book

Context Engineering with DSPy

Name: Context Engineering with DSPy
Author: Mike Taylor
ISBN: 9798341671263

by Mike Taylor

December 2026

Intermediate to advanced

300 pages

4h 49m

English

O'Reilly Media, Inc.

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Brief Table of Contents (Not Yet Final)
1. Introduction to Context Engineering
Defining Context EngineeringContext Engineering vs Prompt EngineeringIntroducing DSPyFailure Modes for Long ContextsContext OverflowToken CostsContext DistractionLost in the MiddlePrompt InjectionContext ConfusionContext FragmentationContext ClashContext DriftContext PoisoningContext Engineering TechniquesContext EditingContext SummarizationMemory OffloadingPrompt OptimizationFewShot LearningRetrieval Augmented Generation (RAG)Tool LoadoutGuardrailsControl FlowMulti-Agent SystemsConclusion
2. Introduction to DSPy
Language ModelsSetting up OpenAIChanging LM ProviderSignaturesDefining a SignatureGet Over the UnfamiliarityModulesPredict ModuleBuilt-In ModulesReAct AgentsEvaluationExample DatasetsEvaluation MetricsRunning EvaluationsTrain-Test SplitOptimizersRunning an OptimizerGEPA Prompt OptimizerConclusion
3. DSPy in 8 Steps
3.1 Specify your Signatures3.1.1 HumanizeAIText3.1.2 DetectAIText3.2 Build your Modules3.2.1 TextTransformer3.2.2 AIDetector3.3 Explore a few Examples3.3.1 Run your Program3.3.2 Inspect History3.3.3 MLFlow Traces3.4 Collect your Dataset3.4.1 Example Dataset3.4.1 Load from CSV3.4.1 Convert to DSPy Example format3.4.1 Train-Test Split3.5 Define your Metrics3.5.1 Exact Match3.5.2 LLM Judge3.5.2 Testing your Metric3.6 Establish a Baseline3.6.1 Evaluate your Judge3.6.2 Evaluate your Task3.7 Optimize your Program3.7.1 Distilling from a Smarter model3.7.2 Running the GEPA Optimizer3.7.3 LLM Judge Metric3.7.4 Optimizing your Task Program3.7.5 Evaluating your Optimized Program3.8 Test and Iterate3.8.1 BestOfN ModuleConclusion
4. Strategies for Collecting Datasets
4.1 Error Analysis4.1.1 Manually Review and Annotate Data4.1.2 Categorize Errors4.1.3 Define a Dataset4.2 Domain Experts4.2.1 Qualitative Interview4.2.2 Example Correction4.2.3 Gold-Standard or Fool’s Gold?4.3 Third-Party Datasets4.3.1 Built-in DSPy Datasets4.3.2 HuggingFace Datasets4.3.3 Kaggle Datasets4.4 Synthetic Bootstrapping4.4.1 Model Distillation4.4.2 Data Enrichment4.4.3 Differential PrivacyConclusion
5. Formalizing Evaluation Metrics
5.1 String Comparison5.1.1 Passage Match5.1.2 Regex Match5.1.3 Edit Distance5.2 Semantic Similarity5.2.1 Embedder5.2.2 Embedding Distance5.2.3 NLP Classifiers5.3 LLM-as-a-Judge5.3.1 Human-in-the-Loop5.3.2 Training a classifier5.3.3 Evaluator-Optimizer pattern5.4 Panel of Judges5.4.1 Criteria Rubrics5.4.2 Weighted Scoring5.4.3 Multi-predictor FeedbackConclusion
6. Deep Dive into Prompt Optimizers
6.1 Automatic Few-Shot Learning6.1.1 LabeledFewShot6.1.2 BootstrapFewShot6.1.3 BootstrapFewShotWithRandomSearch (BootstrapRS)6.1.4 KNNFewShot6.1.5 BootstrapFewShotWithOptuna6.2 Automatic Instruction Optimization6.2.1 COPRO6.2.2 MIPROv26.2.3 GEPA6.2.4 SIMBA6.2.5 InferRules6.2.6 AvatarOptimizer6.3 Automatic Finetuning6.3.1 BootstrapFinetune6.3.2 BetterTogether6.3.3 GRPO6.4 Program Transformations6.4.1 Ensemble6.5 Choosing the Right OptimizerConclusion
7. Customizing DSPy Programs
7.1 Built-In Modules7.1.1 Predict7.1.2 ChainOfThought7.1.3 MultiChainComparison7.1.4 BestOfN7.1.5 Refine7.1.6 ReAct7.1.7 ProgramOfThought7.1.8 CodeAct7.1.9 RLM (Recursive language models)7.1.10 Building multi-stage modulesBuilt-in module summary7.2 Other Components7.2.1 majority7.1.8 Parallel7.3 Multimodal Types7.3.1 Images7.3.2 Audio7.3.3 Subclassing BaseType for videos7.3.4 Documents with the Attachments library7.4 Chat Adapters7.4.1 ChatAdapter7.4.2 JSONAdapter7.4.3 XMLAdapter7.4.4 TwoStepAdapter7.4.5 Building custom adaptersConclusion
About the Author

Content preview from Context Engineering with DSPy

About the Author

Mike Taylor has been working with AI since the GPT-3 beta in 2020, and over 250,000 people have taken his AI engineering courses on Udemy. He coauthored the best-selling O’Reilly book Prompt Engineering for Generative AI, and he is the cofounder and CEO of AskRally, generating AI personas to simulate market feedback.

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Context Engineering for Multi-Agent Systems

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Context Engineering with DSPy

by Mike Taylor

About the Author

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.