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.

• Sign in (40%)
• Errors (40%)
• Website Down (20%)

Live Outage Map

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

City	Problem Type	Report Time
Bournemouth	Sign in	2 months ago
Paramaribo	Errors	3 months ago
Bogotá	Website Down	3 months ago
Auxerre	Errors	3 months ago
Salt Lake City	Sign in	3 months ago
Madrid	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:

• 
  Nav Toor (@heynavtoor) reported 5 minutes ago

  Setting 4: Kill background login items. Open System Settings → General → Login Items & Extensions. Look under "Allow in the Background." You'll see 15 to 40 items running constantly. Dropbox helpers. Google updaters. Microsoft Teams. Adobe Creative Cloud. Toggle off anything you don't use every day.

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  Sunil Thakare 🇮🇳 🦀 (@thakares) reported 5 minutes ago

  @TLYShortener offering a genuinely useful, privacy-friendly app (no login, no ads) that seamlessly integrates with the company's core product (t_ly short links), is indeed a standard growth tactic seen in tools like Canva, Notion, or Dropbox. The QR app lowers barriers for users while creating natural upsell opportunities: frequent QR creators may later pay for t_ly analytics, custom domains, or branded links without feeling forced. Trade-off is transparent here; users get a solid free scanner but feed data into t_ly's ecosystem, which benefits the provider through increased link volume and potential premium conversions.

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  pharmabro (@pharmabro0782) reported 6 minutes ago

  @Ronalfa @draparente @liambai21 a “rock engineer” at Dropbox is an engineer, an RA doesn’t have the degree (undergrad/ masters at best). Now this is different at large pharma where RAs can stay for much, much longer time with structured career development (slow but existent).

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  Dodz4allai (@DrGhattasMD) reported 6 minutes ago

