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AI Prompt Engineering for B2B SalesPremium

Master structured extraction, grounding, and personalization. Build LLM pipelines that never hallucinate. 9 modules, 19 lessons, 5+ hours of reading.

The curriculum

9 modules · 19 lessons · 302 minutes of reading

Video Lessons Coming Soon: We are producing video walkthroughs for this course. Stay tuned!
Module 1

Prompting 101 (The Basics)

How LLMs predict tokens, the anatomy of a prompt, and why models hallucinate.

20 min

Outcome: You understand the underlying mechanics of AI, ensuring you never write a 'hopeful' chatbot prompt for a production system again.

  1. 1.1Token Prediction vs Knowledge RetrievalLLMs don't 'know' facts. They guess the next token.8 min
  2. 1.2The Anatomy of a Production PromptRole, Context, Task, Constraints, and Format.12 min
Module 2

Structured Outputs & Self-Healing

OpenAI Structured Outputs, JSON schemas, catching parse errors.

43 min

Outcome: You guarantee the AI returns mathematically perfect JSON every single time, preventing downstream workflow crashes.

  1. 2.1The 'Return JSON' ProblemWhy `prompt + 'return JSON'` crashes your app.10 min
  2. 2.2OpenAI Structured Outputs (Strict Mode)Mathematically perfect JSON.18 min
  3. 2.3Building a Self-Healing LoopWhat happens when Anthropic/Claude fails?15 min
Module 3

Tone Matching & Personalization at Scale

Banning 'AI speak', negative constraints, few-shot prompting.

28 min

Outcome: You generate outbound emails that pass the 'human smell test', doubling reply rates compared to generic AI copy.

  1. 3.1Killing the 'AI Smell'Why your outbound emails are getting ignored.12 min
  2. 3.2Few-Shot Prompting (Show, Don't Tell)The most powerful technique for tone matching.16 min
Module 4

Context Window Engineering

Hierarchical XML tagging, RAG basics, pre-filling assistant responses.

26 min

Outcome: You can feed an LLM 100 pages of a company's documentation and extract the exact pain points without the model losing focus.

  1. 4.1Hierarchical XML TaggingHow to manage massive context windows.14 min
  2. 4.2Prefilling Assistant ResponsesForcing the model into a specific state.12 min
Module 5

Cost & Latency Engineering

Model routing (Haiku vs Sonnet vs Opus), prompt caching, batching.

27 min

Outcome: You drop your AI enrichment costs by 80% while maintaining the exact same data quality and pipeline output.

  1. 5.1Model Routing & Cost MathDon't use a sledgehammer to crack a nut.12 min
  2. 5.2Prompt Caching StrategiesSaving 90% on API costs by not repeating yourself.15 min
Module 6

Automated Evaluation (Evals)

Building an eval pipeline, rubric engineering, LLM-as-a-Judge.

38 min

Outcome: You stop guessing if a prompt is better and start proving it with hard data across hundreds of edge cases before shipping.

  1. 6.1Writing an Eval RubricIf you can't measure it, you can't improve it.20 min
  2. 6.2LLM-as-a-Judge ArchitectureGPT-4 grading Claude.18 min
Module 7

Fine-Tuning vs Prompting

When prompting hits a ceiling, formatting training data.

30 min

Outcome: You know exactly when to invest in a fine-tuned model to solve edge cases that raw prompting can never fix.

  1. 7.1The Fine-Tuning Decision MatrixWhen prompting hits a ceiling.14 min
  2. 7.2Formatting Training DataThe JSONL structure for OpenAI.16 min
Module 8

Agentic Workflows for GTM

Function calling, building a multi-step research agent.

45 min

Outcome: You deploy autonomous agents that do the work of a junior SDR, researching and qualifying accounts while you sleep.

  1. 8.1Function Calling (Giving LLMs Hands)How an LLM interacts with the real world.25 min
  2. 8.2Building a Multi-Step Research AgentChaining tools together.20 min
Module 9

Capstone - Cold Email Personalization Engine

Build a stripped-down version of an engine that researches, scores, and drafts.

45 min

Outcome: You possess a production-ready, highly valuable GTM asset you can deploy internally or sell to clients as a service.

  1. 9.1Capstone: Engine ArchitectureWiring the pipeline together.20 min
  2. 9.2Capstone: The Final Code PipelineExecuting the plan.25 min