model training

4 articles · 15 co-occurring · 0 contradictions · 11 briefs

every CEO / exec should train a SOUL.MD" — Article demonstrates training a personalized leader model (SOUL.MD) on executive voice/preferences as a concrete fine-tuning use case

Related concepts

state machine patterns 2 observability as context 2 workflow automation 1 tool integration patterns 1 system prompt management 1 state management 1 reproducibility 1 output validation refinement 1 multi turn conversation management 1 multi agent orchestration 1 model training strategy 1 mid training optimization 1 memory persistence across sessions 1 memory persistence 1 decision support systems 1

Signal history

2026-W15

2026-W14

Evidence chain (4 articles, showing 4)

@aaronjmars: every CEO / exec should train a SOUL.MD, then let employees use it for intern... example_of

every CEO / exec should train a SOUL.MD" — Article demonstrates training a personalized leader model (SOUL.MD) on executive voice/preferences as a concrete fine-tuning use case

@Letta_AI: At Letta, our mission is to build machines that learn: AI that actually build... extends

Rather than updating model weights, Letta agents learn by actively managing their own context" — Proposes alternative learning paradigm for agents: in-context learning through active context managemen

@PrimeIntellect: pi-agent-rl-toolkit by @Indelwin, for Pi by @badlogicgames example_of

[QUOTED] "create a training loop that tested tool-calling ability" — Concrete example of constructing a custom training loop within the pi-agent framework for capability assessment.

[AINews] Context Drought extends

[inferred] "New research explores alternatives to fine-tuning and improving reproducibility, with open datasets supporting diverse languages and AI development" — Indicates shift in research toward al

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