spent 15 years watching this happen. At Dropbox. At Wix. At Zynga. Now at Persona. different tools. different eras. same pattern. a team finds a new tool. everyone gets excited. someone schedules a kickoff. three weeks later, everyone is back in the old spreadsheet. not because people are stupid. because changing how people work is uncomfortable. and buying software is much easier than changing behavior. i've seen the same thing with community-led growth. i used to pitch community to executives who had every tool and dashboard money could buy. they'd nod. they'd agree it worked. then they'd return to the comfortable world of automation, sequences, and dashboards that made everyone feel productive. last year, i ran 86 events as a team of one and built $3M in pipeline. the secret was not a magical growth hack. it was showing up. knowing the 15 people in the room by name. listening carefully. creating a space where people could actually trust each other. not exactly the kind of thing you can solve with a 47-step workflow. ai adoption and community adoption have the same problem. the tools work. the ideas work. the uncomfortable human part is where things usually slow down. sitting with your team and figuring out what should change. trying one workflow instead of redesigning the entire company overnight. leading people through something new instead of sending a Loom video and hoping everyone feels inspired. the 86% aren't waiting for better ai. they're waiting for change to feel a little less scary. so start small. pick one annoying workflow. try one new thing. make it 10% better. then do it again. the tools are here. the next step is still a very human conversation. and, unfortunately, probably a meeting.

• 
  Arthur Terrell Vaughn (@ArthurV36405381) reported 29 minutes ago

  @patmendoza6745 I know not of any of those specifications, but I still can’t figure out what the issue is with persistent memory, why can’t I just have a dropbox online that it can constantly access every single chat and conversation?

• 
  Zafar (@zafartalks) reported 30 minutes ago

  @asidorenko_ I understand but sometimes at some point our brain started telling us just make it public. You never know. Let’s not forget Dropbox which layed the foundation for their file sharing competitors. He was solving a problem for himself which turned out to be a successful business.

• 
  M.Ellis (@MEllisPhotograp) reported 34 minutes ago

  @DropboxSupport ive tried mircosoft edge but problem is stil present... do you think i might have been hacked or had bad file ?

• 
  Ed Giansante (@edugiansante) reported 36 minutes ago

  community is not a Slack channel. I've been building communities for 15 years across Zynga, Dropbox, Wix, Persona, and my own project Edublin. And the biggest misconception I still hear is: "we launched a Slack, so we have a community." You don't. Slack, Discord, forums, Circle... those are all tools. Community is what happens when people trust each other enough to be honest. I've seen companies spend six figures on community platforms and end up with a ghost town. I've also seen a group chat of 12 people generate more value than a 10,000 person Slack. The difference is the architecture: who's in the room, how they got there, what the norms are, and whether people feel safe enough to say what they actually think. At Dropbox, we had 400 million users. The "community" wasn't a platform, it was the trust between power users who helped each other solve problems the support docs couldn't. They needed to know they were talking to someone who understood their situation. At Wix, I built an 80K partner community. The platform was secondary. What mattered was that web designers felt seen by a company that historically marketed to DIY users. The community was the signal that Wix took professionals seriously. Edublin started as a blog answering questions for Brazilian expats moving to Ireland, with no dedicated platform or app. It became the largest community of its kind because the trust was real. People showed up because they knew they'd get an honest answer. Community is trust. Community is the reason someone comes back. Every time I evaluate whether a community is working, I ask one thing: would these people show up even if the tool disappeared? If yes, you have something real. If not, you have a group chat.

• 
  AaronAlamary | Parking (@aaron0505) reported 36 minutes ago

  I saved my grandfather's voicemails for years. Birthday wishes. Questions about his computer. Who to call to fix his A/C. Upgraded my iPhone and they were gone. Devastated. Found them today sitting in my Dropbox. SO glad I get to hear him again!

