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TCG Case Study Template
Use after a beta user agrees to be referenced (anonymized or named). Keeps ROI claims defensible for marketing and investors.
File naming: artifacts/case-studies/YYYY-MM-<slug>.md
Metadata
| Field | Value |
|---|---|
| Customer (public name) | |
| Segment | indie / YC startup / SMB product team |
| Stack | LangChain / AutoGen / custom / other |
| Agent topology | # agents, avg steps per task |
| TCG plan | Free / Pro |
| Period analyzed | YYYY-MM-DD → YYYY-MM-DD |
| Author |
1. Baseline (before TCG)
- Monthly LLM spend (USD):
- Primary models:
- Main workload: e.g. coding agent, support bot, RAG pipeline
- Pain: e.g. bill spike, no attribution, unknown cache usage
- Tools used before TCG: LangSmith / none / spreadsheet / other
2. Integration
- Endpoint:
POST /api/v1/optimize(+ feedback if used) - Frequency: per trace / nightly batch / other
- Data sent: full logs / truncated / PII redacted by customer
- Applied recommendations? yes / partial / no (critical for honesty)
| Intervention | Applied? | How |
|---|---|---|
| Compression / HCA summary | ||
| Routing tier change | ||
| Prompt structure / cache blocks (v1) | ||
| HERMES / policy |
3. Metrics (quantitative)
| Metric | Before | After | Δ | Source |
|---|---|---|---|---|
| Est. monthly tokens (input) | TCG / provider bill | |||
| Est. monthly cost (USD) | ||||
| Avg tokens per successful task | ||||
| % calls on premium model | ||||
| Cached input tokens (if provider reports) | ||||
| p95 latency (optional) |
TCG-reported fields (from API):
_guard.baseline/_guard.saved(note: may be estimated from logs, not provider invoice)_vmm.saving_ratioif compression applied_routing.targetTierif used
Claimed savings %: ___%
Method: (baseline_cost - after_cost) / baseline from TCG or invoice comparison — state which.
4. Qualitative
- What surprised the team?
- What they would not give up (quality guardrails)?
- Would they pay $12/mo? Why / why not?
5. Limitations (required)
- Savings include model routing, not only prompt optimization
- Sample size: N traces / M days
- Seasonality or product change during period
- TCG did not proxy LLM traffic (beta)
6. Publishable quote (optional)
“…” — Role, Company
7. Internal only
tenant_id/ trace ids (do not publish)- Support issues / blockers for product