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AI43 · Open models

Open Source & Self-Host

Build a private AI stack on open models — and run it on infrastructure you control.

Duration
4 weeks · 12 build sessions
Format
Telegram POD · self-host lab
Pace
Three build sessions per week
Waiting list

01 · What you’ll learn

What you’ll learn

  1. 01

    Decide what runs locally, in a private environment, or with an external provider.

  2. 02

    Choose open models for dialogue, extraction, coding, retrieval, and multimodal work.

  3. 03

    Deploy an inference gateway, route tasks between models, and cut cost with caching.

  4. 04

    Evaluate quality, safety, speed, and cost — and keep human control.

03 · How we learn

How we learn

Start with one real workload. Each build session improves a concrete layer of your stack, while the POD reviews architecture and trade-offs.

03 · Who it’s for

Who it’s for

  • Teams and independent builders with sensitive or recurring AI workloads
  • Product, operations, and IT practitioners who need control over data and tooling
  • Advanced learners ready to run and evaluate their own models

06 · AI43 POD

Learner perspectives

I stopped asking AI for answers and started building criteria for better decisions.
Product lead
The POD made the difference: seeing how others approached the same quest exposed my blind spots.
Independent consultant
Short quests fit around work, but the method stayed with me after the course.
Operations manager

AI43 · Telegram POD

Run an AI stack you control.

Join the waiting list and we’ll share dates when the first Open Source & Self-Host POD is ready.

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