Learn how to make multiple specialized AI agents work in parallel, handling front-end, back-end, and code reviews simultaneously, without overwhelming your context window. We’ll walk through manual .toml configurations, using the Codex Agents Library, and running parallel prompts directly in the terminal.
Watch the full video on YouTube: https://youtu.be/xItvCoWNPVo?si=igDiJVWWBmYtVrHXhttps://youtu.be/xItvCoWNPVo?si=igDiJVWWBmYtVrHX (https://youtu.be/xItvCoWNPVo?si=igDiJVWWBmYtVrHX)
25 Jan 2026
Claude Code + Ollama Explained in 4 Minutes
Did you know the new Claude Code CLI tool doesn't have to run on Anthropic's servers?
In my latest video, I show you a "hack" to redirect Claude Code to use your local Ollama server. This means you can use open-source models (like Llama 3, Qwen, or GPT-OSS) directly in your terminal for free.
Why do this?
Privacy: Your proprietary code never leaves your local network.
Cost: Zero API fees.
The Catch? I put it to the test on a machine with 32GB RAM and 8GB VRAM. While it works, the speed difference compared to the cloud is massive.
Check out the full tutorial and performance test to see if your rig can handle it!
Watch on YouTube: https://youtu.be/COpg79ab6ug (https://youtu.be/COpg79ab6ug)
Read the full tutorial: https://proflead.dev/posts/claude-code-with-ollama-tutorial/ (https://proflead.dev/posts/claude-code-with-ollama-tutorial/)
11 Jan 2026
How to use Ollama (2026 Tutorial)
Learn how to use Ollama in 2026! This complete ollama tutorial covers everything you need to run large language models (LLMs) locally on Linux, Mac, and Windows. We dive into the CLI, new Cloud features, and how to use local ollama Python scripts to integrate AI into your own projects.In this video, we explore the power of ollama to run open-source models like Gemma and Mistral without paying for cloud API fees. You will learn how to download models, manage them via the command line, create custom model files, and set up a local server. Key Topics Covered:
Installing Ollama on any operating system.
Running your first LLM locally (Gemma, Llama, etc.).
Using Ollama Cloud to offload heavy models (like 100B+ params).
Writing Python scripts to interact with your local models.
Creating custom "Modelfiles" for personalized AI behavior.
Watch on YouTube: https://youtu.be/AGAETsxjg0o?si=h7_IB4vRqT6shmo0 (https://youtu.be/AGAETsxjg0o?si=h7_IB4vRqT6shmo0)
The full tutorial: https://proflead.dev/posts/ollama-tut... (https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbkVlemRRSENSNWpxRHpFdVBvb1JGaFhaTkxkd3xBQ3Jtc0trQUhyZWpjcDNtRkUxSk9kQmY2MUZvZFZZSUZrQmRxNVBSeEE0cW1UWGdBMGRXVTRnY3gybmh2WlctTXNiOF9LYXZZc1RONHdxdmxIbi1aZVFiRnhZWmVHbWl1N0Fid1RKcU5lSlUwRWM1Q2lmZW9CTQ&q=https%3A%2F%2Fproflead.dev%2Fposts%2Follama-tutorial%2F&v=AGAETsxjg0o)Download Ollama: https://ollama.com (https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqa0djMWlkZndoWk1QcG94VV9wQVEzVVpjVk1rZ3xBQ3Jtc0trUTM5U0YwUWJ5YTVlU1NIQ1QtTHhOSUphZzZDSWdiRUxjR1FGSExhaDdhNHNQc200VEdFYTRMa3ZMc3JETDhXT0VlUENPZnRtOERMNVJaTjRrbDhVczhCaHMtUTEtdnF6X1ZOaEoxcVNWcHI4ZFhNOA&q=https%3A%2F%2Follama.com%2F&v=AGAETsxjg0o)Ollama Library: https://ollama.com/library (https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbmtpUkNSUlp2b3ZfMXJRWHJydk0tMzdKUzd4Z3xBQ3Jtc0tuUFVkRG1NdDNKQXU5TlgtYkVvTGNkeGkyYzNDZTlNWHY4UTV0UG83Sk5fYnJCa0I5dGFxQjcyR1NVTXJ5Z0RVb0p0WC1EMnBUQ2hIekl2VHk1Zkl3bzAtSDdVX2RkbUxZQk9FVkRoOExSY1REcGVDcw&q=https%3A%2F%2Follama.com%2Flibrary&v=AGAETsxjg0o)
Reach and audience
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YouTube views
472,707
Score snapshot 15 Sept 2025
Podcast Authority Score: 33 / 100
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Quality
31
Social presence
0
YouTube
86
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0
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