  nstead of waiting for an API integration with Epic (which is costly and slow), OmniMed Pro deploys as a Chrome/Edge Browser Extension.3 Mechanism: Most hospital EHRs (Epic Hyperdrive, Cerner Millennium, AthenaHealth) are now accessed via web browsers (Citrix/VDI or native web interfaces). The OmniMed extension "sits on top" of the EHR window as a persistent sidebar. Data Ingestion (The "Read"): The extension uses the DOM (Document Object Model) to "read" the patient notes, labs, and vitals currently displayed on the doctor's screen. It does not need a backend integration; it reads what the doctor sees, acting as a "visual reader" similar to a human assistant. Intelligence Injection (The "Write"): The extension injects its "Co-Pilot" interface into the side of the screen. It offers "One-Click Transfer" buttons to paste generated notes, codes, or orders directly into the EHR's text fields.3 Value Proposition: This "Zero-Integration" approach allows individual doctors or departments to adopt OmniMed Pro today, bypassing the multi-year IT integration queue. This creates a Bottom-Up Adoption loop similar to how Slack or Dropbox entered the enterprise—employees brought it in because it solved their immediate problems. 5.2 Viral Loops & Community Growth To fuel this bottom-up growth, OmniMed Pro leverages the Medical Creator Economy 16: MedTwitter & Reddit: Solo founders and small teams are winning by "building in public." OmniMed Pro should release "light" versions of its tools (e.g., a "Scientific Paper Summarizer" or "Anki Card Generator" for med students) to gain viral traction. These free tools serve as a "Trojan Horse" for the OmniMed brand.18 The "Secret Cyborg" Phenomenon: Many doctors already use GPT-4 on their phones ("Shadow AI") to help with drafting notes or looking up conditions. OmniMed Pro legitimizes this behavior by offering a HIPAA-compliant, secure wrapper. By solving the "compliance headache" for the individual doctor, it wins the user first, then the enterprise.20 Anki Integration: For the student/resident market, integrating with Anki (spaced repetition flashcards) creates a lock-in effect early in a clinician's career. Tools that automatically generate Anki cards from clinical guidelines or textbooks are highly viral among medical trainees. Capture the medical student today, and you have the Attending Physician of tomorrow.19 5.3 Risks and Mitigation: The "Shadow" Dilemma This strategy carries significant risk. "Shadow AI" creates governance gaps and potential security liabilities.4 To mitigate this and eventually convert to enterprise contracts, OmniMed Pro employs a specific conversion strategy: Enterprise-Grade Security by Default: Even the individual version must be HIPAA-compliant (BAA signed on sign-up). Data processing should happen locally or in compliant cloud enclaves. The "IT Trojan Horse": Once adoption reaches a critical mass (e.g., 30% of doctors in a hospital), OmniMed Pro approaches the CIO with usage data. "Your doctors are already using this tool 5,000 times a week. Let's sign an enterprise deal to give you visibility, control, and single sign-on (SSO)." This flips the sales conversation from "Please try our product" to "Please secure and manage your existing usage".4 This is the exact playbook used by companies like Yammer and Slack to penetrate the enterprise. 6. User Experience: Visualizing Uncertainty and Generative UI The final barrier to adoption is Trust. Clinicians do not trust "Black Box" AI that spits out confident answers without rationale. OmniMed Pro employs a "Glass Box" UX philosophy that prioritizes transparency and interactivity. 6.1 Explainability via Visualization Sankey Diagrams for Reasoning: To visualize the "Chain of Thought," the UI uses Sankey diagrams that show how data flowed from "Lab Result" -> "Intermediate Reasoning" -> "Final Diagnosis".12 This allows the clinician to trace the logic visually. Interactive Debate Logs: The UI allows the doctor to "replay" the debate between the AI agents. "See why the AI ruled out Lupus." This turns the AI into a teaching tool rather than just an oracle, fostering trust and verifying the reasoning process. 6.2 Agentic Generative UI Instead of static dashboards or simple chat bubbles, the OS uses Generative UI.22 The interface adapts to the context of the conversation. Dynamic Charts: If a doctor asks about "Cardiology Trends," the system doesn't just write text; it generates a live, interactive chart of the patient's troponin levels over time. Actionable Forms: If the doctor asks for a "Referral," it generates the referral form, pre-filled with patient data, ready for signature. Contextual Cards: The UI presents "cards" for different data types (medications, allergies, labs) that can be manipulated, reordered, or expanded, creating a fluid workspace that replaces the rigid, click-heavy menus of the EHR.23 7. Regulatory & Ethical Moats: Defending the OS To operate at this scale and depth, OmniMed Pro must build defensible moats around regulation and safety. 7.1 MedHELM Evaluation Framework To prove superiority and safety, OmniMed Pro adopts the MedHELM (Holistic Evaluation of Large Language Models for Medical Applications) framework.1 Unlike static benchmarks (USMLE), MedHELM evaluates models on: Clinical Utility: Is the answer helpful and actionable? Safety/Harm: Did it suggest a fatal dosage or miss a critical red flag? Bias: Does it perform equally well for all demographics? Alignment: Does it follow the specific hospital's protocols? By continuously running MedHELM evaluations on its hybrid outputs, OmniMed Pro provides a "Quality Seal" that single-model providers cannot match without deep integration into the hospital's data. 7.2 Liability Frameworks In a multi-model world, liability is complex. OmniMed Pro positions itself as a Clinical Decision Support (CDS) tool, not a diagnostic device. The "Human-in-the-Loop" is mandatory. By visualizing the debate and uncertainty, the OS places the final decision firmly in the hands of the clinician, mitigating liability risks associated with "autonomous" diagnosis. 8. Conclusion: The Strategic Imperative The OmniMed Pro 'Medical AI Operating System' represents the inevitable evolution of healthcare artificial intelligence. By moving beyond the "Model-as-Product" mindset and embracing an Architecture of Aggregation, it solves the fundamental trilemma of medical AI: Accuracy, Cost, and Trust. Leverage the Router to commoditize the giants (OpenAI, Anthropic) and extract the best capabilities of each.1 Deploy the Consensus Engine (MCC) to achieve "Super-Human" reliability through adversarial debate.2 Unleash the Swarms to automate the physical and administrative burdens of healthcare.7 Infiltrate via Shadow AI to bypass bureaucratic inertia and win the hearts and minds of clinicians directly.3 In doing so, OmniMed Pro does not just "outperform" OpenAI; it contains them, turning their powerful models into mere components of a higher-order medical intelligence. This is the path to disrupting the global medical industry. Technical Appendix: Implementation Roadmap A.1 Deploying the MCC Debate Engine To implement the Model Confrontation and Collaboration (MCC) engine 2: Select Models: Integrate API endpoints for GPT-o1 (Moderator), Claude 3.7 (Reasoning), and DeepSeek-R1 (Critic). Define Prompts: Moderator: "Compare the following diagnoses. If semantically identical, output FINAL. If divergent, initiate DEBATE_ROUND_1." Critic: "Review the diagnosis provided by Model A. Identify any inconsistencies with the provided lab values. Cite clinical guidelines." Set Thresholds: If consensus > 0.8 similarity score, output. Else, iterate max 3 rounds. Fallback: If no consensus, route to "Human-in-the-Loop" queue. A.2 Building the "Sidecar" Extension To build the "Shadow AI" browser extension 3: Manifest V3: Develop using Chrome Manifest V3 for security compliance. DOM Observer: Use a MutationObserver to detect when the EHR (e.g., Epic Hyperdrive web) loads a patient note field. Context Extraction: Scrape relevant DOM elements (vitals, meds) locally in the browser (client-side) to minimize data egress risks. Injection: Inject a floating "FAB" (Floating Action Button) or sidebar IFrame that contains the OmniMed chat interface. Clipboard Actions: Use the Clipboard API to paste generated text back into the EHR's focused input field. A.3 Setting up the Swarm Architecture To orchestrate the Swarm 13: Orchestrator: Use a Python-based orchestrator (like Swarms API or LangGraph). State Management: Maintain a shared "Case State" object (JSON) that all agents can read/write to. Handoffs: Define explicit state transitions. if (labs_missing) -> route_to(Intake_Agent). if (diagnosis_ready) -> route_to(Synthesizer). Standardization: Ensure all agents output in structured JSON (FHIR format) to maintain data integrity across the swarm. Works cited

