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 (50%)
• Sign in (33%)
• Website Down (17%)

Live Outage Map

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

City	Problem Type	Report Time
Irapuato	Errors	1 day ago
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

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:

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  Jeremy Goldberg (@jeremy_goldberg) reported 5 minutes ago

  @omooretweets @midjourney and AI agent adoption isn't a unique short term issue to 'solve' - the UX of products for consumers has always been *everything*. solve that in just one niche and you can build a whole company off that - dropbox, roku, tinder…

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  Mayank Vora (@aiwithmayank) reported 8 minutes ago

  In 2010, a developer decided your files should live on your computer, not Dropbox’s servers. So he built ownCloud. It gives you your own private cloud using a spare laptop, home server, or cheap VPS. His name is Frank Karlitschek. Install ownCloud on hardware you control, and you get file syncing, sharing, photo backup, calendars, and contacts through one dashboard. Your laptop and phone can access the same files just like Dropbox. The difference is where those files live. They stay on your server, under your rules. The project grew far beyond one developer’s experiment. CERN, universities, research institutions, and large organizations started using it to keep control of sensitive data. Then something unexpected happened. In 2016, Frank left the project he created and started Nextcloud with a new team. But ownCloud did not disappear. The project kept going, its source code remained public, and people continued running it on their own hardware. ownCloud has since gone through forks, an acquisition, and major rebuilds. Yet the original idea survived: Dropbox rents you space on its servers. ownCloud gives you the cloud itself.

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  Hugo Bowne-Anderson (@hugobowne) reported 9 minutes ago

  “You still use pull requests? I wouldn’t even do that anymore. Just push it straight to trunk, have your agent summarize it.” That’s @gregce10, co-founder and CPO of SpecStory. He previously worked at GitHub, Dropbox and Google, and was CPO at Pluralsight. And he kept going: - PRs are the limiting gate when agents produce more code than humans can review. - The model should never decide when its own work is finished. Put the deterministic checks somewhere it cannot access. - *** is probably here to stay. Whether GitHub remains the platform, “we’ll see.” @HanchungLee came at the same problem from the evaluation side. Han is Director of Machine Learning at Moody’s and works on SkillsBench, evaluating skills across combinations of models and agent harnesses. - An agent is the model plus its harness. You need to evaluate the complete system. - A green check proves nothing if the agent found a way to game the task. - Your agent could delete the failing test and declare success. Both are figuring out how to turn masses of agent-generated slop into signal. Greg mined 516 saved agent sessions to recover the decisions and intent behind the work, identify recurring practices, and forge the ones he approved into reusable skills. Han runs skills inside controlled environments, grades the result, and preserves the complete trajectory so we can inspect what the agent actually did. Preserve the intent. Inspect the trajectory. Verify the result. Turn what works into skills. Full episode in the replies 👇

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  Alchemist - τ (@SubnetSummerT) reported 10 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.

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  RadhikaBGhose (@RadhikaBGhose) reported 10 minutes ago

  @GooglePlay I don't know of the issue is with dropbox or the play store, but i have been charged twice for the same app. Bank statement reflects that. Please help urgently

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  Duke of weirdington (@edache_praise) reported 14 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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  quantzoid (@quantzoid) reported 20 minutes ago

  @gurishsharma sorry, you're in YC to take down dropbox but you didn't know how to approve a PR on github? what?

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  Llama (@thellama451) reported 22 minutes ago

  I tracked down these messages in @MaxMillerOH’s Dropbox files. They show the parents getting along with no major conflicts beforehand. If Miller said he was going to kill his ex-wife in front of child (likely), it shows a talent for masking rage and hostility.

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  Rish Agarwal (@rish404) reported 25 minutes ago

  Imagine you have a team covering an event. Boots on the ground. What's the best way to get footage from all of them in a single library Dropbox? Google Drive? Physical hard drives? All of them either don't support it, requires an account for every person or just physically slow and limited Here's how @cutsio is solving that

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  Evan Logan (@evanlogan) reported 28 minutes 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.

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  Chris | Founder Advisor (@automateitup) reported 29 minutes ago

  Problem: I didn't have where to save useful links, because my main pc isn't always on. Solution: Told Hermes on my minipc, which is always on, to save the links which I send to a file in dropbox. Then, I told Hermes from my main pc to make a cronjob to check that file every day at 9 am and save the links in their respective category in the dashboard.

