ContentPosts from @rchengvariant..
Link
@faun shared a link, 1 week ago

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..

Vibe Coding Will Break Your Enterprise
Link
@faun shared a link, 1 week ago

Le Chat now integrates with 20+ enterprise platforms—powered by MCP—and remembers what matters with Memories.

Le Chat now includes20+ secure, MCP-based connectorsfor tools like GitHub, Snowflake, Stripe, and Jira. That means in-chat search, summaries, and actions—straight from enterprise systems. Developers can plug in their owncustom MCP connectors, and run Le Chat wherever it fits: on-prem, private cloud..

Le Chat now integrates with 20+ enterprise platforms—powered by MCP—and remembers what matters with Memories.
Link
@faun shared a link, 1 week ago

OpenAI to launch its first AI chip in 2026 with Broadcom, FT reports

OpenAI’s firstin-house AI chipis nearly out of the oven. It’s headed for fabrication atTSMCand built to handle OpenAI’s own workloads—no outside sales, according to theFinancial Times. Why it matters:Big AI shops are going vertical. Custom silicon means tighter control over runtime, reliability, an..

OpenAI to launch its first AI chip in 2026 with Broadcom, FT reports
Link
@faun shared a link, 1 week ago

GPT-5 Thinking in ChatGPT (aka Research Goblin) is shockingly good at search

GPT-5's“thinking” modeljust leveled up. It's not just answering queries—it’s doing full-on research. Picture deep, multi-step Bing searches mixed with tool use and reasoning chains. It reads PDFs. Analyzes them. Suggests what to do next. Then actually does it. All from your phone. What’s changing:L..

GPT-5 Thinking in ChatGPT (aka Research Goblin) is shockingly good at search
Link
@faun shared a link, 1 week ago

Simplifying Large-Scale LLM Processing across Instacart with Maple

Instacart builtMaple, a backend brain for handling millions of LLM prompts—fast, cheap, and shared across teams. It’s not just another service. Maple runs onTemporal,PyArrow, andS3, strip-mines away provider-specific boilerplate, auto-batches prompts, retries failures, and slashes LLM costs by up t..

Simplifying Large-Scale LLM Processing across Instacart with Maple
Link
@faun shared a link, 1 week ago

Hermes V3: Building Swiggy’s Conversational AI Analyst

Swiggy just gave its GenAI tool, Hermes, a serious glow-up. What started as a simple text-to-SQL bot is now acontext-aware AI analystthat lives inside Slack. The upgrade? Not just tweaks—an overhaul. Think: vector-based prompt retrieval, session-level memory, an Agent orchestration layer, and a SQL..

Hermes V3: Building Swiggy’s Conversational AI Analyst
Link
@faun shared a link, 1 week ago

Best Practices for High Availability of LLM Based on AI Gateway

Alibaba Cloud’s AI Gateway just got sharper. It now handlesreal-time overload protectionandLLM fallback routingusing passive health checks, first packet timeouts, and traffic shaping. It proxies both BYO and cloud LLMs—think PAI-EAS, Tongyi Qianwen—and redirects load spikes or failures on the fly. F..

Best Practices for High Availability of LLM Based on AI Gateway
Link
@faun shared a link, 1 week ago

Why language models hallucinate

OpenAI sheds light on the persistence ofhallucinationsin language models due to evaluation methods favoring guessing over honesty, requiring a shift towards rewarding uncertainty acknowledgment. High model accuracy does not equate to the eradication of hallucinations, as some questions are inherentl..

Why language models hallucinate
Link
@faun shared a link, 1 week ago

The Big LLM Architecture Comparison

Architectures since GPT-2 still ride transformers. They crank memory and performance withRoPE, swapGQAforMLA, sprinkle in sparseMoE, and roll sliding-window attention. Teams shiftRMSNorm. They tweak layer norms withQK-Norm, locking in training stability across modern models. Trend to watch:In 2025,..

The Big LLM Architecture Comparison
Link
@faun shared a link, 1 week ago

From Zero to GPU: A Guide to Building and Scaling Production-Ready CUDA Kernels

Hugging Face just dropped Kernel Builder—a full-stack toolchain for building, versioning, and shippingcustom CUDA kernels as native PyTorch ops. Kernels arearchitecture-aware,semantically versioned, andpullable straight from the Hub. It tracks changes with lockfiles and bakes inDocker deploysout of..