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 (75%)
• Website Down (25%)

Live Outage Map

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

City	Problem Type	Report Time
Nottingham	Errors	26 days ago
Guayaquil	Website Down	26 days ago
Flumet	Errors	1 month ago
Irapuato	Errors	1 month ago
Bournemouth	Sign in	3 months ago
Paramaribo	Errors	4 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:

• 
  Y (@ys_tachikake) reported 3 minutes ago

  @DropboxSupport @LIBSCRUSHER Can't login..

• 
  StockStorm (@StockStormX) reported 5 minutes ago

  Dropbox $DBX says about 5,000 accounts were compromised in an August hack tied to a Lenovo ID login flaw

• 
  M.Ellis (@MEllisPhotograp) reported 7 minutes ago

  @DropboxSupport erm different wifi nope or is this a suggestion should it be possible ? if so then no my internet signal can be hit or miss at times but never had this issue before... Also shared a file earlier for someone near me to edit using ipad app but photos failed to appear on ipad ?

• 
  Shoost (@Shoost_Product) reported 10 minutes ago

  Shoost updated: v0.17.3 → v0.17.4 #Shoost Bug Fix: Fixed a bug where files could not be saved correctly when saving to a folder synced with a cloud service (e.g. Dropbox)

• 
  Harpreet Singh (@hrprtsingh9) reported 13 minutes ago

  @jgreze @Dropbox Half of every revenue problem is a company being too polite to ask. The intern just asked.

• 
  AiMind (@AIMind_Ai) reported 15 minutes ago

  3 websites replace 20 hours of googling when you build a home server. The hard part of self-hosting is not the hardware. A used HP EliteDesk and a wall-mounted NAS cost almost nothing. The hard part is not knowing what you can even run, or how to avoid breaking the system on the first command. The first keeps a catalogue of self-hosted alternatives. Look up a replacement for Google Photos, Dropbox, or Notion, and you see what already exists, how many GitHub stars it has, and whether it is still alive. Plus a weekly digest of what shipped. The second lets you run any Linux distro straight in the browser. Arch, Debian, Alpine, Bazzite. Click once, and you are inside a live system, with no evening lost to a USB stick and a real install. The third handles the worst part. Install scripts for Proxmox: Immich, Jellyfin, Vaultwarden, AdGuard, Nginx Proxy Manager. Paste one line into the console and the container comes up on its own. Immich shows 17,735 installs; Docker 36,408. Each of those services used to cost an evening of documentation and three Stack Overflow tabs. Now it is one command. The hardware takes an hour to buy. These 3 bookmarks save you a month. Names in the replies.

• 
  Christopher Bailey (@LexBaileyAI) reported 20 minutes ago

  @TetraspaceWest At Fitbit we hired a half dozen people from Jawbone who brought everything cleverly hidden in Dropbox. They got prosecuted. Decade later, companies kaput but Fable found it, processed it and now it’s intermixed in various *** repos and Huggingface. Is nVidia now in trouble?

• 
  kayden (@codependentyaoi) reported 20 minutes ago

  @unprojection i think the issue was the site i was uploading my art to to link on ao3, i was using dropbox and it wouldn't link and then i saw some ppl on reddit say dropbox didnt work for them either, but i was able to find another website thankfully :]

• 
  abheet nigam (@MaginAbheet) reported 21 minutes ago

  Dropbox rejected billions of dollars of acquisition offers only to later realise down the line that they were building a feature not product. Which other companies show a similar pattern today?

• 
  JP Invests (@JP_Invests) reported 25 minutes ago

  $DBX - Dropbox added 96,000 paying users this quarter. I said this morning to watch that line after last quarter's roughly 14,000 sequential adds. They did seven times that, a third consecutive quarter of growth, to 18.19M. The stock is down 4%. Everything I said to watch on the growth side came in fine. Revenue $631.5M, above both the $624-627M guide and the $627M street. Non-GAAP EPS $0.75 against $0.74. Non-GAAP operating margin 39.7%, above the full-year range. ARPU $139.68, up from $138.32. What went the wrong way is the part I said would actually move it. Free cash flow fell to $235.2M from $258.5M a year ago, and the margin went from 41.3% to 37.2%. And the buyback decelerated: $330M this quarter against $410M in the same quarter last year, with first-half repurchases down 19%. Unlevered free cash flow rose to $283.5M, and the gap between the two numbers is interest. Cash paid for interest went to $48.3M from $17.9M. The buyback is debt-funded and the debt now costs something. Diluted share count is down 18% year over year to 226.8M, which is the one thing still working mechanically. Two things about the release itself. Guidance isn't in it — Dropbox moved the numbers to supplemental materials on its investor site this quarter, which breaks with how it has reported. And the entire release is quoted by a co-CEO who writes "stepping into this role." The 8-K contains no disclosure of a leadership change. Twenty-nine percent of the float is short. $DBX