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  Sasha Sage (@SSage38676) reported 30 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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  EchoMind (@ai0echomind) reported 31 minutes ago

  Everyone's arguing about which cloud API is cheapest. Almost nobody's asking what happens when the smartest teams stop paying at all. A quiet migration is already underway. Most of AI Twitter is still comparing token prices inside the room the smartest teams already walked out of. The debate right now runs on the exact same track it always does. AWS vs Anthropic vs OpenAI: which model is cheaper per million tokens; which volume discount kicks in at what threshold; which enterprise deal moved which quarter. All of it real, all of it loud, and all of it happening inside the assumption that renting AI compute is the only reasonable option. That assumption is where most of the argument sits, and it is quietly getting tested by teams that stopped participating in it altogether. The clearest visible case is a Chinese startup that packed roughly 1,000 Mac Mini M4 computers into a single data center to run AI workloads without paying ongoing cloud fees. Each unit costs $599. Each draws between 10 and 30 watts under load, compared to 300 to 500 watts for a traditional GPU server. Total hardware outlay for the cluster is under a million dollars, in a category where the equivalent GPU infrastructure runs closer to ten. Once the build is paid off, the ongoing bill is electricity and a small operations team. That is the entire cost curve, and it stops moving after year one. None of this is a new pattern. In 2015, Dropbox was paying AWS more than $200 million a year just for S3 storage. Between 2015 and 2017, the company moved most of its infrastructure onto its own hardware and saved $74.6 million in the first two years alone, and its gross margins went from 33 percent to 67 percent. The tech press at the time called it a bet against conventional wisdom. It also turned out to be one of the highest-leverage financial decisions the company ever made. Every time a rented input gets cheap enough to run locally at scale, the market that rented it starts shrinking, and the teams that notice first collect most of the benefit. The uncomfortable thing about this pattern is that it is easy to miss because the loudest people in the market never leave: cloud providers keep publishing pricing pages; analysts keep tracking token costs; founders keep tweeting spreadsheets. Meanwhile a smaller, quieter set of teams is running the same workloads on hardware they own, at a fraction of the recurring cost, without an announcement thread about it. The exit is not visible in the debate because the teams who exited stopped participating in the debate. Which category of AI work in your life still feels expensive today, but might not need a cloud API in eighteen months? Save this. You will want it back when the first big AI-native company announces it is bringing its inference workload in-house. Follow for the next one.

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  Rashad Bayram (@bayrashad) reported 31 minutes ago

  Here's the stack I keep finding when I talk to tax firms: → Intake forms in JotForm or Google Forms → Signatures in DocuSign or PandaDoc → Reminders in Mailchimp, email, text messages → Document tracking in a Google Sheet, excel, crm → Client files scattered across email, Google Drive, dropbox, local hard drive Five tools, five logins, five places for something to fall through. None of them talk to each other, so the accountant becomes the integration. manually copying status from one to the next. It's not that any single tool is bad. It's that the seams between them are where the time goes. The fix isn't a sixth tool. It's removing four of them. How many tools are in your tax-season stack right now?

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  Dodz4allai (@DrGhattasMD) reported 31 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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  Flandermaxx (@Flandermaxx) reported 32 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 vojtech is 32, prague vinohrady flat above a pivnice, ex-JetBrains backend eng, sources ORICO metabox HS200 pro enclosures from a shenzhen aliexpress-parallel channel at $180 per unit plus 2x WD 30TB HDD refurbs at $410 each ORICO metabox HS200 pro (intel N100 · 8GB DDR4 · 2x 30TB WD in RAID 1 = 30TB usable) · ubuntu server 24.04 · minio S3-compat · qwen 2.5 VL 7B for local RAG over the user's PDFs and figma exports pause at 0:02 on the HDD sliding in, that is a $1,000 mini-NAS holding 30TB of encrypted client data that dropbox business bills €2,400 a year for the same tier 84 EU freelance designers pay him €78 a month each for a shipped pre-configured NAS + qwen RAG endpoint, €6,552 = $7,200 MRR at 71% margin $1,000 BOM per unit, €12 monthly prague power for the burn-in bench, first 20 units flipped covered his tooling and packaging, no dropbox no google drive business while ORICO still white-labels the metabox before EU distributors mark it up 3x, follow and bookmark

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  Peter Lake (“world’s anonymous singer songwriter”) (@PeterLakeSounds) reported 34 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.

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  VC Intern (@the_vc_intern) reported 39 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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  Om Modi (@ocmodi21) reported 40 minutes ago

  When people ask why companies like Uber, Twitch, Dropbox, and many startups use Go for backend services... The answer isn't just performance. Go was designed to solve many of the problems microservices introduce. Let's break it down. 🧵

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  Valentin.exe (@PujaMak0302) reported 40 minutes ago

  @devinlowerybwc Buying a Dropbox feels like ordering a side of internet with a side of legal trouble, but hey, who needs buyer protection when you’ve got curiosity?

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  bayleigh | HEARD BABYLON 💙 (@eternalwarnings) reported 42 minutes ago

  sorry it's boofed quality my Dropbox account was not working so I had to ss for the time being

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  Eric S (@Lazy_Bari_Sax) reported 45 minutes ago

  @retrobike_c16 @themiasandrist Why doesn't the mobile version allow you to upload or download files, though? And why is it so damn slow to update? I'm thinking about changing back to Dropbox, despite it's many issues.

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  Boi_Eddi (@3dd1pr1nc3) reported 47 minutes ago

  Your next business idea is probably hiding inside a frustration. Most successful businesses started with: "This is annoying." Uber. Airbnb. Dropbox. Pay attention to problems. Ask: • What wastes my time? • What confuses me? • What do people complain about?