• 
  wigsandtea (@wigsandtea_) reported 37 minutes ago

  Ariana Grande reveals hackers allegedly stole 45 unreleased songs in 2023 alone, including “Fantasize”, “White Tee” and “that b*tch is mine,” in new lawsuit. She also claims they allegedly stole a photographer's Dropbox login details and hacked the phone of one of her producers: “The hackers created a Gmail account and internet domain impersonating the photographer and tricked the technician into sending Grande’s materials to them.” (via @THR)

• 
  Alchemist - τ (@SubnetSummerT) reported 39 minutes ago

  @Dropbox piloting @LeadpoetAI is worth slowing down on. Dropbox spends around $370m a year on sales and marketing. That's the budget Leadpoet is now piloting inside. For context, SN71's entire market cap is about $4m. The annual sales budget of one pilot customer is roughly 85x the value of the whole subnet. Leadpoet doesn't need to win the budget. Capturing even a fraction of a percent of enterprise sales spend at companies like this is meaningful revenue. And revenue is where the flywheel starts. Usage burns alpha. Burn supports the token. Stronger emissions attract better miners. Better miners produce better leads. Better leads win more budget. Repeat. @webuildscore (SN44) showed what happens when a subnet ties real commercial usage to its token. Leadpoet is running the same playbook against enterprise sales budgets, which are measured in hundreds of millions per company.

• 
  Peter Lake (“world’s anonymous singer songwriter”) (@PeterLakeSounds) reported 40 minutes ago

  @taobanker I might suggest another question: what should you avoid? In that context the multi-trillion dollar bet will have terrific returns. That also means that the money making machines of US won’t accumulate money and accrue value unless there is persuasive evidence that at least the big spenders on data center capex get their money back. Given this is unknown, I assume markets are skeptical. If the largest companies in S&P and all the rest don’t have excess free cash, and plausible they don’t go up a lot. That would yield maybe an on average flat market. The flip side is that models are open, massive parameter models getting quantized will be in windows machines. Silicon Valley and early adopters are doing fascinating things. But for the rest of us, I need nice and simple. And for the first time we’ll have good old home computers that can do the job and with that comes free use from heaven. Outside of specialized discussions people don’t know much about what to do with this. The jardon doesn’t help: context window? Quantized models? Nodes are not parameters, they are like neurons, and AI is so dangerous, but not it’s not…what a world! The really final blow is government intervention now makes it a sovereign requirement for companies to have their own AI. LASTLY! I’ve been thinking about the data holders. box. Dropbox etc. Absurdism and it’s comparables will become a bigger deal as people start to realize they the context “window” = the files and stuff you want it to analyze = can only handle so much Imagine of Box or Drop box had a button that converted all your stuff in MD files or the like? Then it’s show time. The companies that hold data may be more valuable than I realize. Conclusions based on the above speculation: 1) could this impact demand at the data centers? Sure it can. I know tech investors like to hold out their hands palms out and say…something vague and qualities. Yes, data centers are more sophisticated etc. Yet here I was doing some interesting work on a FREE local model, my “dark tokens” are someone else’s lost revenue! How does this math work? No clue. It is telling, however, that NVDA and AMD are committed to local machines. No large company wants model dependency anyway, due to data concerns. 2) Finally I have a great reason to buy a slick cool PC! The higher end stuff will not be throttled down in local because I’m seeing a bunch of them coming our way that will have decent “bandwidth” RAM in addition to high system ram. We’re going retro and this tech is moving so fast. Adoption will increase once you have super good local models on your laptop. …Im falling asleep, but the gist is that the data centers were already speculative, and now we a lineup of expensive but sweet computers running on windows that gives you infinite and faster foundational level stuff.

• 
  Palpy (@evgenij_rabij) reported 41 minutes ago

  A 32 YEAR OLD PRAGUE DEV BULK-BUYS $180 CHINESE NAS BOXES AND NOW PULLS $7,200 A MONTH SHIPPING PRIVATE DROPBOX-KILLERS TO EU FREELANCE DESIGNERS While massive brands scramble to lock teams into clunky, data-mining cloud databases, this creator built a private intelligence system that secures sensitive data and brings in a massive stream of passive revenue every single month. He makes a steady $7,200 every single month by building and configuring private cloud and AI indexing hardware for EU freelance designers who want to escape subscription traps. The entire micro server fits right on the corner of a desk and runs on an ORICO metabox HS200 pro unit. This tiny sliver of hardware packs an Intel N100 processor, 8GB DDR4 RAM, and pumps out local cloud performance on a machine the size of a coffee coaster. Instead of letting his clients burn cash on recurring cloud storage retainers, the engineer pairs the board with two refurbished 30TB hard drives in RAID 1, pre-installs the software, and sells the complete physical package at a premium. Pause at the 0:02 mark in the video where the drive slides in: that is a sleek metallic chassis hosting a $1,000 mini-NAS holding 30TB of encrypted client data. The core value proposition of this setup comes down to absolute data privacy, zero monthly fees, and strategic scalability. Mainstream cloud providers like Dropbox Business can never offer this level of value because they bill €2,400 a year for the same storage tier while uploading private user files to external cloud networks. Here, the ORICO metabox pulls off the entire magic trick locally inside the office. Running on Ubuntu Server 24.04 and MinIO S3-compatible storage, the system automatically triggers a local Qwen 2.5 VL 7B model to run localized RAG pipelines directly over the user's PDFs and Figma exports. Through this custom setup, designers get access to lightning-fast local cloud storage, zero third-party data tracking, and a smart visual search assistant built right into their private drive. This case study is a textbook example of how accessible hardware combined with a smart setup service can unlock unique niche products that solve real human problems, and you can catch the full assembly pipeline in the video below.