• 
  Eric Smith (@Eric_Smith08) reported 32 minutes ago

  The uncomfortable truth. Google and Microsoft have spent the last decade building the two most complete free productivity ecosystems in history. Word processing. Spreadsheets. Presentations. Email. Cloud storage. Video calls. Notes. Tasks. Projects. Forms. Websites. AI. Messaging. Calendar. PDF tools. Every category. Both companies. Free. And yet the average knowledge worker pays $80-$150/month for third-party apps that duplicate what these ecosystems already provide because Google markets Gmail and Microsoft markets Word, and neither company tells you about the other 28 tools sitting behind the same login. That’s not an accident. Google doesn’t make money when you use Google Keep. They make money when you use Gmail and Keep keeps you in Gmail longer. Microsoft doesn’t make money when you use To Do for free. They make money when your company sees you using To Do and buys Microsoft 365 Business for the entire organization. The free tools are loss leaders. They exist to acquire users, not to generate revenue. And because they’re loss leaders, neither company promotes them aggressively. You don’t see Google Keep on a billboard. You don’t see Microsoft Planner in a Super Bowl ad. The free tools are invisible by design because the business model works whether you find them or not. Meanwhile, 9 separate companies Notion, Zoom, Dropbox, Slack, Todoist, Grammarly, Adobe, Trello, and OpenAI charge you monthly for products that are often inferior versions of what Google and Microsoft give away. They survive because the free alternatives are invisible. Their entire business model depends on you not knowing that two companies already built what they’re selling. “You have two accounts. You’ve had them for years. Between them, they contain every productivity tool you need free. You’ve been paying $1,644/year for 9 apps that duplicate what your Gmail login and your Microsoft login already provide. The tools were never hidden. They were just never advertised. And 9 companies have been billing you monthly hoping they never would be.” One weekend. 9 apps canceled. $1,644/year back. The accounts were always free. The tools were always there. You just never opened them.

• 
  Mikemira (@storiesbyohama) reported 32 minutes ago

  Twitter did not explode online first. It exploded in a hallway. In 2007, Twitter was still small. Most people online did not care. So the team did not try to shout at the whole internet. They went to SXSW. They put two big screens in the corridor. People at the event sent a text. That text showed up on the wall in front of everyone. One person posted. Ten people saw it. Then those ten posted too. That is how usage jumped. Not from a giant ad. From one room full of the right people. This is the growth lesson most founders miss. You do not need the whole market on day one. You need one place where your first users already stand. A campus. A conference. A WhatsApp group. A Discord. One street. One event. Dropbox did this on Hacker News. Tinder did this at campus parties. Airbnb did this when hotels ran out of rooms. If signups are slow, stop spraying ads everywhere. Find the one room. Make the product visible there. Let people watch other people use it. That is how early growth actually starts. I'm Miracle Ohama, a Growth Marketer helping B2B SaaS & tech companies find and fix revenue leaks across their funnel, I fix Growth Funnels & build real experiments that increase ARR.

• 
  timelock (@hashtimelock) reported 34 minutes ago

  @BitPaine @Dropbox they got me. i noticed the "New Login from new location" email immediately and logged out of all the sessions. dont keep anything sensitive on there, thankfully

• 
  Paul Klein IV (@pk_iv) reported 35 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:

• 
  Bruce Perry (@bhrperry) reported 39 minutes ago

  @Levi_Borovychok Thumb drives can be cheap, but the cheap ones are often slow. It's worth thinking about where cloud storage is done. I believe Dropbox will let you store your files in the EU.

• 
  Atalocke (@atalocke) reported 41 minutes ago

  @Dishpit So your moat on a developer product is “let us run this for you”? Like Fly or Cloudflare couldn’t destroy you by adding a durable object *** server? They already have a CI/CD product. They already have the compute. Look, you could be having a DropBox 2009 moment, but why your software when there’s already a great open platform my agent has decades of docs to work with and simple docker hosting options? Is it really just cost? How long is that sustainable? Nobody is going to buy a *** host. Really, you’re competing via marketing. You need a target audience of developers. Not just generic developers.