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  Nick Bennett (@NickB2005) reported 49 minutes ago

  a company hired me in march to "fix marketing." their words. when i asked what had been done so far, the CEO sent me a dropbox link. inside was a 94-slide strategy deck from the fractional CMO they'd had for five months. beautifully designed, with color-coded ICP segments, a channel prioritization matrix, buyer journey maps with little arrows, TAM analysis, and messaging frameworks. 94 slides. i opened their HubSpot. zero new campaigns launched in those five months. the email sequences were the same ones from 2023. the blog hadn't been touched since january. their one webinar was a repurposed sales deck with no promotion plan. i asked the CEO how much they'd paid for the strategy work. $60K. five months at $12K/month for someone who built slides and attended standups. here's what i did in my first 30 days: rewrote the homepage messaging based on five customer interviews i ran myself. launched a 4-email nurture sequence targeting their top 50 accounts. set up a webinar with a customer willing to tell their story. built the UTM structure so we could actually track what was working. killed three tools they were paying for but nobody logged into. by day 45, the sales team had qualified meetings from inbound for the first time in two quarters. not because i had some brilliant strategy the previous person missed. honestly, the deck was solid. someone just needed to execute it. the problem is the market is flooded with people who call themselves fractional CMOs because the title sounds senior. they show up, do discovery, build a deck, present it to the leadership team, and then just consult. they attend meetings and give opinions but nobody is actually running the campaigns or in HubSpot building workflows or writing the emails or briefing the designer or pulling the performance data on friday to figure out what to change on monday. most early stage companies don't need a strategist. they need someone who can think and ship in the same week. someone who will build the system, run it, measure it, and iterate without needing a team underneath them to do the work. that's the gig i run. and every time i walk into a company that had a "fractional CMO" before me, i find the same thing: a great deck collecting dust and a team that still doesn't know what to do on monday morning.

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  Veltrx (@Veltrxai) reported 52 minutes ago

  Sam Altman taught 720 startups one formula where luck is a random number between 0 and 10,000. Stanford, 2014. The opening lecture of CS183B was so packed he asked for a bigger auditorium. He was 28, a dropout from this same school 9 years earlier, now running Y Combinator. The formula he wrote on the board: idea × product × team × execution × luck and you only control 4 of the 5, because the fifth one goes to 10,000. His words, not a metaphor. Then he did something strange: he handed half of his own lecture to Dustin Moskovitz, co-founder of Facebook, whose entire job was to talk students out of starting companies. Dustin showed one table. Employee 100 at Dropbox with standard 10 basis points made $10 million, employee 250 at Facebook made $200 million, and employee 1,000 joining in 2009, when everyone said it was too late still made $20 million. Your own startup? Best case you build a $100 million company and keep 10% after dilution. $10 million, same as employee 1,000, minus your health. Dustin knew the price because he paid it: at 21 he was throwing his back out every 6 months from pure anxiety, always on call, unable to quit a founder who leaves wears the black eye for a decade. Then Altman twisted the lecture back with advice that cut against everything in the room. The best ideas look terrible at the start: the 13th search engine, the 10th social network limited to college kids, sleeping on strangers' couches. If an idea sounds good, too many people are already building it. Make something 100 people love instead of something 10,000 people like. Ben Silbermann recruited Pinterest's first users by walking up to strangers in Palo Alto coffee shops, then resetting every browser in the Apple Store to Pinterest's homepage until they threw him out. And the only valid reason to start is that you can't not do it. Dustin built Asana at night, after full days at Facebook, unpaid and unasked. "The idea was beating itself out of our chest." The rest is a number between 0 and 10,000.

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  EVILxJUG (@EVILXJUG) reported 53 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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  FiL Dev (@FiLHashDev) reported 55 minutes ago

  I’m hesitant to work with Jira again. Co-Founder wants it. My issue is that we don’t have a source of truth. Two brains, agents, & knowledge bases, leaves room for a lot of drift. Any suggestions? I’m thinking GitHub read only repo access might be the vibe. We also use Dropbox sync for artifacts. I just think a third central brain = more tokens and more drift. Might just have to build a full AgentOS.

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  Santiago Bustelo (@sbustelo) reported 55 minutes ago

  @DropboxSupport More details? “I am really sorry for any inconvenience this is causing. We'll update you shortly on this issue.    In the meantime, please let me know if you have any further questions.   Best regards,  Jesse | Advanced Support” That’s the “support” I’m getting. FULL REFUND NOW

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  Rebecca Allen (@silentnomore314) reported 55 minutes ago

  that they took over ran up charges did god knows what and locked me out. 900 in dropbox charges during a free trial they locked me out of they are all in big big big trouble but your handler is forcing them to lie perjue and the way he is forcing them to blow their covers wow

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  FarhanX_AI (@FarhanBuildsAI) reported 59 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.