ContentPosts from @jazad89..
Link
@kaptain shared a link, 1 month, 1 week ago
FAUN.dev()

From Deterministic to Agentic: Creating Durable AI Workflows with Dapr

Dapr droppedDurable Agents- a mashup of classic workflows and LLM-driven agents that can actually get things done and survive rough edges. They track reasoning steps, tool calls, and chat states like a champ. If things crash, no problem: Dapr Workflows and Diagrid Catalyst bring it all back... read more  

From Deterministic to Agentic: Creating Durable AI Workflows with Dapr
Link
@kaptain shared a link, 1 month, 1 week ago
FAUN.dev()

Implementing assurance pipeline for Amazon EKS Platform

AWS released a full-stack CI/CD validation pipeline forAmazon EKS. It pulls in six layers of testing,Terraform,Helm,Locustload testing, and evenAWS Fault Injectionfor pushing resilience to the edge. The goal: bake policy checks, functional tests, and brutal load tests right into pre-deployment. Fewe.. read more  

Link
@kaptain shared a link, 1 month, 1 week ago
FAUN.dev()

v1.35: New level of efficiency with in-place Pod restart

Kubernetes 1.35, as you may know, introducedin-place Pod restarts(alpha). It's a real reset: all containers, init and sidecars included - without killing the Pod or kicking off a reschedule. Think restart without the cloud drama. Big win for workloads with heavy inter-container dependencies or massi.. read more  

Link
@kaptain shared a link, 1 month, 1 week ago
FAUN.dev()

1.35: Enhanced Debugging with Versioned z-pages APIs

Kubernetes 1.35 makes a quiet-but-crucial upgrade: z-pages debugging endpoints now returnstructured, machine-readable JSON. That means tools- not just tired humans - can parse control plane state directly. The responses areversioned, backward-compatible, and tucked behind feature flags for now... read more  

Link
@kaptain shared a link, 1 month, 1 week ago
FAUN.dev()

v1.35: Watch Based Route Reconciliation in the Cloud Controller Manager

Kubernetes v1.35 sneaks in an alphafeature gatethat flips the CCM route controller from "check every X minutes" to "watch and react." It now usesinformersto trigger syncs when nodes change - plus a light periodic check every 12–24 hours... read more  

Link
@kala shared a link, 1 month, 1 week ago
FAUN.dev()

The 2026 Data Engineering Roadmap: Building Data Systems for the Agentic AI Era

Data engineering’s getting flipped.AI agentsandLLMsaren’t just tagging along anymore - they’re the main users now. That means engineers need to buildcontext-aware, machine-readable data systemsthat don’t just store info but actually make sense of it. Think:vector databases,knowledge graphs,semantic .. read more  

The 2026 Data Engineering Roadmap: Building Data Systems for the Agentic AI Era
Link
@kala shared a link, 1 month, 1 week ago
FAUN.dev()

Streamlining Security Investigations with Agents

Slack broke down how it's threading AI into its product without torching user trust.Slack AIleans hard ontenant-specific data isolationandzero data retention- no leftover crumbs from LLM interactions. Instead of piping user data through someone else’s APIs, Slack runs LLMs onits own infrawhere it ca.. read more  

Streamlining Security Investigations with Agents
Link
@kala shared a link, 1 month, 1 week ago
FAUN.dev()

2025: The year in LLMs

2025 was the year LLMs stopped just answering questions and started building things.Reasoning modelslike OpenAI’s o-series and Claude Code took over tool-driven workflows. Asynchronous coding agentsbroke out. These models didn’t just write code - they ran it, debugged it, then did it again. That loo.. read more  

2025: The year in LLMs
Link
@kala shared a link, 1 month, 1 week ago
FAUN.dev()

Meet the ‘Mad Max’-Loving CEO Challenging Nvidia With a Renegade Chip

June Paik spurned a takeover offer from Meta Platforms last year. Now his South Korean company, FuriosaAI, has an AI chip entering mass production... read more  

Link
@kala shared a link, 1 month, 1 week ago
FAUN.dev()

My LLM coding workflow going into 2026

Anthropic saysClaude Code writes about 90% of its own code now. Why? Because devs are getting smart with AI. They're slicing problems into tight, testable chunks and running structured workflows that keep LLMs on a short leash. It's not just prompts anymore. Think context packaging, multi-agent setu.. read more  

My LLM coding workflow going into 2026