Send emails with Bolt.new and Mailtrap
Learn how to integrate Mailtrap with your Bolt.new application to send transactional emails and manage contacts without writing complex code.
Updates and recent posts about Gemini 3.. Story
Link
@anjali shared a link, 8 months, 3 weeks ago
Customer Marketing Manager, Last9
APM for Kubernetes: Monitor Distributed Applications at Scale
Understand Kubernetes APM by linking request flows with pod, node, and cluster data to get complete visibility at scale.
Story
@laura_garcia shared a post, 8 months, 3 weeks ago
Software Developer, RELIANOID
🌊 Load Balancing Smart Wave with RELIANOID — Built for Marine Telemetry
The Smart Wave platform is key for real-time telemetry from offshore buoys, vessels, and coastal stations. But how do you ensure it performs reliably — even over satellite links? We've published a new technical guide showing how to load balance Smart Wave using RELIANOID: ✅ MQTT & TCP ingestion for ..
Link
@faun shared a link, 8 months, 3 weeks ago
FAUN.dev()
Claude Code Ushers in a New Era of Agentic Programming
The rapid evolution of agentic coding is transforming software development, moving beyond traditional methods to intelligent, autonomous systems. Anthropic's Claude Code represents a significant leap in AI assistance for developers, shifting the paradigm from direct text manipulation to hands-off co.. read more
Link
@faun shared a link, 8 months, 3 weeks ago
FAUN.dev()
My Own DNS Server At Home
RunningBIND on Fedora with Podmanputs you in the driver’s seat—local DNS, full zone control, and no third-party middlemen. It handles staticforward/reverse zonesacross multiple IPv4 subnets, skips the mess of dynamic updates, and plugs into your router as a recursiveforwarding resolver. Call it a se.. read more
Link
@faun shared a link, 8 months, 3 weeks ago
FAUN.dev()
Vibe Coding Will Break Your Enterprise
Tools likeReplitandLovableare fine for quick hacks. Not for enterprise. They can’t handle service integration, durable state, or transactions that don’t fall apart. What enterprises need: realagentic systems. These aren’t glorified code editors—they’re stateful, resilient operators. They juggle work.. read more
Link
@faun shared a link, 8 months, 3 weeks ago
FAUN.dev()
Redis to acquire Decodable
Redis is buyingDecodable, the real-time streaming startup, to crank up itsRedis Data Integration (RDI)and beef up real-time data ingestion. Decodable’s stack lands in Redis Cloud first, syncing outside data into Redis fast enough to feed hungry AI agents real context. What's really happening:Redis i.. read more
Link
@faun shared a link, 8 months, 3 weeks ago
FAUN.dev()
Closer to the Metal: Leaving Playwright for CDP
The Browser-Use crew ditched Playwright and went straight to the Chrome DevTools Protocol. Why? Speed. Way faster element scraping, screenshots, and async automation. They didn't stop there—cooked up a custom CDP Python client with strong type safety, an event-driven core, and real support for crash.. read more
Link
@faun shared a link, 8 months, 3 weeks ago
FAUN.dev()
Top Tech Conferences & Events to Add to Your Calendar in 2025
Check out TechRepublic's events guide for a list of upcoming conferences, some of which are in-person and others that are virtual or hybrid. This list will be updated periodically to include new events and details... read more
Link
@faun shared a link, 8 months, 3 weeks ago
FAUN.dev()
What makes Claude Code so damn good (and how to recreate that magic in your agent)!?
Claude Code skips the multi-agent circus. One main loop. At most, one fork in the road. Everything runs through a flat message history, tracked by a tidy little to-do list. Over half its LLM calls? Outsourced to lighter, cheaper models likeclaude-3-5-haiku. Smart split: heavyweight reasoning when y.. read more
At its core, Gemini 3 emphasizes low hallucination rates, deep synthesis across large information spaces, and multi-step reasoning. Models in the Gemini 3 family are trained with scaled reinforcement learning for search and planning, enabling them to autonomously formulate queries, evaluate results, identify gaps, and iterate toward higher-quality outputs.
Gemini 3 powers advanced agents such as Gemini Deep Research, where it excels at producing well-structured, citation-rich reports by combining web data, uploaded documents, and proprietary sources. The model supports very large context windows, multimodal inputs (text, images, documents), and structured outputs like JSON, making it suitable for research, finance, science, and enterprise knowledge work.
Gemini 3 is available through Google’s AI platforms and APIs, including the Interactions API, and is being integrated across products such as Google Search, NotebookLM, Google Finance, and the Gemini app. It is positioned as Google’s most factual and research-capable model generation to date.
