Prompt Engineering in Software Systems
- Why
prompts are application logic
- Prompting
vs traditional programming
- Common
prompt failure modes
- Reliability
challenges in production
LLM API Prompting Fundamentals
- System,
user, and developer messages
- Instruction
hierarchy
- Context
window management
- Token
and prompt size considerations
Designing Clear & Deterministic Prompts
- Task,
context, and constraints pattern
- Explicit
output format control
- Tone
and style constraints
- Reducing
ambiguity
Few-Shot & Example-Based Prompting
- When
and how to use examples
- Designing
high-quality examples
- Avoiding
example bias
- Scaling
few-shot templates
Structured Outputs & Schema Enforcement
- JSON
and schema prompts
- Output
validation strategies
- Handling
malformed outputs
- Retrying
and repair patterns
Prompt Chaining & Multi-Step Workflows
- Breaking
tasks into steps
- Passing
context between prompts
- Conditional
logic
- Workflow
orchestration patterns
Reducing Hallucinations & Errors
- Grounding
with data
- Asking
for uncertainty flags
- Verification
and cross-check prompts
- Fallback
strategies
Prompt Testing & Evaluation
- Unit
testing prompts
- Prompt
regression testing
- Quality
metrics and evaluation sets
- A/B
testing prompts
Prompt Versioning & Lifecycle Management
- Storing
and managing prompt versions
- Change
control and approvals
- Rollback
strategies
- Documentation
and audit trails
Prompt Security & Safety
- Prompt
injection risks
- Input
sanitization
- Output
filtering
- Guardrails
and policy prompts
Performance & Cost Optimization
- Token
minimization
- Prompt
compression strategies
- Caching
and reuse
- Latency
optimization
Prompting for Common Developer Tasks
- Extraction
and classification prompts
- Summarization
and transformation
- Code
explanation and generation (support)
- Data
cleaning and normalization
Prompting with Tools & Functions
- Function
calling and tool use prompts
- Designing
tool schemas
- Tool
selection strategies
- Handling
tool errors
Prompting for RAG & Knowledge Systems
- Prompting
with retrieved context
- Citation
and grounding prompts
- Chunking
and context assembly
- Reducing
retrieval noise
Production Best Practices
- Observability
for prompts
- Monitoring
output quality
- Drift
detection
- Continuous
improvement
Hands-on Exercises
Summary and Conclusion