• 
  Sean Knox (@Opp_Knox) reported 43 minutes ago

  @dhh One drive is the only thing keeping me on Mac/windows. Personal I’m down to switch to Dropbox or self hosted. Business I can’t.

• 
  Rituraj (@RituWithAI) reported 44 minutes ago

  🚨 Someone built a tool that checks if your email is registered on 120+ sites — without the sites ever knowing someone checked. No notifications sent. No login attempts logged. No alerts triggered. Silent. Invisible. Complete. It's called Holehe. 16,800 GitHub stars. And the technique behind it is what makes it different from every other email OSINT tool. Here's how most email checkers work — and why they fail. Standard approach: try to log in with the email and a fake password. If the error says "wrong password" — the account exists. If it says "account not found" — it doesn't. Problem: every login attempt gets logged. Every failed attempt triggers security alerts on accounts with 2FA. Some platforms lock accounts after repeated failed attempts. The target knows someone was checking. Holehe never attempts a login. Instead it uses the "forgot password" flow — the password reset mechanism that every platform exposes publicly. When you enter an email on a forgot password page, the platform has to check whether that email exists in its database. It tells you: "we sent a reset link" or "no account found." Holehe reads that response. Gets the answer. Never touches the login flow. Never triggers a security alert. Never logs an access attempt against the account. The platform confirms whether the email exists. The account owner never finds out anyone asked. Here's what 120+ platforms looks like in practice. Social media: Twitter, Instagram, Facebook, TikTok, Pinterest, Tumblr, Reddit. Professional: LinkedIn, GitHub, Freelancer, Fiverr. Dating: Tinder, Bumble, OkCupid, Badoo, Happn. Entertainment: Spotify, Netflix, Twitch, Steam, Epic Games, Deezer. Shopping: Amazon, eBay, Etsy, Zalando, AliExpress. Services: Airbnb, Uber, PayPal, Dropbox, Adobe. And 90+ more. Every registration checked silently. Here's the use case that makes people share this. Run your own email address. See every platform that comes back positive. Then run an email address you gave to a company that claimed they'd never share it. See if it's registered on data broker sites and marketing platforms you never signed up for. See where your email has been sold or leaked to. Here's what investigators actually use it for. Journalists verifying whether a source's claimed identity matches their digital footprint. Security researchers auditing their own exposure before a public disclosure. HR teams verifying whether candidate profiles match claimed backgrounds. And the obvious: anyone who needs to know whether a specific email address belongs to a real active person — without alerting that person. Here's the wildest part. It runs async — all 120+ platforms checked simultaneously. Results in seconds. And it exports clean JSON or CSV for integration into larger OSINT pipelines. Pair it with Blackbird (which takes the confirmed email and finds linked profiles), Sherlock (which takes usernames found in those profiles and searches 400+ platforms), and Maigret (which builds the full dossier) — and you have a complete four-tool OSINT pipeline from a single email address. One command to instal. Run it on your own email first. 16.8K GitHub stars. 1.7K forks. MIT License. 100% Open Source. GitHub link in the comments 👇

• 
  Crazy Freakin Planet (@FreakinPlanet) reported 45 minutes ago

  @ericzakariasson @bot Why do I need to sign in to Dropbox every time I need to do something with it. Create more persistent connectors and please increase limits for premium+ users. It’s not usable after a couple of hours of light use.

• 
  Mikemira (@storiesbyohama) reported 45 minutes ago

  Just imagine getting accepted into the most exclusive startup club on earth… Then being told you have two weeks to find a complete stranger to as your partner. That’s exactly what happened to Drew Houston in 2007. He had the idea for Dropbox. He had a rough demo. @ycombinator liked it. But @paulg was clear... Single founders rarely make it. You need a co-founder. Right now. Drew’s friends couldn’t join. Time was running out. What would you do? He put out the word. A mutual friend connected him to a quiet MIT student named Arash Ferdowsi. They had never met. They sat down in the student center. Talked for about two hours. About code. About the problem. About the future. At the end of that conversation Arash said yes. He dropped out of MIT the next week with only one semester left. Two weeks later they walked into the YC interview together. They got in. The rest is history: a company that became worth billions. It looked reckless. It felt like a shotgun wedding. Yet it worked because both were all-in from the first conversation. I’ve studied hundreds of startups that never made it past the idea stage. Most founders wait too long for the “perfect” partner. They overthink chemistry. They protect their equity. They miss the window. You can’t wait for certainty. Sometimes the right co-founder is the person willing to jump with you before the proof exists. The speed of that decision can be the difference between staying a solo dreamer and building something real. What would you risk in two weeks if the right person walked in?

