{"product_id":"context-engineering-with-dspy-self-optimizing-prompt-pipelines-for-building-reliable-ai-agents","title":"Context Engineering with DSPy: Self-Optimizing Prompt Pipelines for Building Reliable AI Agents","description":"\u003cp\u003e\u003cspan\u003eAI agents need the right context at the right time to do a good job. Too much input increases cost and harms accuracy, while too little causes instability and hallucinations. \u003c\/span\u003e\u003cspan class=\"a-text-italic\"\u003eContext Engineering with DSPy\u003c\/span\u003e\u003cspan\u003e introduces a practical, evaluation-driven way to design AI systems that remain reliable, predictable, and easy to maintain as they grow.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eAI engineer and educator Mike Taylor explains DSPy in a clear, approachable style, showing how its modular structure, portable programs, and built-in optimizers help teams move beyond guesswork. Through real examples and step-by-step guidance, you'll learn how DSPy's signatures, modules, datasets, and metrics work together to solve context engineering problems that evolve as models change and workloads scale.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eThis book supports AI engineers, data scientists, machine learning practitioners, and software developers building AI agents, retrieval-augmented generation (RAG) systems, and multistep reasoning workflows that hold up in production.\u003c\/span\u003e\u003c\/p\u003e\n\u003cul class=\"a-unordered-list a-vertical\"\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eUnderstand the core ideas behind context engineering and why they matter\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eStructure LLM pipelines with DSPy's maintainable, reusable components\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eApply evaluation-driven optimizers like GEPA and MIPROv2 for measurable improvements\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eCreate reproducible RAG and agentic workflows with clear metrics\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eDevelop AI systems that stay robust across providers, model updates, and real-world constraints\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch3\u003e\u003cspan\u003eAbout the Author\u003c\/span\u003e\u003c\/h3\u003e\n\u003cdiv class=\"a-section a-spacing-small a-padding-small\"\u003e\n\u003cdiv id=\"refreshable_btf_reverse_interleave_34\" class=\"celwidget\" data-feature-name=\"refreshable_btf_reverse_interleave_34\" 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_about-the-author-card_carouselItemStyles_expander__3Fm-M\" data-a-card-type=\"basic\" name=\"a-cardui-deck-autoname-0-card0\"\u003e\n\u003cdiv class=\"a-cardui-body\"\u003e\n\u003cdiv class=\"a-reactive-container a-reactive-container-transition\"\u003e\n\u003cdiv class=\"a-cardui-content a-cardui-uninitialized _about-the-author-card_carouselItemStyles_peekableContent__hWM3i\" data-a-max-height=\"80\"\u003e\n\u003cdiv id=\"editorialReviews_feature_div\" class=\"celwidget\" data-feature-name=\"editorialReviews\" data-csa-c-type=\"widget\" data-csa-c-content-id=\"editorialReviews\" data-csa-c-slot-id=\"editorialReviews_feature_div\" data-csa-c-asin=\"\" data-csa-c-is-in-initial-active-row=\"false\" data-csa-c-id=\"sr2tb4-4v2e56-xn6wd2-2lz7dz\" data-cel-widget=\"editorialReviews_feature_div\"\u003e\n\u003cdiv class=\"a-section a-spacing-small a-padding-base\"\u003e\n\u003cdiv class=\"a-section a-spacing-small a-padding-small\"\u003e\n\u003cdiv id=\"author-subheader-B0CYLSYPXX\" class=\"a-row stores-row stores-widget-atf\"\u003e\n\u003cdiv data-csa-c-content-id=\"widget:author-subheader-B0CYLSYPXX\" data-csa-c-painter=\"AmazonStoresAuthorSubHeader\" data-csa-c-slot-id=\"author-subheader-B0CYLSYPXX\" data-csa-c-type=\"widget\" data-csa-op-log-render=\"\" data-widgetid=\"author-subheader-B0CYLSYPXX\" data-widgettype=\"AuthorSubHeader\" class=\"a-column a-span12 stores-column\" data-csa-c-id=\"qhnoam-l55p47-fy7cu7-bpvbya\"\u003e\n\u003cdiv id=\"AuthorSubHeader-author-subheader-B0CYLSYPXX\"\u003e\n\u003cdiv data-testid=\"observer\"\u003e\n\u003cdiv