Tools for Everyday Software and AI Work

Tools from Cueset Labs: a prompt template advisor, a fine-tuning vs RAG advisor, LLM cost and cascade calculators, and a touch typing trainer for the IT sector.

Decision aids from the lab. Answer a few questions and walk away with something concrete: a prompt, a strategy, or a cost you can plan around.

Prompt Advisor

Turn a rough idea into a production-ready prompt template, annotated and ready to fill in. Answer a few questions about your task, format, and constraints, and it builds the scaffold for you.

Topics: prompting, templates, LLM, generation.

Strategy Advisor

Get an opinionated call on fine-tuning vs. RAG vs. prompt engineering for your situation, with a full implementation roadmap, not just a verdict. Four questions is all it takes.

Topics: fine-tuning, RAG, strategy, LLM ops.

Inference Cost Calculator

See what inference would actually cost each month before you commit to a model, ranked across models from Anthropic, OpenAI, Google, Mistral, and more. Set your token counts and request volume; prices are fetched live.

Topics: cost, pricing, models, budgeting.

Model Router / Cascade Planner

Model a cascade: a cheap small model takes every request, and a share escalates to a frontier model. See the blended monthly cost against all-frontier and all-small, and the break-even escalation rate where the cascade stops paying off. Prices are fetched live.

Topics: routing, cascade, cost, SLM.

Touch Typing for the IT Sector

Find the keys that slow you down in the material your IT role types, from code and commands to user stories. A three-minute diagnostic builds a fault report and a 10-lesson plan to fix it, and Virtual Coach uses your webcam to catch wrong-finger habits. Runs in the browser, and your keystrokes stay on your device.

typing.cuesetlabs.io

Topics: typing, diagnostic, IT roles, webcam.

Approaches the Strategy Advisor can recommend

• RAG: Retrieval-Augmented Generation
• Long-Context Prompting: Inject the full knowledge base per call
• Knowledge Fine-Tuning: Internalize facts into weights for sub-100ms responses
• RAG + Fine-Tuning: The production combination for high-stakes systems
• Prompt Engineering, Format: Schema injection and few-shot examples
• Constraint-Based Prompting: Explicit length and style directives
• Fine-Tuning, Format: Near-100% structural compliance for automated pipelines
• Fine-Tuning, Style: Lock brand voice permanently into model weights
• Persona + Style Prompting: Describe the voice; show examples; iterate fast
• Chain-of-Thought Prompting: Structure the reasoning; no training required
• Supervised Fine-Tuning: Domain-specific behavioral alignment
• RAG + Chain-of-Thought: Retrieve context, then reason over it explicitly
• Preference Fine-Tuning (DPO): Systematic safety and policy alignment
• Fine-Tuning, Consistency: Narrow the output distribution for predictable behavior
• Defensive Prompt Engineering: Enumerate failure modes and specify fallback behavior
• Prompt Distillation: Bake a long prompt into fine-tuned weights
• RAG Pipeline Optimization: Fix retrieval before adding more model
• Fine-Tune a Smaller Model: Match frontier quality at 10–50× lower cost