Identify tasks suited to LLM processing, design pipelines, and iterate with agent-assisted development.
Scanned 9/3/2026
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# Project Development Methodology
Identify tasks suited to LLM processing, design pipelines, and iterate with agent-assisted development.
## Prerequisites
- Understanding of LLM capabilities
- Familiarity with batch processing
## Instructions
### Task-Model Fit
**LLM-suited tasks**:
- Synthesis across sources
- Subjective judgment with rubrics
- Natural language output
- Error tolerance acceptable
- Batch processing (no conversational state)
**LLM-unsuited tasks**:
- Precise computation
- Real-time requirements
- Perfect accuracy required
- Sequential dependencies
- Deterministic output needed
### Manual Prototype First
Before building automation:
1. Copy one representative input into model
2. Evaluate output quality
3. Identify failure modes
4. Estimate tokens per item
If manual prototype fails, automated system will fail.
### Pipeline Architecture
```
acquire → prepare → process → parse → render
```
- **acquire**: Fetch raw data
- **prepare**: Transform to prompt format
- **process**: LLM calls (expensive, non-deterministic)
- **parse**: Extract structured data
- **render**: Generate final outputs
### File System as State Machine
```
data/{id}/
├── raw.json # acquire complete
├── prompt.md # prepare complete
├── response.md # process complete
├── parsed.json # parse complete
```
Check file existence to determine processing state.
### Architectural Reduction
Start minimal. Vercel's d0 agent: 17 tools → 2 tools (bash + SQL), 80% → 100% success rate.
**When reduction works**:
- Data layer is well-documented
- Model has sufficient reasoning
- Specialized tools were constraining
## Guidelines
1. Validate task-model fit with manual prototype
2. Structure pipelines as discrete, idempotent stages
3. Use file system for state management
4. Design prompts for parseable outputs
5. Start minimal; add complexity only when proven necessary
6. Estimate costs early and track throughout
## Notes
- Karpathy's HN Capsule: 930 items, $58 cost, 1 hour
- Expect multiple architectural iterations
- Test whether scaffolding helps or constrains model
Source: muratcankoylan/Agent-Skills-for-Context-Engineering
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