class=\"AuthorSubHeader__author-subheader__FGJjD\"\u003e\n\u003ch4 class=\"AuthorSubHeader__author-subheader__name__HkJyX\"\u003eMike Taylor\u003c\/h4\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv id=\"author-cards-author-stores-home-top-author-stores-home-banner-container-B0CYLSYPXX\" class=\"a-row stores-row stores-widget-atf\"\u003e\n\u003cdiv 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pd_rd_r-e9f9637b-be79-496d-b98b-6ac1a59f627d c-f\" data-csa-op-log-render=\"\" data-csa-c-content-id=\"amzn1.sym.19c78dee-0e9f-4438-9c9c-d4065952d9ca\" data-csa-c-slot-id=\"author-stores-home-banner-container-1\" data-csa-c-type=\"widget\" data-csa-c-painter=\"content-grid-card-cards\" data-csa-c-id=\"e71wp1-u339ar-hy1rpb-66a8w2\" data-cel-widget=\"content-grid-card_author-stores-home-top_0\"\u003e\n\u003cdiv class=\"_Y29ud_acsUxWidgetDesktop_veWWI\" id=\"CardInstanceTHYctC5IbGeYbx3otJXdQQ\" data-card-metrics-id=\"content-grid-card_author-stores-home-top_0\" data-mix-claimed=\"true\"\u003e\n\u003cdiv class=\"_Y29ud_cctcg_2Y2xs celwidget US _Y29ud_bxwContentGrid_1NA_h _Y29ud_bxwContentGridEmber_1AoXs _Y29ud_bxcGridPadding_2eHHL _Y29ud_bxcGridn-bottom-layout_2xG7v _Y29ud_bxcGridlsFontLayout_2HpbT\" data-is-mobile=\"false\" data-csa-c-id=\"kttp6z-kx0hq-ahn4rf-53ktwu\" data-cel-widget=\"\"\u003e\n\u003cdiv class=\"_Y29ud_bxcGridContainer_2u9rb _Y29ud_bxcGridContainerWidth1500_36D4w _Y29ud_bxcGridmpGutterLayout_2hYHk\"\u003e\n\u003cdiv class=\"_Y29ud_bxcGridRow_Zu5i8\"\u003e\n\u003cdiv class=\"_Y29ud_bxcGridColumn_J5gfU _Y29ud_bxcGridColumn12Of12_1hOQf\" id=\"grid-row-0-col-0\"\u003e\n\u003cdiv class=\"celWidget _Y29ud_bxcGridContent_3IC_p\" data-cel-widget=\"acsux-widgets_content-grid_row1-col1\"\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cspan\u003ehas been working with AI since the GPT-3 beta in 2020, and over 500,000 people have taken his AI engineering courses. He coauthored the best-selling O'Reilly book Prompt Engineering for Generative AI. His work focuses on evaluating and optimizing AI workflows.\u003c\/span\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv id=\"detailBullets_feature_div\" class=\"celwidget\" data-feature-name=\"detailBullets\" data-csa-c-type=\"widget\" data-csa-c-content-id=\"detailBullets\" data-csa-c-slot-id=\"detailBullets_feature_div\" data-csa-c-asin=\"\" data-csa-c-is-in-initial-active-row=\"false\" data-csa-c-id=\"t349r2-bb2r8t-8bxoey-jtikc7\" data-cel-widget=\"detailBullets_feature_div\"\u003e\n\u003cdiv id=\"detailBulletsWrapper_feature_div\" data-feature-name=\"detailBullets\" data-template-name=\"detailBullets\" class=\"a-section feature detail-bullets-wrapper bucket\" data-cel-widget=\"detailBulletsWrapper_feature_div\"\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv id=\"buffetServiceCard_feature_div\" class=\"celwidget\" data-feature-name=\"buffetServiceCard_Books\" data-csa-c-type=\"widget\" data-csa-c-content-id=\"buffetServiceCard_Books\" data-csa-c-slot-id=\"buffetServiceCard_feature_div\" data-csa-c-asin=\"\" data-csa-c-is-in-initial-active-row=\"false\" data-csa-c-id=\"jfq7r0-xs9jvg-57e5or-23tzqc\" data-cel-widget=\"buffetServiceCard_feature_div\"\u003e\n\u003cdiv class=\"celwidget c-f\" data-csa-op-log-render=\"\" data-csa-c-content-id=\"DsUnknown\" data-csa-c-slot-id=\"DsUnknown-7\" data-csa-c-type=\"widget\" data-csa-c-painter=\"buffet-disclaimers-card-cards\" data-csa-c-id=\"p5n8f9-aezsar-b34lrv-40giwp\" data-cel-widget=\"buffet-disclaimers-card_DetailPage_6\"\u003e\n\u003cdiv id=\"CardInstancerMVdbLEqitA0CXT3OZ3Vjg\" data-card-metrics-id=\"buffet-disclaimers-card_DetailPage_6\" data-acp-tracking=\"{}\" data-mix-claimed=\"true\"\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e","brand":"Shroff\/O'Reilly","offers":[{"title":"Default Title","offer_id":50915736846406,"sku":"9789368082613","price":1800.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0754\/2797\/1142\/files\/9789368082613.png?v=1793692090","url":"https:\/\/cb-india.com\/products\/context-engineering-with-dspy-self-optimizing-prompt-pipelines-for-building-reliable-ai-agents","provider":"Computer Bookshop (India) Pvt Ltd","version":"1.0","type":"link"}