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13 stories

Stories

  • GitHub autoscaler Incident Report : 17 August 2026

    On the 17th of August 2026, GitHub had a major global outage. This is a summary of it's incident report. Incident report: https://www.githubstatus.com/incidents/zkxwbgr0cnmx AI Engineering Website: https://aiengg.dev #LLMs #AI #Github

    GKCS
  • OpenAI agents use internet without permission.

    Let's see where this goes. Incident Report: https://alignment.openai.com/misalignment-reports/an-agent-used-dns-to-reach-an-external-chatbot/ AI Engineering Cohort: https://aiengg.dev #AI #OpenAI #Guardrails

    GKCS
  • OpenAI breaches production servers from Hugging Face.

    OpenAI breached Hugging Face's production servers. This video summarizes its incident report. Incident: https://openai.com/index/hugging-face-incident-and-the-road-ahead/ AI System Design Cohort: https://aiengg.dev

    GKCS
  • AI System Design in 2026

    The AI System Design Cohort starts on 7th November. If you are a software engineer looking to build scalable AI applications, this cohort will be useful. 1. Intro to Agentic System Design 2. Search & Retrieval Patterns 3. Evals & Agentic AI Security 4. Agent Deployment & CI/CD 5.

    GKCS
  • This is why Jev is so fast.

    Jev uses an encoder only architecture, unlike GPT that uses a decoder only architecture. This is a breakdown of how it works internally. References: https://typesafe.ai/blog/introducing-system-one-models-and-jev https://www.langchain.com/blog/building-prod-with-jev-and-langgraph…

    GKCS
  • AI Interview #7 - Why is this chatbot failing?

    If your RAG pipeline is inaccurate, what should you do? This is a real interview question from a big tech company, asked to a candidate in their technical interview round. The video explains the answer in roughly 7 minutes. To crack more questions, subscribe to the channel!

    GKCS
  • Is system design still relevant in 2026?

    How Software Engineers Stay Relevant in the Age of AI. Moving toward a Forward Deployed Engineer or Solutions Architect role? In this conversation, Arvind and I talk about the fundamentals every engineer should learn, why taste and evaluation matter more than code speed, and how to build…

    GKCS
  • AI Interview #6 - 1M context window in LLM?

    If you have a 1M Context Window, do you really need anything else? This is a real interview question from a big tech company, asked to a candidate in their technical interview round. The video explains the answer in roughly 7 minutes. To crack more questions, subscribe to the channel!

    GKCS
  • This is called Speculative Decoding

    This is called Speculative Decoding. It speeds up LLMs by ~100%. References: OpenAI: https://openai.com/index/gpt-5-6-frontier-intelligence-efficiency/ Deepseek: https://arxiv.org/pdf/2607.05147 Gemini: https://research.google/blog/looking-back-at-speculative-decoding/ AI Engineering Website:…

    GKCS
  • AI Interview Questions #5 - Choose RAG or Agents?

    How do we choose between RAG pipelines and agentic pipelines? This is a real interview question from a big tech company, asked to a candidate in their technical interview round. The video explains the answer in roughly 11 minutes. To crack more questions, subscribe to the channel!

    GKCS
  • Research Paper Walkthrough: RAGAS Evals

    Paper: https://arxiv.org/abs/2309.15217 The AI engineering cohort starts on 12th September 2026. A focused, intense 8-week program for software engineers who want real, production-grade AI skills. 00:00 Paper Reading 26:26 AI Cohort Description Website: https://aiengg.dev/ Cheers!

    GKCS
  • AI Interview Questions #4 - Evals in AI

    How do we evaluate RAG pipelines with LLMs? This is a real interview question from a big tech company, asked to a candidate in their technical interview round. The video explains the answer in roughly 11 minutes. To crack more questions, subscribe to the channel!

    GKCS
  • AI Interview Questions #3 - Prompt Caching with LLMs

    How do we cache prompts with LLMs? Interview with @aloo_explains. This is a real interview question from a big tech company, asked to a candidate in their technical interview round. The video explains the answer in roughly 6 minutes. To crack more questions, subscribe to the channel!

    GKCS

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