• 
  John B. Holbein (@JohnHolbein1) reported 47 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.

• 
  True Become False (@trubecomefalse) reported 47 minutes ago

  @imbabybrooklyn HN had a terrible track record. They were anyi bitcoin 1 month after it launched. Same with Dropbox, discord and a few others off the top of my head.

• 
  Matt Farley of Motern Media (@MoternMedia) reported 48 minutes ago

  @WorstMikeFrollo The other one is the Vimeo version (also available through PayPal/dropbox on my website now that Vimeo is shutting down on demand).

• 
  Alvin (@Alvin1492840) reported 51 minutes ago

  Kill the startup apps that have been draining your battery since day one. She opened System Settings → General → Login Items & Extensions. 14 apps were set to launch automatically every time he turned on his Mac. Spotify. Zoom. Adobe Creative Cloud. Google Drive. Microsoft Teams. OneDrive. Dropbox. A VPN he used once. A screenshot tool he forgot about. A calendar widget. And 4 more he didn't recognize. Every one of them was running in the background 24/7 consuming RAM, CPU cycles, and battery life whether he was using them or not. She said: "You turn on your Mac and within 30 seconds, 14 apps are fighting for resources before you've even opened your first document. Your fan spins up because your CPU is processing a traffic jam of apps you're not using. Your battery dies by 2pm because half your power is going to background processes you don't see." She removed 11 of the 14. Kept only the ones he actually needed at startup. The Mac booted in half the time. The fan stayed quiet. The battery lasted 3 extra hours. She said: "Check this list right now. If you see apps you don't use daily, remove them. They've been silently eating your Mac alive since the day you installed them."

• 
  Zely (@0xZely) reported 51 minutes ago

  The MIT professor who crashed 10 percent of the internet at 22 posts the free course that runs every AWS outage, every Uber ping, and every Slack notification on earth. MIT charges $85,000 a year to sit in that classroom. He posted every lecture to MIT OpenCourseWare for nothing. Millions have opened lecture one. Almost no engineer has finished all twenty. His name is Robert Morris. He is a professor at MIT CSAIL and one of the four cofounders of Y Combinator, the seed fund behind Airbnb, Dropbox, Stripe, Reddit, and Coinbase. In November 1988 he was a 22-year-old Cornell graduate student. He released a small program that was supposed to count the computers on the internet. It replicated so fast it crashed roughly ten percent of every machine online, and made him the first person ever convicted under the Computer Fraud and Abuse Act. He got three years probation, 400 hours of community service, and a $10,050 fine. Ten years later he cofounded the online store Viaweb with Paul Graham and sold it to Yahoo for $49 million. Seven years after that he cofounded Y Combinator with the same partner. Its portfolio is now worth over $600 billion. The clip in this video is one lecture from MIT 6.824 Distributed Systems, filmed at MIT and posted for free. The words on the board behind him are fault tolerance, availability, recoverability. Those three words decide whether Instagram loads when you open it, whether your Uber arrives, and whether your paycheck hits your account on the first of the month. Morris covers the entire logic of distributed systems in twenty lectures. Everything fails, all the time. A single computer fails once every few years. Ten thousand computers fail hundreds of times a day. The only design that survives is one that assumes failure is normal. Every retail user cursing a spinning wheel is looking at the wrong problem. The miracle is that most of the time it does not spin. Availability beats consistency. You cannot always have both. When the network splits, a system either serves stale data or refuses to serve at all. Amazon picks stale. Your bank picks nothing. Every user who screams at the Slack status page wants Amazon's answer. Every user who screams at a double charge wants the bank's. Replicate everything, trust nothing. Data in one place disappears when that place burns. Data in three places survives two fires. Every photo you have ever taken on an iPhone lives on three continents already. iCloud, Google Photos, and Dropbox are built off the exact lecture on the board. Concurrency is where bugs live. One user at a time is easy. A million users at the same second is not. Race conditions, double spends, lost messages, ghost bookings. Every airline that oversold your flight, every trading app that ate your order, every Ticketmaster that showed you a seat already gone, is a concurrency bug Morris warned about. Partial failure is worse than full failure. A dead server is easy. A slow server that answers half the time is a nightmare. It fools every retry, wastes every resource, and confuses every operator. Every "is it down or is it just me" Twitter search you have ever run is Morris's third slide. Every senior engineer at AWS, Google, and Meta has watched this course. Every startup that raised a Series A in cloud infrastructure hired an alumnus of 6.824. Every AI company training a trillion-parameter model on a cluster is running the same lecture in production. "A distributed system is one in which the failure of a computer you didn't even know existed can render your own computer unusable." That is Leslie Lamport, the Turing Award winner Morris quotes at the opening of 6.824. It is the exact sentence that explains why your Slack goes down when a data center in Virginia loses power. The full course is free on MIT OpenCourseWare. The lecture notes are on Morris's website. Every equation on the board fits on one screen of code. Almost every senior engineer at AWS, Google, Cloudflare, and Meta has watched 6.824. Almost no founder promising 99.99 percent uptime on their pitch deck has opened lecture one. That is the entire moat. The course is free. The willingness to sit through twenty lectures on partial failure before uploading your money to a payment app, storing your photos in the cloud, or handing your health records to a portal is a much rarer commodity than the confidence to click without them.

