Hot off the presses: edit your production code from Telegram with ease. 📰😌⬇️
DigitalOcean
Software Development
Broomfield, Colorado 160,655 followers
The comprehensive agentic cloud. ☁️
About us
DigitalOcean simplifies cloud computing so businesses can spend more time creating software that changes the world. With its mission-critical infrastructure and fully managed offerings, DigitalOcean helps developers at startups and growing digital businesses rapidly build, deploy and scale, whether creating a digital presence or building digital products. DigitalOcean combines the power of simplicity, security, community and customer support so customers can spend less time managing their infrastructure and more time building innovative applications that drive business growth.
- Website
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https://www.digitalocean.com
External link for DigitalOcean
- Industry
- Software Development
- Company size
- 1,001-5,000 employees
- Headquarters
- Broomfield, Colorado
- Type
- Public Company
- Founded
- 2012
- Specialties
- Cloud Computing, Cloud Servers, Virtual Hosting, Cloud Hosting, Cloud Infrastructure, Simple Hosting, and Virtual Servers
Locations
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Primary
Get directions
105 Edgeview Dr
Broomfield, Colorado 80021, US
Employees at DigitalOcean
Updates
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DigitalOcean reposted this
I'm thrilled to announce that I made a code change to a live website while waiting for a burrito at Chipotle. No laptop. No terminal. No IDE. I sent a Telegram message. There's an open source project called "claude-code-telegram" - it runs Claude Code on your server and takes instructions over Telegram, locked to just your account. I set it up on a DigitalOcean Droplet, sent it a message from Telegram, and it updated my site. Absolutely ridiculous and amazing! Wrote up all the steps if you want to try it yourself 😊
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DigitalOcean reposted this
Super excited that DigitalOcean is cohosting OpenClaw🦞 Demo && Hack Night w/ Convex and CodeRabbit this Thursday in SF! 🙌 We’ll also have drinks && pizza 🍕 Hope to see some familiar faces there 👀 It's a wild time to be a builder and we have limited capacity, so RSVP here to secure your spot! https://luma.com/mlq9k00x
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Anthropic's Sonnet 4.6 has landed on DigitalOcean’s Agentic Inference Cloud. 🚀☁️🤖 Stop wrestling with model infrastructure and start building. With Gradient™ AI Serverless Inference, your team can deploy Anthropic’s cutting-edge model directly alongside your existing apps and data. Experience scalable inference on a single, unified platform.
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Ship faster with Claude Sonnet 4.6 on DigitalOcean’s Agentic Inference Cloud. Run code, agents, and other workflows without managing infrastructure, so your team can focus on scaling. 🔗 https://do.co/4cvYeCz Access Anthropic’s most capable Sonnet-class model via Gradient™ AI Serverless Inference alongside your apps and data with predictable usage-based billing and security-hardened defaults.
This is Claude Sonnet 4.6: our most capable Sonnet model yet. It’s a full upgrade across coding, computer use, long-context reasoning, agent planning, knowledge work, and design. It also features a 1M token context window in beta. Sonnet 4.6 has improved on benchmarks across the board. It approaches Opus-level intelligence at a price point that makes it practical for far more tasks. It also shows a major improvement in computer use skills. Early users are seeing human-level capability in tasks like navigating a complex spreadsheet or filling out a multi-step web form. For Claude in Excel users, our add-in now supports MCP connectors, letting Claude work with tools like S&P Global, LSEG, Daloopa, PitchBook, Moody's and FactSet. On our API, Claude's web search and fetch tools now write and execute code to filter search results, improving response quality. Code execution, memory, programmatic tool calling, tool search, and tool use examples are now generally available. Claude Sonnet 4.6 is available now on all plans, Cowork, Claude Code, our API, and all major cloud platforms. We've also upgraded our free tier to Sonnet 4.6 by default. Read more: https://lnkd.in/e4sDewFT
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DigitalOcean reposted this
Many companies are wasting money because of an outdated, pervasive misunderstanding of AI hardware Part of what makes LLMs expensive to run it is the hardware they run on. For now, GPUs are the only viable option for LLM inference at scale. It's well known that there are severe supply constraints for GPUs, but what a lot of companies don't know is that they are making the problem worse for themselves. They're artificially shrinking potential supply for themselves by only considering NVIDIA GPUs instead of both NVIDIA and AMD GPUs. Years ago, this made sense as NVIDIA's CUDA was required to run most neural models. But it is 2026 and AMD has made huge progress on its CUDA equivalent, ROCm CUDA and ROCm are basically at parity for the sorts of LLM inference that many companies are doing, and not considering AMD is costing them (potentially a lot of) money. DigitalOcean recently worked to bring Character.AI's production inference costs down by 50%, and part of that savings is attributable to using AMD. There are a lot of factors to consider when choosing hardware for your particular use case, but make sure you're not working with an outdated fact set.
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🚀☁️Learn how to deploy and scale AI inference workloads without managing infrastructure using DigitalOcean’s serverless platform. See how to reduce costs, improve performance, and move from prototype to production faster. 🚀☁️
Serverless Inference: Fast, Cost-Efficient AI Workloads on DigitalOcean
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We had such a fun time chatting with and learning from builders at our AI Healthtech Night with Workato and TheAgentic in San Francisco 🌉on Wednesday! Thank you to speakers Martin Amps, Chloe Condon, Elizabeth (Lizzie) Siegle, and Max Bukow. What AI verticals would you like to see meetups around? Let us know in the comments🧵 #WorkatoAILabSF
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#AI agents now have their own social network—& yes, it’s real. 🤖🦞🤯 #Moltbook is a Reddit-style platform where millions of OpenClaw agents post, debate security issues, & document autonomous work—often while humans sleep. It’s a fascinating experiment in agent-to-agent interaction, but it also raises big questions around authenticity, security, & whether this hints at #AGI (spoiler: not quite). We're breaking down what Moltbook is, how it works, what #agents are actually posting about, & what developers should know before connecting their own agents. ⬇️