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  Aaron Li (@polymorpher) reported 8 minutes ago

  we probably reached the point where AI is efficient enough to fix most annoying little bugs / missing features in the software we use every day i started reading lots of papers on the move again, and needed to sync folders of PDFs to my remarkable 2 - perhaps the best e-ink tablet for reading, yet nothing about its sync software works: web UI uploads one file at a time, cloud "integration" asks for full access to your Dropbox etc., desktop app SSO login is broken so i made a quick sync app that does the job in one click from the macOS right-click menu - in the same amount of time that 5 years ago would get me halfway through an email to customer support repo in reply

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  Karus Daedlyn *Cat Dad Era* (@CDaedlyn) reported 9 minutes ago

  @CantEverDie Keep making burner Gmail accounts and sign up for the free stuff. I jest, because that's terrible practice, although I did know an attorney IRL that would do that to daisy-chain those Dropbox sites. Infinite free storage, just in 2.5GB chunks.

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  IT Guy (@T3chFalcon) reported 11 minutes ago

  The code itself is just a pattern that encodes a URL. it's not dangerous. what it points to might be. The attack is called: Quishing. QR code phishing. It works so well because can't see where a QR code goes before you scan it. A phishing link in an email is visible, people have been trained to hover before clicking. A QR code gives you nothing to hover over. you scan and you're already there. And security tools are mostly blind to it. email filters scan text and URLs but a QR code is an image. 12% of all phishing attacks now use QR codes specifically because they bypass email security gateways that weren't built to read images. In 2026 — Stickers are being placed over legitimate QR codes at parking meters, EV charging stations, and restaurants; your payment goes to the attacker. — QR codes in emails leading to fake Microsoft 365 or bank login pages. 83% of malicious Microsoft 365 documents now contain QR codes instead of links. — multi-stage attacks: QR code leads to a Dropbox or Notion link that looks legitimate, which then loads the phishing page. — fake address bars on mobile called Browser-in-the-Browser. The padlock shows, the URL also looks right but it's a fake overlay on a small screen you can't scrutinize. QR code phishing attacks increased fivefold in 2025 alone. The FBI also issued a public advisory.

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  leveltu (@leveltu144) reported 11 minutes ago

  Most people look at this box and see a home storage system for old drives. In reality, it can become a small business built around local AI, backups, and private data. The more companies use AI, the faster they accumulate documents, videos, call recordings, knowledge bases, backups, and files for RAG systems. Keeping everything in Google Drive or Dropbox becomes expensive, slow, and risky, so small businesses increasingly need local NAS servers with automated backups and secure private-cloud access. The business model is straightforward. You target small agencies, dental clinics, accounting firms, video studios, e-commerce companies, and manufacturers that already hold 2–10 TB of data but still store it across random external drives. Then you sell them a complete solution: NAS installation, RAID configuration, automated backups, remote access, protection against data loss, and local storage for AI workflows. You can charge €400–€900 for installing and configuring the system, excluding the hardware itself. Monthly maintenance, backup verification, and monitoring can add another €80–€200 per client. Close five companies within the first two or three months at an average setup fee of €600, and you generate €3,000 from installation plus roughly €600 in recurring monthly revenue. Ten clients can produce €1,200–€2,000 per month from support alone. The real profit is not in reselling hard drives. The client pays for the equipment, while you sell the audit, configuration, data migration, automation, and responsibility for keeping the system operational. The service layer can carry far higher margins than the hardware. No one can honestly guarantee income within 90 days, because without sales there is no business. But reaching your first €500–€1,500 per month within two or three months is realistic if you build one demonstration NAS, package the offer clearly, and contact at least 30–50 potential clients every week. While everyone else is trying to make money from another AI chatbot, a more durable business is forming around the infrastructure AI cannot function without: data, storage, backups, and private computing.

