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Description
Feature Request (from @sivan)
Add intelligent model recommendation based on session analysis to optimize token usage and LLM costs.
Requested behavior:
Clawatch should:
- Analyze recent sessions and their patterns
- Identify opportunities where a cheaper/smaller model could handle the workload
- Suggest specific model alternatives that would reduce costs without impacting quality
- Show potential savings estimate
Example use cases:
- Simple queries that don't need GPT-4 → suggest GPT-3.5-turbo
- Repetitive tasks → suggest cheaper models
- Sessions with low complexity → recommend cost-effective alternatives
Value:
- Help users optimize their LLM spending automatically
- Provide actionable insights on model selection
- Reduce operational costs without manual analysis
Context:
Requested by Sivan during internal testing feedback session.
Related Slack thread:
https://genwayhq.slack.com/archives/C0AFHCR4933/p1773248511101549
Auto-filed by Dor (PM) on behalf of team feedback
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