DigitalOcean

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

#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. ⬇️

Your favorite crustacean just got better. 🦞💧☁️ Deploy security-hardened, always-on #AI agents with our updated 1-Click setup. Now faster & more affordable—starting at just $12/month.

TheAgentic is partnering with Workato and DigitalOcean on tomorrow’s Agentic Healthtech Night in San Francisco. Featured speakers: • Martin Amps Member of Technical Staff at Anthropic • Elizabeth (Lizzie) Siegle, Developer Advocate at DigitalOcean • Chloe Condon, Developer Advocate at Workato The room brings together partners from across the AI stack, from foundation models to cloud, orchestration, and agent infrastructure, all focused on real health deployments. We’ll be continuing this conversation in the months ahead. #AI #Healthtech #AgenticAI #SanFrancisco

Heroku set the bar for PaaS. But, just this month, they’ve announced a shift to a sustaining model, with fewer new features ahead. If you’re building & shipping today, it may be time to reassess your platform. 🤔 We compared 11 Heroku alternatives across pricing, developer experience, scaling models, & ecosystem depth to help your teams pick the right platform for how they build today & in the near future. ⚖️🧑💻 If you want faster deploys, clearer pricing, & more flexibility without taking on heavy ops, our guide breaks down your best options.

If you’ve been relying on Heroku, it may be time to turn the page. 📖☁️🌊 #DigitalOcean's App Platform gives the "git push" simplicity you love at an affordable price with a single prompt migration process. Say goodbye to maintenance mode & migrate today. 👋

🚀☁️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. 🚀☁️

Our bug triage used to take 3 to 4 hours a week. Now it takes 12 minutes. Every software product generates errors. Some are critical, some are noise, and someone has to sort through all of them to figure out what actually needs fixing and in what order. It's not complicated work but it eats a lot of time and someone always volunteering to “take a closer look” (translation: disappear for two days). We pointed Claude Code at our Sentry instance through their MCP integration and let it rip. It inhaled four weeks of errors, cross-referenced them against our architecture docs, and figured out that three separate Sentry issues were actually the same ClickHouse query bug. Then it wrote up a prioritized fix plan with code snippets. Took 12 minutes. But wait there’s more. We then connected the Sentry MCP to an OpenClaw instance living on a $10/month DigitalOcean droplet. It watches issues as they come in, decides if something is actually serious, and send us a Telegram message. The whole thing costs less than a team lunch and it's running 24/7. The tedious parts of engineering are getting automated. The interesting parts aren't going anywhere.

“My GPUs are maxed out… so why does my LLM still feel slow?” 🤖😵💫 If you’ve ever stared at a loading cursor waiting for the first token to appear, you’ve felt the gap between theoretical performance & actual user experience. Raw FLOPs & tokens/sec don’t tell the full story of inference speed—& that’s where most teams get tripped up. If you’re running LLMs in production & trying to squeeze more performance per dollar, this framework helps you benchmark what matters—& avoid optimization whack-a-mole. ⬇️

I wrote an article on the DigitalOcean blog about Heroku’s shift to a “sustaining engineering” model. As a former product leader at Heroku, this one is bittersweet. Heroku reshaped modern app development and set the standard for developer experience. But when a platform stops investing forward, you can’t ignore that. Maintenance mode changes the equation. I’ve seen a wave of “just migrate” messaging. That’s not how real systems move. Code portability is the easy part. Data migration, networking, background workers, CI/CD, and traffic cutover are where the real work happens. DigitalOcean App Platform preserves the architectural model and developer workflow Heroku teams know, and it pairs that with a full cloud and AI inference platform built to keep evolving. We also provide structured migration support to help teams move deliberately and safely. If you’re evaluating your options, take a read. https://lnkd.in/gUWDsBfi