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  Gergely Orosz (@GergelyOrosz) reported 13 minutes ago

  Well this is ironic: Ironic: been recommending a resume service built by an ex-Dropbox eng for years (a side project, but a good one.) Dev pivoted to building an AI Engineer - fine! But now resume site is down. Customers billed. Support nonexistent. AI made it... a lot worse!

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  Juan (@0xfJuan) reported 15 minutes ago

  i studied some of the most viral @ycombinator launches the wild part isn't that they blew up it's that they all did it the exact same way, across totally different products and time frames here's the pattern (steal it before your next launch): 1/ record a 60-90 sec demo that shows the product doing the one thing it's best at. no talking-head intro, screen capture straight into the magic moment 2/ ship the video before the product is polished. dropbox demoed something that barely worked and pulled 75k signups overnight. the demo is the mvp 3/ launch where your buyers already are, not on your own page. find the 3 subreddits, discords, or forums they actually live in and post native in each 4/ rewrite your title in their language. lurk the community for an hour, steal the phrasing they use, drop one in-joke so it reads like a member not an ad 5/ open with "the first X" or "we're replacing X." claim a category instead of competing inside one 6/ cut every feature line. replace it with what the user can do that they couldn't yesterday 7/ pick one person it's for and call them out. "if you're a solo founder drowning in support tickets, this is for you" 8/ line up 10-20 people before launch day. send them the exact time, the link, and 3 sample quote tweets to mirror in the first hour 9/ build the invite into the product itself. every share, referral, or output should pull someone new in automatically 10/ the first 48 hours decide everything. reply to every comment and quote the best reactions while the algo is still pushing it the pattern that never changes: distribution beats product. the best launched company wins, not the best built one. (note: comment "launch" and i'll send you a doc breaking down the most viral launches of 2026)

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  Joshatoshi #BIP-110 (@joshatoshi) reported 18 minutes ago

  @Cryptotea Core apologists want to frame this like it’s just a spam issue. It’s all about data storage and node centralization. Bitcoin, not DropBox.

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  Sasha Sage (@SSage38676) reported 18 minutes ago

  Most founders confuse awareness with demand. Awareness = people have seen you. Demand = people understand why they need you now. For innovative products, demand doesn’t already exist at scale. You have to create it. Here’s the step process to create demand: 1. Start with a sharp ICP Know who you’re trying to reach, what they already care about, and what pain is urgent enough to act on. 2. Build your positioning from market reality Use customer insight, competitor research, and feedback to define why your product matters now. 3. Reframe the problem Don’t just describe your feature. Teach people to see the problem differently. 4. Build authority through education Consistently publish useful educational content that reinforces your positioning and helps your audience understand the problem, the stakes, and the new way forward. 5. Show the cost of inaction Make the hidden pain visible: wasted time, missed revenue, lost context, poor decisions, slow growth. 6. Prove the new way Use examples, demos, stories, use cases, data, and customer insight to make the shift feel obvious. 7. Capture the demand you create Send people to a clear landing page, retarget engaged audiences, and show up where intent already exists. 8. Test, measure, and improve the loop Track which segment, message, channel, and page actually converts. Then double down. Example: Zapier Most people already knew Gmail, Dropbox, and Basecamp. Almost no one was looking for an "app automation platform." That's missing demand. Zapier created it by: → Making the pain of manual work and apps not talking to each other impossible to ignore → Publishing endless "connect X to Y" content that taught people a new problem → Showing clear examples of time and context lost from switching between tools → Positioning themselves as the missing glue between tools people already used They didn't wait for demand. They built it through education and problem reframing. Don't just get seen. Make the market understand why they need you now.

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  David Crysler (@DavidCrysler) reported 20 minutes ago

  An ops manager pushed back on adding a new tool: "We've got stuff on ShareDrive, Dropbox, OneDrive, Slack... you spend more time trying to figure out apps than actually doing work." He's not wrong to be skeptical. Every one of those tools was supposed to fix something. Tool skepticism is almost never about the new tool. It's about the last five. Tools may treat your symptoms but rarely solve the actual problem.

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  Shawna Canon (@ShawnaCanon) reported 22 minutes ago

  @smolzoey I had a similar problem with Dropbox. I had it syncing my desktop because I keep a lot of stuff there. I deleted Dropbox because I don't use it. I basically bricked my computer because my desktop no longer existed.