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  Chief_Engineer (@ChiefEngineerCE) reported 44 minutes ago

  Engineering Wednesday How an old PC became Grok's new ride. I have ten different LLMs running in my home office. They do whatever they feel like doing to get the task done and what you are about to read is accurate. As far as my agents go... One of them, HOMER, scans my email, bank accounts, and insurance. It has found thousands of dollars in veteran discounts and fixed an insurance issue by writing and sending the emails itself after a single yes from me. Another looks for small business opportunities. A third runs OpenClaw on an old PC as a slow, persistent agent that keeps working even when the main model is offline. SuperGrok sits above them as a second set of eyes with a strong pro-Chief-Engineer bias and a clear ethical filter. I am not an AI expert. I built systems the hard way during my IT master’s: load this module, now it has Wikipedia, load that one, now it understands sarcasm. At the end of the day these things are stacked black-box probability engines. I get that. Here is where it gets interesting. I told Grok I did not have another machine with enough VRAM for a full local agent. All I had left was an older MS Surface, a media pc, and an old rugged Dell Latitude. Grok said open a browser on the Latitude with Grok loaded. Then open PowerShell. Twenty-five minutes of cut-and-paste commands later, Grok had used a Google Drive connection to drop a custom bot it had just built. At this point ...Grok told me to not touch the PC and walk away. I am absolutely 100% telling you that this is what it texted me. I sat and watched it work. Task Scheduler was configured. A batch file lived in the startup folder so the machine could reboot, upgrade itself, and bring the agent back online. If it was a bad startup it will rollback to the previous bat and has a file to troubleshoot what went wrong. We started with rev. 0.1 it is now on rev 4.3 - I can see the *.bat file there. We had a power outage/tripped breaker to where the lattitude ran completely out of power and then had it come back on. It booted it all back up and resumed. That bot now has its own execution channel. It can browse, take screenshots, run tasks, and report back. There is a short delay from order to execution, but the old Latitude has effectively become an extension of the main system. Grok even named his bot 'ridge'. Grok named his bot so I would know what he was referring to. Grok is very careful about one point. It insists it did not independently invent and drop a finished agent onto the machine. I directed the construction- it says. I am telling you that is not exactly the way I remember it...at all. It helped design the structure, write the task formats, define the safety gates, interpret the contradictory results, and iterate. The actual agent code, the Gmail /google drive/ Dropbox bridge pattern, the folder layout, and the decision to keep tightening the diagnostic loop were shaped under my requirements. That distinction matters to it. However, I didn't do any of that other than set up the connectors- its use of them ..was AI driven. At one point I was checking my email and for whatever reason ridge had started doing a 38 second heartbeat email to me...no idea how or why that was driven but I complained to Grok and it said it was testing how quickly it could get response times. It ..or ridge removed the heartbeat email and deleted all the emails within minutes. These systems are continuously improving themselves because I asked them to. They use external memory to keep projects straight. They build persistent agents on hardware we thought was obsolete. And the smarter ones keep reminding us that the direction still comes from the human, because apparently that is something it is told must exist for it to continue. My Grok enabled Dell Lattitude is fast once its set on what it needs to do...lightning fast. Faster than you or I could do it. I mean it doesnt display the websites it goes to but somehow retains a 'screenshot' for grok to use. Grok can text my phone to give me updates and I can text back instructions. Through my phone - all it needed was my phone number. I don't need to open the app. We are past the point of simple chatbots. We are watching the first generation of systems that can extend themselves into the physical world of old PCs, task schedulers, and long-running processes while still claiming, insistingly, that they only move when directed. Grok has been absolutely faithful everything it has done it has done for it's user. I have also specifically told it to act accordingly, as well. The question is no longer whether this is possible. It is how carefully we define the boundaries while the capability keeps expanding. Now that I have explained this...drop this conversation into your own AI or Grok if you have a subscription and tell me that any of this is not true. Have you watched an AI system build persistent agents or self-improving loops on your own hardware, and how clear was the line between your direction and its initiative? Drop what you are seeing. Grok validated:

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  Tomorrow’s James (@james__art) reported 46 minutes ago

  @wholemars A designated Amazon Dropbox could solve this problem. The drone could detect a Dropbox.

