Two Average Devs

Two Average Devs

Two developers discussing AI, local LLMs, and the business and technology surrounding them.

Episódios

  1. 26 de out.

    Episode 7 - Code to hit a local LLM, Demo of Financial app harness, and DeepSeek v4.1 Flash news

    In this episode, Roger and Jay talk about the latest news around DeepSeek v4.1 Flash, reverse engineering of software with AI, and write a simple app in Python to call make an API call to a local LLM. We look at the wire protocol to help developers understand more deeply what goes on under the covers. We also show an in-progress financial app AI harness and some of the tradeoffs to be aware of when working on a harness. YouTube:https://youtu.be/Y2SQpeh5gHI Spotify: https://podcasters.spotify.com/pod/show/jo71/episodes/Episode-7---Code-to-hit-a-local-LLM--Demo-of-Financial-app-harness--and-DeepSeek-v4-1-Flash-news-e3r3i08 Apple Podcasts: https://podcasts.apple.com/us/podcast/episode-7-code-to-hit-a-local-llm-demo-of/id6806730077?i=1000798140252 Substack: https://jayongg.substack.com/p/episode-7-code-to-hit-a-local-llm-8c9 00:00 Intro 00:40 Deepseek v4.1 Flash update 08:42 Windows Media debugging 11:40 Reverse Engineering with AI 13:12 Studying Computer Science 16:06 Writing an app to talk to a Local LLM served from llama.cpp 29:38 Financial app harness example

  2. 13 de out.

    Episode 6: Getting up and running with llama.cpp

    Roger and Jay show and discuss getting llama.cpp up and running on your PC, even without a GPU. We go into detail around building llama.cpp (or where to download it), where to get a model, and we run it, with some fun queries. YouTube: https://youtu.be/x5G4DMWwdsg Spotify: https://open.spotify.com/episode/7buRgF4LmmNA1GilgjRRUA?si=jBNSRYR8SdWYEoXl2Ex3og Apple Podcasts: https://podcasts.apple.com/us/podcast/two-average-devs/id68067300Episod77 Substack: https://jayongg.substack.com/p/episode-6-getting-up-and-running-82e?r=95m6jr 00:00 Intro 01:30 Installing Llama.cpp 05:50 Getting llama.cpp code 13:59 Downloading and installing a model 18:21 Running llama.cpp 25:30 Discussion on models, Ling, and Qwen, and optional homework.

  3. 10 de out.

    Episode 5: Surface Ultra Announcement

    Jay and Roger talk about the excitement and implications of the Surface Ultra and it demonstrates Microsoft's belief in the future of local LLMs. Explainer about the Surface hardware: https://lindybeat.net/podcasts/2avgdevs/05/ YouTube: https://youtu.be/_Hm443LB1TY Spotify: https://open.spotify.com/episode/3Lzh1UPmVovC4DzDgnGX7W?si=17QJYOuuT0W1HxwiHRa41Q Apple Podcasts: https://podcasts.apple.com/us/podcast/two-average-devs/id6806730077?i=1000795171934 Substack: https://substack.com/@twoaveragedevs/note/p-219777376?utm_source=notes-share-action&utm_medium=web

  4. 8 de out. ·  Bônus

    What do you do if you've been on leave for a year?

    One of my former team members asked me for advice after he was on leave for a year. This is what I told him.

  5. 26 de set.

    Episode 4: Getting Started with Local LLMs

    In this episode, we talk about running local LLMs, explaining how to get started and various . We also kick off a prompt to generate a tool during the episode, live, and you can see the results! References: Tool creation Prompt: https://lindybeat.net/podcasts/2avgdevs/04/tool-creation-prompt.md HuggingFace page for Qwen 3.8 27b: https://huggingface.co/Qwen/Qwen3.8-27B LM Studio: https://lmstudio.ia PI Coding Agent: https://pi.dev Artificial Analysis: https://artificialanalysis.ai/ 00:00 Intro 01:42 Background Prompt - Creating a Disk Space Visualizer Tool 05:08 LM Studio 07:29 LM Studio Get your first model 14:28 Quantization 17:30 LM Studio - Context Length 20:04 LM Studio - App Settings 25:39 LM Studio - Server settings 28:30 Pi Harness 33:55 Pi Harness - Extensions 35:47 Using Pi 36:38 Pi + Qwen3.8 27B finishing up the tool 39:53 Artificial Analysis for model evaluations and hallucination measurements 45:35 Ballast - Disk Info Visualizer 48:05 Context window size

  6. 13 de set.

    Episode 3: OpenAI and Hugging Face

    Jay and Roger talk about the OpenAI/HuggingFace hack, in deeper technical depth than what you might see in the media. Based on the independent METR report and OpenAI information. Here's the main distilled report for those who want to read or follow along: https://lindybeat.net/podcasts/2avgdevs/03/openai-hf-incident/In this episode, we have some visual aids and diagrams. If you're only listening by audio, you should be able to understand the episode without it, but you can check out the visuals online. References: METR report: https://metr.org/blog/2026-08-26-openai-hugging-face-incident-investigation/ https://youtu.be/AWnWTHiJstM?is=paOvYdYaV8-42GVq Apple Podcasts: https://podcasts.apple.com/us/podcast/two-average-devs/id6806730077?i=1000789253823 Spotify: https://open.spotify.com/show/2fppEDcBGDpdA62h4fYiWe?si=ZGb60KNkRaWl_EILY6_7PQ&utm_source=copy-link

  7. 5 de set.

    Episode 2: What are Open Weight models, and how to get started with local models.

    Roger and Jay talk about frontier, open weight, and open source models. We talk about our experiences and how we got started, and how you can get started too. Show Notes: • LinkedIn’s model: https://venturebeat.com/infrastructure/inside-linkedins-generative-ai-cookbook-how-it-scaled-people-search-to-1-3 • LM Studio Bionic - Agent for Work and Code: https://lmstudio.ai/ • Hugging Face – The AI community building the future: https://huggingface.co/ • AI Model & API Providers Analysis | Artificial Analysis: https://artificialanalysis.ai/#intelligence • Unsloth Studio: https://unsloth.ai/docs/new/studio • Subreddits on Local LLMs: https://www.reddit.com/r/LocalLLaMA/ https://www.reddit.com/r/LocalLLM/ • Independent Local AI Benchmarks: https://local.ai YouTube: https://lnkd.in/gAuKdfKK RSS: https://lnkd.in/gvWmh4xB Apple Podcasts: https://lnkd.in/gsi3idmp Spotify: https://lnkd.in/gr69pfa7

  8. 31 de ago.

    Episode 1: Intro and AI News

    First episode, intro of the show. Jay and Roger discuss AI News and recent happenings. YouTube: https://lnkd.in/gakRUH9J RSS: https://lnkd.in/gvWmh4xB Apple Podcasts: https://lnkd.in/gsi3idmp Spotify: https://lnkd.in/gr69pfa7

  • 8 episódios

Sobre

Two developers discussing AI, local LLMs, and the business and technology surrounding them.

Informações

  • Criado por
    Two Average Devs
  • Anos de atividade
    2026
  • Episódios
    8
  • Classificação
    Livre
  • Copyright
    © Two Average Devs
  • Site do podcast
    Two Average Devs