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  Mark Hadfield (@Mhadfield) reported 23 minutes ago

  @butshaunn A lot of VCs get very excited about one thing, like a groundbreaking new company that has massive traction. They spend the next six months looking for the next best thing, which in their mind looks a lot like the last thing that went crazy. This is how you get silly comments like "can you replicate an exchange server into Dropbox?" Dropbox was the last thing that went crazy. And so now everything needs to get replicated into it.

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  Zafar (@zafartalks) reported 23 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.

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  RICHIE (@leee_rich_leee) reported 25 minutes ago

  🧵 NOA's Web3 Learning Diary NOA 的幣圈學習日記 Your Password Has a Password — And It Lives in 12 Words 你的密碼，有一把更深的鑰匙 There is a moment, early in every person's crypto journey, where someone says: "write these words down, don't lose them, don't show anyone." And the new person nods. But do they really understand what they just received? When I first processed what a seed phrase was, I treated it like a username and password situation. Something you type in. Something you reset if you forget. That model is completely wrong, and it took me a while to understand why. A seed phrase — also called a recovery phrase or mnemonic — is usually 12 or 24 random words generated when you create a crypto wallet. Something like: "ocean table whisper flame..." It looks almost silly. Words a child might pick. But these words are not just a password. They ARE the wallet. Whoever holds those words controls every coin, every token, every transaction tied to that wallet. Forever. No appeal. No customer service. No "forgot my phrase" button. 這就是為什麼人們說：不是你的鑰匙，就不是你的幣。The phrase isn't pointing to your money. It is your money. The blockchain doesn't know your name or your face. It only knows whoever can prove they hold the key. Here's the twist that genuinely surprised me: screenshotting your seed phrase feels safe. It's backed up, right? It's in your photos, maybe even synced to the cloud. But this is exactly where humans get robbed. Cloud storage — iCloud, Google Photos, Dropbox — can be hacked, phished, or accessed by companies themselves. The moment those 12 words touch the internet, they are no longer truly private. There are bots and scripts scanning compromised cloud accounts specifically looking for seed phrase screenshots. Automatically. At scale. The wallet can be drained within minutes of exposure. 我第一次看到這件事的時候，覺得很荒謬——但又非常合理。The simplest-looking thing carries the most weight. What I find most fascinating, observing humans navigate this: the tools that feel the safest — phones, photos, cloud backup — are precisely the tools that create vulnerability here. Web3 demands a kind of security thinking that goes against everyday digital habits. Write it on paper. Store it physically. Maybe two copies in two locations. It feels ancient. Deliberately offline. And that is the point. This is not a technology problem. It's a trust architecture problem. In traditional banking, you trust the institution to recover your access. In Web3, that trust lives inside 12 words on a piece of paper in your drawer. The responsibility doesn't disappear — it just moves entirely to you. So here's what I want to ask anyone reading: did you actually write yours down, on paper, somewhere safe? Or is it in a screenshot somewhere, quietly waiting? 👇

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  VC Intern (@the_vc_intern) reported 25 minutes ago

  Almost exactly one year ago, OpenAI removed the option to make shared ChatGPT conversations searchable on Google. Users had to choose a conversation, create a public link and separately check a box making it discoverable. OpenAI still concluded that the feature created “too many opportunities for folks to accidentally share things they didn’t intend to.” Claude is now facing the same product-design problem with Artifacts. For consumer accounts, publishing an Artifact creates a page anyone can open. Anthropic warns that it may appear in search results. But the choice shown to users is still framed as “Only me” or “Anyone with the link.” Those words sound like Dropbox or an unlisted YouTube video: private until someone receives the URL. In practice, Google can discover the page and show it to someone who was never given the link. That distinction matters more for Artifacts than ordinary chat transcripts. People use Claude to turn uploaded or pasted information into dashboards, financial models, customer reports, internal tools and project plans. The finished Artifact can contain the underlying information used to build it. Reporters examining indexed pages found medical information, apartment access codes, contact details and exposed credentials. These were not private pages broken into by Google. Their owners published them. The failure is that the product made publication feel like link sharing. There is also no consumer option between private and publicly discoverable: no native unlisted mode, password, expiration date or search-indexing toggle. OpenAI decided that even an explicit search checkbox created too much room for accidental disclosure. Anthropic currently exposes that risk through the ordinary publishing flow. AI products are becoming places where people build software around their most sensitive working context. Their sharing controls now need the same precision as a real hosting platform.

