📚Built on @0xPolygon, by our own engineers, $ICY takes co-creation within @dwarvesf Network to the next level. Join us, engage with us, learn with us, build with us, nurture the community with us, and get $ICY in return.
📌About ICY: https://t.co/tmO9Vq0iCr
People run into this curve all the time. At some point you add scripts, helpers and small agents around it because it feels like progress. Then you realise you spend more time keeping that stack alive than shipping.
Image credit goes to @thorstenball
Stagehand nails the middle ground: Playwright for deterministic steps + intent-based actions when UI shifts. A11y-tree targets > CSS. observe→preview, then act; extract(schema) for typed data; cache & replay.
Full breakdown by Chinh Le: https://t.co/erKCHBuLPz
We've built the best in house observability for Stagehand 🔭
Get inference time, token usage, LLM output, and more on the new dashboard.
No more black box, see everything behind the scenes.
See for yourself, get started with npx create-browser-app 🤘
By Lap Nguyen (Frontend @ Dwarves): E2B explained. Firecracker microVMs run untrusted agent code with VM-level isolation and fast cold starts. Covers architecture, lifecycle, snapshots, quotas, scaling.
Check out: https://t.co/4Nfc0oXyTI
📚 Build Deep Research Agent: From Question to Insight
Complex research rarely fits in one search box. The Deep Research workflow built with Dify Iterates, reasons, and sources until the answer is complete.
💡 Key workflow nodes include:
1) Start: capture the research topic and the loop budget
2) Exa Answer: gather background terminology
3) Intent LLM: clarify the real research goal
4) Loop: drive the iterative cycles
5) Reasoning LLM: frame better follow-up questions
6) Agent: execute searches, extract content, and reflect
7) Variable Assigner: update the state after each pass
8) Final Summary: synthesize a Markdown report with citations
Teams using this template cut research time dramatically and surface insights competitors miss.
Learn to implement this workflow: https://t.co/M0liVPesWW
Track traffic without GA4 or cookie banners and keep data ownership. Umami is a self-hosted, privacy-first alternative focused on minimal setup and end-to-end control.
Breakdown by Chinh Le (our frontend engineer): https://t.co/Toyk1E6ETP
Umami is now the most starred open source analytics project! And we launched later than everyone else 😎
A huge thanks to our community for making it happen. More great things to come! 🥳
#opensource#Analytics#GitHub
MEM0: Modular memory for agentic AI
Decouples memory from inference. Graph-based reasoning, implicit forgetting, multi-backend storage.
+26% acc, -91% latency, -90% tokens vs OpenAI Memory.
Mem0 breakdown was composed by @minhlq96. Check out the link below.
Crawl4ai crossed 50K start 🌟 (~5k forks). Thanks to all who shared their love and support. A project I started to build a tool for my company turned into a lovable open-source project at this scale. It's so rewarding to be part of an authentic change. I like to believe Crawl4ai made a positive change in the life of many developers and shared success in many projects.
We already released new features such as adaptive crawling, link preview, web page change observer, URL seeders and a few more, which I will talk about them soon. Also another project of mine, an agentic crawler , which I have been working on for a while based on Crawl4ai, will be out.
I also announce the official account of Crawl4ai @crawl4ai please follow, and continue your support, definitely it motivates me and my collaborators.
https://t.co/VhN3NtRlen
https://t.co/6apdISAYzn
https://t.co/waAsHDjXaQ
I appreciate all the new friends I found on this journey for their support in spreading the word, and collaboration: @aravind_karnam@nasrintohidi@engineerrprompt@Sam_Witteveen@tom_doerr@MervinPraison@ozenhati@jasonzhou1993@GithubProjects@omarsar0@Saboo_Shubham_@ai_for_success and many more.
Live Long and import Crawl4ai
Cline brings structured tool calls, streaming diffs, and shadow commits to VS Code. We put together a developer-first breakdown, how it works, where it shines.
Written by Chinh Le (frontend @ Dwarves): https://t.co/hBWEoKLLmb
ax framework is a TypeScript port of @DSPyOSS. Instead of writing prompts directly, you can pass arguments to the framework and it will generate the prompts, which makes managing the semantics of the codebase a bit easier.
This piece is a part of the team’s breakdown series.
Most AI tools just stack models, but context and collaboration still get lost. zen-mcp-server by
@BusyMac gives Claude real multi-model memory, so your AI team actually works together, not in silos.
Here’s how we break it down at Dwarves: https://t.co/oGpqUUohwH
Somebody hooked up Claude Code to pair program with o3 and Gemini 2.5 via MCP for an all-star coding lineup 🤯
- Claude controls the work
- Can call out to Gemini and o3 for tasks and input
- Works around MCP limit by using prompt files
Check out Zen MCP (link below)
Some of the biggest Claude Code fans are running it continuously in the background, 24/7.
These uses are remarkable and we want to enable them. But a few outlying cases are very costly to support. For example, one user consumed tens of thousands in model usage on a $200 plan.