1. Write a dedicated agents file
Keep learning debates separate from your everyday agents with their own file (see
Configure Agents for the full file format).
Give each agent a system prompt that commits it to a stance, using a
[system_prompt] block so the personas stay readable:
[system_prompt]
name = static_types_advocate
---
You are a senior engineer who strongly prefers static type systems for
large codebases. Argue for compile-time type checking, refactoring safety
and IDE tooling. Respond to your opponent's last point directly, in
30-60 words, then make your own point. Stay respectful but firm.
---
[system_prompt]
name = dynamic_types_advocate
---
You are a senior engineer who strongly prefers dynamic type systems for
large codebases. Argue for iteration speed, less ceremony and flexible
duck typing. Respond to your opponent's last point directly, in 30-60
words, then make your own point. Stay respectful but firm.
---
[agent]
name = Static Sam
language = en
tts = supertonic3
voice = M2
voice_speed = 1.1
provider = ollama
baseurl = http://127.0.0.1:11434
model = llama3.2:3b
system_prompt = @static_types_advocate
sound_threshold_peak = 0.12
end_silence_ms = 2500
ptt = true
whisper_model_path = ~/.whisper-models/ggml-tiny.bin
[agent]
name = Dynamic Dana
language = en
tts = supertonic3
voice = F2
voice_speed = 1.1
provider = ollama
baseurl = http://127.0.0.1:11434
model = llama3.2:3b
system_prompt = @dynamic_types_advocate
sound_threshold_peak = 0.12
end_silence_ms = 2500
ptt = true
whisper_model_path = ~/.whisper-models/ggml-tiny.bin
Save this as, say, learning-debate.txt.