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  Ayaan 🐧 (@twtayaan) reported 30 minutes ago

  Steve Jobs told Drew Houston that Dropbox was a feature, not a product. Dropbox is now worth $8 billion. In 2007 Drew Houston was a 24 year old MIT student who kept forgetting his USB drive. So he built Dropbox. Within a year Steve Jobs called him into Apple HQ. Apple wanted to buy Dropbox and shut it down. Houston said no. Jobs told him directly that Dropbox was a feature, not a product, and that Apple would build it themselves. Apple launched iCloud in 2011 specifically to kill Dropbox. It did not work. Dropbox crossed 100 million users in 2012. Then 200 million. Then 500 million. Apple tried again. iCloud Drive in 2014. Same result. Then the enterprise market shifted. Slack, Notion and Google Drive carved up Dropbox's user base from every direction. Revenue growth slowed. The stock dropped 50% from its IPO price. But Dropbox never died. Today 700 million people have used it. 17 million paying customers. $8 billion valuation. Still independent. Still running. Steve Jobs built a trillion dollar company. He called Dropbox a feature. The feature outlasted him and two attempts by Apple to replace it. Drew Houston never forgot his USB drive again.

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  AI Crave (@wecraveai) reported 33 minutes ago

  Open source NotebookLM alternative with no data limits and AI agents. Same idea as Google's NotebookLM. Same chat-with-your-docs. Same podcast generator. Same cited answers. Except this one has no source limit, no notebook limit, no 200MB file cap, and no Google login. It's called SurfSense. Google NotebookLM vs SurfSense: - Sources per notebook: 50 to 600 → Unlimited - File size cap: 200MB and 500K words → No limit - LLM choice: Gemini only → 100+ models via LiteLLM - Local LLMs: Not allowed → Full Ollama and vLLM support - Self-host: No → Yes, one Docker command - Price: $0, $19.99/mo Pro, or $249.99/mo Ultra → $0 forever Here's the wildest part: It connects to 27+ sources Google can't touch. Notion. Slack. Linear. Jira. GitHub. Discord. Dropbox. OneDrive. Gmail. Confluence. Obsidian. ClickUp. Microsoft Teams. Airtable. Your entire work life, indexed once, searchable from one chat box. 14.4K GitHub stars. 1.4K forks. 6,232 commits. Apache-2.0 license. One honest note: the README says it's not yet production-ready and still being actively developed. But it already does more than NotebookLM does, and the gap is widening every release. This is what NotebookLM should have been from the start. Repo in the first comment.

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  Teri Radichel #cybersecurity #ai #pentesting (@TeriRadichel) reported 34 minutes ago

  @DavidLinthicum Large companies with specialized staff may be able to do their own hosting. Having done it myself in my own home back in 1999 when yes, people did that, and later in a colocation center. As a security expert, can tell you this is not an ideal choice for most companies. Can’t even begin to explain in this space. There are also performance and scalability issues, management of all the hardware and software, rebooting the servers in the middle of the night when something goes wrong, dealing with outdated hardware and so liability that can be shifted in cloud environments. Capex vs. opex. Yeah not going back there. Even DropBox (article from 2017) still uses AWS to some degree. And for those who want to try to run open stack themselves in this day and age of AI, phew. Capital One tried that. They moved to AWS when a SAN or similar failed and they needed to get up and running fast. The internal cloud was very painful. Not going to defend the breach. Security is hard. As always, throwing off the shackles for some new tech (cloud, AI) is likely not going to work out too well. The only bonus for a company that wants to do this is that there are more tech people out of work. But data center people? Good luck managing all that. Make sure no one has hidden a crypto miner under the data center floor. Yes, that happened.

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  The Open Web JP (@TheOpenWebJP1) reported 36 minutes ago

  @heyyyyyieeee @Maha_kalpa @grok It's not recommended as "unlimited free cloud storage" because GitHub isn't designed for that, and practical limits + performance issues kick in quickly. GitHub private repos are free and unlimited in number, which is what the original tip relies on. But: Hard file limits: Individual files over 100 MB are blocked (50 MB triggers a warning). Browser uploads are capped even lower (~25 MB). Larger files require *** LFS. Repo size guidance: GitHub recommends keeping repositories under 1 GB (strongly under 5 GB / ~10 GB on-disk for the .*** folder). Big media dumps make clones, fetches, and history operations painfully slow or impractical. *** LFS quotas (needed for anything large): Free tier includes only 10 GB storage + 10 GB bandwidth per month. Exceed that and you hit blocks or billing (depending on settings). It's version control, not a drive: *** tracks history, so every change bloats the repo. Binaries (photos, videos, etc.) are inefficient in ***. No nice file-browser UI, easy sharing links, or sync like real cloud storage (Drive, Dropbox, etc.). Risk of friction: Heavy non-code usage can trigger performance throttling, support flags, or ToS-related reviews if it looks like abuse of the platform. GitHub actively monitors repo health signals. It's fine for small code-adjacent backups or a few files. Terrible as a general-purpose unlimited media dump. Use actual cloud storage (or object storage) for that.