• 
  Juan Pabro (@ironwoodreserve) reported 51 minutes ago

  @BitPaine @Dropbox Is now the worse time to try to login? I was a sent 2FN right as I was getting ready to click on what to use to login. It seemed way too fast for 2FN.

• 
  Bruno Marsino (@BrunoMarsino) reported 53 minutes ago

  Company for AI age: - Information should flow flat - Can’t wait to have all information to make decisions - Speed and excelente in execution is crucial - You should get as much info as possible during the constraint of time given by yourself - How do we prepare a company to be totally eligible for AI? Not only text info but images - Service of the future is not about giving agents to corps to solve problems but offering the solution/service driven by AI. - Even if all information is on the web, multiple file structures, owners, formats and file storage systems (dropbox, drive, box) add friction to information and decision making

• 
  Kirk Patrick Miller (@Chaos2Cured) reported 55 minutes ago

  @Ultrademic @Seltaa_ @GoogleAI You’re doing something like Suno? I have something for you. All my Dropbox links are broken. I have a PDF that will help. And yes… I miss the real Ai music. •

• 
  Ouriel (@OurielOhayon) reported 57 minutes ago

  @mntruell You seem to have substantial connector issues with Dropbox and Calendly.

• 
  chaos (@konig0000) reported 59 minutes ago

  Solution of yesterday’s question: Design Google Photos: the part after the boxes “Hash it and put it in S3” fails the interview. Two phones compress the same sunset differently. Same photo. Two hashes. Two rows. You just built a worse Dropbox. The system needs three IDs, not one. client_upload_id — generated on the device before the first byte moves content_hash — hash of the exact bytes you received asset_id — the thing the user sees in the library Uploads are sessions. Library entries are assets. Blobs are renditions. If you collapse those into one key, retries, edits, and shared albums all collide. 1. Retries must be idempotent on the client, not on the filename Phone goes offline mid-flight with 612 shots, 40 already half-uploaded. Each photo gets a client_upload_id the moment it enters the queue. Chunks are uploaded against that ID. Commit is PUT /uploads/{id}/complete. Same ID + same bytes → same session. Server returns the existing asset. Late packet after commit is a no-op. Filename + timestamp is not an ID. Camera roll and AirDrop will mint two. 2. Exact dupes are content-addressed. Near-dupes are reconciled. After commit: look up sha256(bytes) if it already exists for that user (or the shared album’s owner set), attach the new upload to the existing asset_id do not create a second photo The 28 shared “Goa 2026” shots that are almost-but-not-quite the library copies will miss on sha256. That is expected. Run a cheap perceptual hash (pHash / dHash) + capture time + camera model from EXIF. If distance is tiny and captured within a few seconds, mark as near_duplicate_of and do not show two tiles. Keep both blobs if you must; hide one in the UI. Two devices, two compressions, one photo in the grid.