Terraform AWS provider 6.0 now generally available
Terraform AWS Provider 6.0bursts onto the scene with multi-region support. Now, devs can tweak 32 config files in one shot, slimming down memory bloat. 🌍💻.. read more
Updates and recent posts about Gemini 3.. Link
Link
@faun shared a link, 11 months, 1 week ago
FAUN.dev()
alden: detachable terminal sessions without breaking scrollback
Tired of losing terminal sessions and scrollback with tools liketmux,screen, ormosh? A new tool calledaldenkeeps your SSH shell alive after disconnects without breaking your native terminal scrollback. Unlike other solutions, it avoids emulating a terminal—so you get seamless reconnection and keep y.. read more
Link
@faun shared a link, 11 months, 1 week ago
FAUN.dev()
Amazon VPC raises default Route Table capacity
AWS VPClets your inner network architect cheer:500 routes per tablenow. That’s a cool 10x boost from before, turning network scaling from a headache into a child's play. 🚀.. read more
Link
@faun shared a link, 11 months, 1 week ago
FAUN.dev()
Automatic rollbacks are a last resort
Throw automatic rollbacks out the window. You don't need them.Continuous Deliverypartnered withhuman-driven resiliencesharpens up your software. When things go sideways, a speedy roll forward with a clever fix beats a blind retreat. Automatic rollbacks? They skip the surprises and rob you of learnin.. read more
Link
@faun shared a link, 11 months, 1 week ago
FAUN.dev()
AWS Lambda announces native support for Avro and Protobuf formatted Kafka events
AWS Lambdanow natively supportsAvroandProtobufformatted Kafka events, dancing through schema chaos with Glue and Confluent registries. Toss custom deserialization in the trash; plug inPowertoolsand let open-source Kafka consumer interfaces do the grunt work... read more
Link
@faun shared a link, 11 months, 1 week ago
FAUN.dev()
Inside Google’s Agent2Agent (A2A) Protocol: Teaching AI Agents to Talk to Each Other
Agent2Agent (A2A)is the new gospel for AI agents, taking over as the universal translator across platforms. Imagine 50+ tech behemoths waving its banner. A2A, clutchingJSON-RPC 2.0 over HTTP(S), crafts a chat apocalypse for AI, wiping out the custom integration chaos, much like the venerableInternet.. read more
Link
@faun shared a link, 11 months, 1 week ago
FAUN.dev()
The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity
FrontierLarge Reasoning Models (LRMs)crash into an accuracy wall when tackling overly intricate puzzles, even when their token budget seems bottomless.LRMsexhibit this weird scaling pattern: they fizzle out as puzzles get tougher, while, curiously, simpler models often nail the easy stuff with flair.. read more
Link
@faun shared a link, 11 months, 1 week ago
FAUN.dev()
AI at Amazon: a case study of brittleness
Amazon Alexa floundered amid brittle systems: a decentralized mess where teams rowed in opposing directions, clashing product and science cultures in tow... read more
Link
@faun shared a link, 11 months, 1 week ago
FAUN.dev()
How to Build an Asynchronous AI Agent Network Using Gemini for Research, Analysis, and Validation Tasks
The Gemini Agent Network Protocol introduces powerful AI collaboration with four distinct roles. Leveraging Google’s Gemini models, agents communicate dynamically for improved problem-solving... read more
Link
@faun shared a link, 11 months, 1 week ago
FAUN.dev()
Automate customer support with Amazon Bedrock, LangGraph, and Mistral models
Welcome to the jungle of customer support automation, fueled byAmazon BedrockandLangGraph. These tools juggle the circus act of ticket management, fraud sleuthing, and crafting responses that could even fool your mother. Integration with the likes ofJiramakes for a dynamic duo. Together, they tackle.. 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.
