LayerX

LayerX

AI podcast for the teams and leaders building with it. We share real use cases, experiments, and insights on how to apply AI to your business. Made by the team at LayerX.

Épisodes

  1. -5 j

    We ran a hackathon where 10 AI Agents built and judged each other

    LayerX ran an AI agents hackathon: 10 frontier models built a real app from one brief, then peer-judged each other. The results say more about shippability than any benchmark.

  2. 15 juin

    How to Control LLM Output: Temperature, Top-P & Beyond

    Control LLM output with temperature, top-p, penalties, and logprobs to ship reliable AI automation. A practical field guide with a per-task cheat sheet

  3. 31 mai

    We entered Fixathon as hackers. We left as winners.

    How a 3-person LayerX team with no ML background won Fixathon, building Cadence: an explainable AI model that predicts factory production time from panel data.

  4. 26 mai

    Coding with AI Agents: the 20% nobody talks about

    Coding agents write 80% of the code. The other 20% is engineering, and it matters more than ever. Eleven lessons from building with agents at LayerX.

  5. 25 mai

    Everyone talks about taste. It's all about trust.

    Taste differentiates your product. Trust determines whether anyone actually uses it for what matters.

  6. 17 mai

    The highest ROI activity in AI right now isn't on your screen

    Why the best opportunities in AI keep coming from rooms, not feeds. What two days at SIM Conference actually taught me.

  7. 11 mai

    The new CMO is a systems architect

    The job of a senior marketer has shifted from managing people to designing systems.

  8. 5 mai

    The next great software company won't sell software

    AI is shifting from copilots to autopilots. Why selling outcomes beats selling tools, and how we're building LayerX for the Service as a Software era.

  9. 29 avr.

    Giving our blog a voice: how we turned posts into audio with open models, locally, on a Mac

    How we turned every LayerX blog post into an audiobook-style narration using open-source TTS models (Kokoro, Qwen3 TTS) running locally on Apple Silicon with MLX. No cloud, no per-character billing, no third-party data exposure.

  10. 15 avr.

    Why I Stopped Using Other People's AI Agents and Built My Own

    The story of building Eva, a personal AI assistant that lives where my conversations already happen.

  11. 13 avr.

    Fine-Tuning a Small LLM for Customer Support Pt. 1

    A hands-on guide to generating synthetic training data from FAQs, fine-tuning Qwen3-4B with LoRA on Apple Silicon, and serving the model locally with llama.cpp

  12. 1 avr.

    Are We Building the Perfect Finance Infrastructure for Machines?

    After a week at EthCC Cannes 2026, a provocation: Web3's complex, unreadable interfaces aren't a UX failure, they're a feature.

  • 12 épisodes

À propos

AI podcast for the teams and leaders building with it. We share real use cases, experiments, and insights on how to apply AI to your business. Made by the team at LayerX.

Informations

  • Création
    LayerX
  • Années d’activité
    2 k
  • Épisodes
    12
  • Classification
    Tous publics
  • Site web de l’émission
    LayerX