Join us

ContentUpdates and recent posts about Hexabot..
Link
@kaptain shared a link, 3 months ago
FAUN.dev()

How Does Kubernetes Self-Healing Work? Understand Self-Healing By Breaking a Real Cluster

KubeLab boots a three-nodeKubernetescluster and runs seven failure simulations. It deploysNode.js,Postgres,Prometheus, andGrafana. Then it deletes pods, forcesOOMKill, throttles CPU, drains nodes, and scales aStatefulSetto zero. Each scenario surfaces fixes:readiness probes,PodDisruptionBudget, anti.. read more  

How Does Kubernetes Self-Healing Work? Understand Self-Healing By Breaking a Real Cluster
Link
@kaptain shared a link, 3 months ago
FAUN.dev()

The great migration: Why every AI platform is converging on Kubernetes

The CNCF survey finds82%of container users runKubernetesin production.66%of GenAI hosts use it for inference. Kubernetes now stitches data processing, distributed training, LLM inference, and autonomous agents viaSpark,Kubeflow,Kueue,KServe, andArmada. GPU sharing and scheduling advanced withMIG, ti.. read more  

The great migration: Why every AI platform is converging on Kubernetes
Link
@kaptain shared a link, 3 months ago
FAUN.dev()

How WebAssembly plugins simplify Kubernetes extensibility

Helm 4runsWebAssembly (Wasm)plugins to executeWASImodules insideOCIcontainers and VMs.Helmtemplates standardize module lifecycle. The Wasm plugin adds instruction-level sandboxing and Kubernetes segmentation.Helm 4preserves portability acrossx86/ARM. Compared withHelm 3plugins, it shows up to a 40% .. read more  

Link
@kaptain shared a link, 3 months ago
FAUN.dev()

It's Not Kubernetes. It Never Was

The complexity in managing Kubernetes clusters is a reflection of the organizational decisions and lack of processes within the teams operating them. The move towards multi-cloud environments without sufficient planning or resources has exacerbated these issues. Platform engineering solutions offer .. read more  

It's Not Kubernetes. It Never Was
Link
@kala shared a link, 3 months ago
FAUN.dev()

AI as tradecraft: How threat actors operationalize AI

Microsoft observes threat actors operationalizeAIandLLMsacross the cyberattack lifecycle. They accelerate reconnaissance, phishing, malware development, and post‑compromise triage. Actors abusejailbreakingtechniques andGANs. They craft personas, generate look‑alike domains, embed runtime‑adaptive pa.. read more  

AI as tradecraft: How threat actors operationalize AI
Link
@kala shared a link, 3 months ago
FAUN.dev()

Reasoning models struggle to control their chains of thought, and that’s good

OpenAI's paper unveilsCoT-Control: an open-source suite of 13,000+ tasks fromGPQA, MMLU-Pro, HLE, BFCLthat measuresCoTcontrollability. Evaluations on 13 models show compliance at 0.1%-15.4%. Compliance is tiny. Controllability improves with model size. It drops as reasoning chains lengthen and after.. read more  

Reasoning models struggle to control their chains of thought, and that’s good
Link
@kala shared a link, 3 months ago
FAUN.dev()

The L in "LLM" Stands for Lying

The author arguesLLMschurn out fast, generic answers by remixing low-quality source material. They seed brittle, repetitive code viavibe-coding. The remedy: requiresource attributionand auditable inference to separate originals from forgeries and to reshape model training and deployment. Requiringso.. read more  

The L in "LLM" Stands for Lying
Link
@kala shared a link, 3 months ago
FAUN.dev()

The reason big tech is giving away AI agent frameworks

A catalog of majoragent frameworks: LangGraph, CrewAI, Google ADK, AWS Strands, Microsoft Agent Framework, OpenAI Agents SDK, Mastra, Pydantic AI, Agno. Hyperscalers co-design free SDKs (e.g.,Strands,ADK). They tie those SDKs to metered runtimes -Bedrock,Vertex AI. Revenue shifts to inference and de.. read more  

Link
@kala shared a link, 3 months ago
FAUN.dev()

LLMs are getting better at unmasking people online

Researchers at ETH Zurich show LLMs can stitch anonymous bios to public web data and reidentify users across platforms. Fine-tuned models and agent chains parse unstructured text and automate deanonymization in minutes at penny-level inference costs... read more  

LLMs are getting better at unmasking people online
Link
@devopslinks shared a link, 3 months ago
FAUN.dev()

Amazon is back up after outage affecting tens of thousands of shoppers

Amazon faced an outage, affecting tens of thousands of shoppers globally on Thursday afternoon. Downdetector reported a surge in complaints, peaking at 20,000 by 3:49 p.m. ET. The outage involved checkout and pricing errors caused by a software code deployment... read more  

Hexabot is a self-hosted AI chatbot and workflow automation platform designed for developers, startups, and teams that need more control over AI-powered business automation.

Unlike simple chatbot builders or fully prompt-based agents, Hexabot combines visual workflow design with real software extensibility. Teams can create conversational flows, automate business processes, connect APIs, build custom actions, integrate messaging channels, and add AI reasoning steps where they make sense.

Built with a modern JavaScript and NestJS foundation, Hexabot is designed for developers who want to move fast without losing control. It supports extensibility through plugins, custom actions, channels, and reusable workflow components, making it suitable for customer support automation, sales workflows, internal operations, lead qualification, RAG-based assistants, and multi-channel conversational AI.

Hexabot is fair-core licensed and self-hosted, making it a strong choice for teams looking for a flexible alternative to closed SaaS automation platforms while keeping ownership of their infrastructure, data, and customization layer.