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Inside Language Models
How can we connect a readable account of a model’s state to the work it actually does?
- Intermediate states
- Causal use
- Readable explanations
Reasoning Budgets
When should a system keep its answer, think again or seek new information?
- Stop or refine
- Selective effort
- The next useful action
Financial Agents
What makes an agent’s financial output worth relying on?
- Market views
- TradingAgents
- Signal validation
Context Compaction
What must survive when an agent can no longer carry its whole history?
- Preserving the task
- Recovering detail
- Checkpoint implementations
Decision Models
How can a model judge a question it has never been trained to name?
- Jev’s interface
- Alternative methods
- Training and calibration
Models and Agent Systems
When should better agent performance come from the model, the system or its experience?
- Model and harness
- Repair and completion
- Learning from experience
Knowledge and Memory
Which knowledge should influence an AI system’s next answer?
- Knowledge placement
- Source conflicts
- Memory over time
LLMs in Finance
Where can language add value to a financial system?
- Semantic value
- Signal fusion
- Production controls