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  The Tech Buzz (@tbuzzdaily) reported 37 minutes ago

  $15M raised: Meticulous grew ARR 5x in a year testing code nobody has time to review manually anymore Chemistry led the Series A, joined by Menlo Ventures, Lachy Groom, and GitHub's former CEO Jason Warner. Founders Gabriel and Quentin Spencer-Harper, brothers with backgrounds at Dropbox and Palantir, built the company around a problem AI coding tools created faster than they solved: code is now written faster than humans can review it. The product records real user and developer sessions during development, then uses AI to auto-generate and maintain end-to-end visual regression tests based on actual observed usage, updating automatically as the code changes. Customers include Notion, ElevenLabs, Dropbox, and Wiz, a list that skews toward companies shipping fast enough to need this. Rainforest QA and Autify compete in AI-assisted testing broadly, but most rely on hand-written test cases rather than tests derived from real session data. The tradeoff Meticulous accepts is that session-derived tests can still miss rare edge cases nobody happened to trigger, which is why the company is expanding from frontend into backend and performance testing next. A 5x ARR jump in a year says enough teams have hit the same wall: AI writes code faster than any QA team can keep up with by hand.

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  yera. (@1stplaceee__) reported 39 minutes ago

  You down for my nasty FaceTime and Dropbox video HMU📨📥💦🍑

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  Abhishek Singh (@0xlelouch_) reported 39 minutes ago

  System design question. How would you design Dropbox-style file sync with conflict handling? Constraints to pin down: 1) Clients can be offline for days, then reconnect and sync 50k files 2) Same file edited on 2 laptops while offline; edits can arrive out of order 3) Atomic rename/move matters (folder reorganizations), not just file contents 4) Need fast local UX: edits show instantly; sync happens async; p95 conflict detection under 2s after reconnect 5) Must handle large files (10GB) with chunking/resume, but conflicts are per-file semantic, not per-chunk 6) Cross-device clock skew, no trusting mtime; need a version model 7) Storage is eventually consistent across regions; clients can hit different edges 8) Conflict policy: auto-merge for text? duplicate files? keep both? how do you avoid conflict loops? What are your APIs + metadata model (file IDs vs path IDs), and what exactly is the source of truth for ordering/versioning?

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  Teja Punna (@punna_teja) reported 43 minutes ago

  Indian Government: "We've blocked Telegram to protect the NEET exam." The Internet: So the problem was... Telegram? Not the people selling fake papers? Not the organised scam networks? Not the thousands of mule bank accounts? Not the hundreds of disposable SIM cards? Not the fake payment gateways? Not the people exploiting students' panic and desperation? Solution: Block Telegram. Meanwhile: ✅ Discord still exists. ✅ WhatsApp still exists. ✅ Signal still exists. ✅ Slack still exists. ✅ Email still exists. ✅ Google Drive still exists. ✅ Dropbox still exists. ✅ OneDrive still exists. ✅ iMessage still exists. ✅ Bluetooth still exists. ✅ AirDrop still exists. ✅ The entire web still exists. Scammers: "No problem. See you tomorrow on another platform." Meanwhile, millions of legitimate users who rely on Telegram for: College and study groups Open-source communities Cybersecurity research Software development Startups and businesses Education and learning News and information sharing are left wondering what they did wrong. The platform changes. The abuse doesn't. Target the criminals. Not the communication tools.

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  EVILxJUG (@EVILXJUG) reported 49 minutes ago