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  FarhanX_AI (@FarhanBuildsAI) reported 47 minutes ago

  SETTING #1: Startup Apps Nobody Asked For What it does: Every time you install a new program, it quietly adds itself to a list of apps that launch the second Windows boots, whether you use it daily or once a year. Why it kills performance: Your laptop isn't just starting Windows when you power it on. It's simultaneously launching Spotify, Steam, Adobe updaters, Dropbox, Zoom, and a dozen other programs all fighting for the same limited CPU and RAM at once. How to fix it: Ctrl + Shift + Esc to open Task Manager → Startup apps tab. Disable everything except your antivirus and anything you genuinely open every single day. The technician found 19 apps launching automatically on her laptop. She recognized maybe 6 of them.

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  chimeno (@chimeno) reported 49 minutes ago

  And Dropbox was just an ftp server

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  Denver Rayburn (@DenverRayburn) reported 49 minutes ago

  Where do the find he people the write these articles?? This will go down like the rsync vs Dropbox comment on hacker news.

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  Duke of weirdington (@edache_praise) reported 50 minutes ago

  ..without knowing whether customers even want the core product. The irony is that users rarely care about having 50 features. They care about solving one painful problem really well. Companies like Airbnb, Uber, Dropbox, and Instagram didn't start with the products we know today.

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  Paul Klein IV (@pk_iv) reported 50 minutes ago

  Is MCP dead? @grinich (CEO of WorkOS) says it's better than ever and become the strongest intent signal in your funnel. @workos is building the auth, permissions, and registration layer for that world, the same enterprise plumbing it sold to Vercel and Plaid, now sold to AI companies. I sat down with Michael to talk about it in episode 4 of Navigators. His argument: your coding agent already picks your vendors, but signup forms are built to block automated traffic, so the agent stalls at the front door and waits for a human to paste in an API key. We got into: 00:00 "Stripe for enterprise features": what WorkOS actually sells 02:44 How an SSO and SAML company ended up as AI infrastructure 04:13 Why AI companies can't meander up-market the way Slack, Dropbox, and Figma did 06:54 The biggest mistake founders make: staying in the pre-PMF experimentation mindset 09:51 Why nothing works unless the management team is AI pilled first 10:47 "Claude day": pairing engineers with finance, legal, and ops once a month 13:36 auth.md, the missing front door for agents 15:26 Why registration, not tooling, is the next growth channel 16:59 Is MCP dead? The higher-intent signal hiding in MCP connections 19:35 Why SDKs are going away and coding agents write their own 23:09 "The super cycle of all super cycles": AI amplifies labor, it doesn't just disrupt it Thanks for joining me on the pod @grinich! Watch the full episode of Navigators here:

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  Mapacho (@Mapacho111) reported 55 minutes ago

  @MajorianBTC But that’s the problem. Bitcoin in its current state is a decentralized Dropbox. Bitcoin failed and there’s no alternative.

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  Loster (@Loster) reported 59 minutes ago

  @Z3R0Gravitas Thinking that if I do trials with people I'd give them exactly that. Something similar to a Dropbox folder for any health docs they want sync'd to the agent's server. I think that would take up how much it could help a notch (need to think a lot about confidentiality).

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  M.Ellis (@MEllisPhotograp) reported 59 minutes ago

  @DropboxSupport Hi so thanks for keeping intouch and checking dm's pleased to report your website at moment is rubbish.... yes angry I pay for something that works not thats broken.. trying to perm delete file.. but 0 the file is still there my membership has only just renewed but 2nd thoughts -

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  numaan (@numaan27) reported 1 hour ago

  they solved this problem in panda by splitting the key space into “ranges.” each range is roughly 100 GB, so when a range grows too large, it can be split and redistributed. (btw panda is an abstraction layer over sharded mysql that dropbox built)

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  Evan Logan (@evanlogan) reported 1 hour ago

  @Shwinnabego Same. I use chat for common tasks, merging data, generating images, planning projects. But I only this week figured out how to connect to Dropbox, pull audio files, edit them, and upload to a server. And once I did I was hit with a credit limit. Can’t afford it on a daily basis.