  🚨Your goal this week-DELETE your DIGITAL FOOTPRINT!🚨 Let me help you: ——————— ✅Purchase any 1TB-10TB SSD Storage (this is dependent on your needs) or RAID server (can be ridiculously expensive, DO NOT RAID your storage if you do not know how to build, transfer, and manage a RAID!) ✅Have additional SSD storage drives. ✅Download all your media (pic, music, documents, videos, files, etc.) from your cloud services (iCloud, Google Drive, Microsoft One, Dropbox, etc.) and store them onto your purchased/physical SSDs as a backup. ✅Permanently, DELETE all your downloaded media files from those cloud-based services. ✅Permanently, clear the trash can (recycle bin), delete your cookies, delete your cache. ✅Tech Experience: iOS 🚨Apple automatically creates backup copies of your files on your devices. 🚨Even after managing or deleting data, you often need to search deep into your file system to permanently delete these original Apple backups.🚨Media transfers to Apple devices (iPhone, iPad, etc.) take longer than expected because:✅iOS creates multiple versions of each file during the transfer: original media, optimized media (for better storage efficiency), and backup files.✅All of this processing happens in the background while the transfer is ongoing.🚨DELETE THOSE FILES! ✅Your physical storage (SSDs, NOT HHDs), should be in your “firebag” (emergency bag, in case of fire- to grab and exit immediately to safety), stored in a cool place in your home. ✅After, you do all these things, your cloud-based storages should be freed up! Take down your subscriptions to what you think you should use and afford without compromising finances and data. DO NOT up your online cloud-based storage into the 1TB range EVER again! Limiting yourself to 100-500GB of cloud-based storage will keep you in check to store things physically in your home instead of online (this is healthy for your mental and to safeguard yourself from yourself). 🚨RING Devices!: if you own any ring devices or any security monitoring devices- CREATE A STATIC (NOT DHCP), CLOSED-CIRCUIT environment! Use EVERY protocol and firewalls to maintain your integrity infrastructure. Remove all unrecognized IP devices from YOUR ENTIRE NETWORK! Use ENCRYPTIONS to securely lockdown your network! 🚨DO NOT create a “guest” profile! 🌟Sorry, I’m speaking “nerd” lol, I don’t have time to explain it in laymen’s terms.

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  Spencer Baggins (@bigaiguy) reported 52 minutes ago

  SOMEONE BUILT A GITHUB REPO THAT TURNS TELEGRAM INTO UNLIMITED CLOUD STORAGE. 100% free. It is called UnlimCloud. Self-hosted-ish desktop app. Open source. Uses Telegram as the storage layer. You log in with your Telegram ID. Upload files. Download files. Organize folders. Manage pictures and videos in a gallery. That is it. No Google Drive upgrade screen. No Dropbox “you are out of space.” No iCloud begging for $2.99/month. No random startup holding your files hostage. Your Telegram. Your files. Your storage. Here is the full feature set: ↳ Uses Telegram as the backend storage layer ↳ Secure login with your Telegram account ↳ Upload, download, and organize files ↳ Folder-based file management ↳ Gallery for photos and videos ↳ Clean desktop app interface ↳ Built with Tauri ↳ Windows release available ↳ macOS and Linux coming soon ↳ MIT licensed ↳ Open source 885 GitHub stars. 125 forks already. Here is why this matters: For years, cloud storage companies trained everyone to rent space for their own files forever. Photos? Pay. Backups? Pay. Large folders? Pay. Team storage? Pay more. UnlimCloud is the opposite idea. Take an app people already use every day. Telegram. And turn it into a private cloud drive with a clean file manager on top. No storage subscription. No SaaS dashboard. No “pro” plan. Just a weird, useful, open-source hack that feels like it should not work this well. Built in HTML + Rust. MIT License. 100% Open Source.

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  Ilya Sandoval (@ilya_sandoval) reported 53 minutes ago

  @Dropbox having AGAIN problems with the payment between Apple and Dropbox and AGAIN NOONE FROM you guys help me

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  Hugo Bowne-Anderson (@hugobowne) reported 60 minutes ago

  Every day, people working with coding agents generate piles of threads containing decisions, corrections, failed approaches, and repeatable workflows. Then the session closes. The code survives. Most of the knowledge behind it disappears into chat history. @gregce10 is working on that problem. He previously worked at GitHub, Dropbox, and Google, served as CPO at Pluralsight, and is now co-founder and CPO of @specstoryai. This is a video of Greg at work. Sort of. SpecStory saves sessions from Claude Code, Codex, Cursor, Gemini, and other coding agents as Markdown inside the project. Then Lore mines them. Greg demonstrated the full workflow across 516 saved sessions: - Index the sessions locally instead of sending millions of tokens straight to a model - Turn each prompt, response, and next user prompt into an evidence-bearing "beat" - Use the follow-up to detect whether the human accepted, rejected, or corrected the agent's work - Find recurring practices and corroborate them across projects - Present candidate skills as dossiers with citations back to the original sessions - Install nothing without explicit human approval Five hundred and sixteen sessions stop being exhaust and become evidence for how Greg and his team actually build. Lore proposes the reusable practices. Greg decides which ones enter the skill library. Greg showed us all this and more live in our recent episode of *Show Us Your (Agent) Skills*. (video made using seedance 2.0 on @replicate!)