{"id":60,"date":"2026-08-27T08:45:05","date_gmt":"2026-08-27T03:15:05","guid":{"rendered":"https:\/\/chandankar.com\/blog\/?p=60"},"modified":"2026-08-28T23:00:40","modified_gmt":"2026-08-28T17:30:40","slug":"technical-delivery-management-in-the-age-of-ai-section-5-ai-prompt-library-ready-to-use-pocket-reference-micro-ebook","status":"publish","type":"post","link":"https:\/\/chandankar.com\/blog\/general\/technical-delivery-management-in-the-age-of-ai-section-5-ai-prompt-library-ready-to-use-pocket-reference-micro-ebook\/","title":{"rendered":"Technical Delivery Management in the Age of AI &#8211; Section 5: AI Prompt Library, Ready to use Pocket Reference Micro-eBook"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<h3 class=\"wp-block-heading\">AI Delivery Is Moving Beyond Prompting &#8211; From generic AI assistance to role-specific delivery capability<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The biggest challenge with AI in IT delivery is no longer access to AI.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It is knowing <strong>where AI fits, what context it needs, what output should be produced, how that output should be validated, and where human judgment must remain accountable.<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A Technical Delivery Manager assessing a dependency escalation does not need the same AI interaction as a Business Analyst decomposing requirements.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A Cloud Architect evaluating a migration does not need the same approach as a Scrum Master analysing flow.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">And an AI Delivery Lead designing an AI-enabled workflow should not approach the problem like someone asking an AI assistant for a summary.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">That observation led me to create the <strong>AI Delivery Prompt Pocket Library<\/strong>\u2014a practitioner-focused micro-eBook designed to make AI more useful across the IT consulting and technology delivery lifecycle.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">What is the AI Delivery Prompt Pocket Library?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">This is <strong>not another introduction to Generative AI, LLMs, prompting, Agile, or AI agents<\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It is designed for practitioners who already understand their profession and need a practical answer to a different question:<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p class=\"wp-block-paragraph\"><strong>\u201cI have this delivery situation right now. How can I use AI effectively to move it forward?\u201d<\/strong><\/p>\n<\/blockquote>\n\n\n\n<p class=\"wp-block-paragraph\">The library brings together:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>206 copy-ready prompts \u00b7 19 practitioner roles \u00b7 6 delivery functions \u00b7 9 Agile methodology adapters<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">covering delivery leadership, Agile and Product, Business Analysis, Engineering, Architecture, Operations, Quality, Customer Engagement, and AI Delivery &amp; Architecture.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The prompts are designed around the operating sequence:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>ROLE \u2192 SITUATION \u2192 PROMPT \u2192 CONTEXT \u2192 RUN \u2192 VALIDATE \u2192 ACT<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The objective is not to generate more AI output.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>It is to improve the quality and speed of professional thinking, decisions and delivery outcomes.<\/strong><\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">Why Role-Based AI Matters<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">One of the recurring problems I see with generic prompting is that the prompt often ignores the <strong>professional responsibility of the person using it<\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A delivery leader thinks in terms of outcomes, risks, dependencies and governance.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A Product Owner thinks in terms of customer value, prioritization and product decisions.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">An Architect thinks in terms of alternatives, constraints, NFRs, integration and trade-offs.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A QA Lead thinks in terms of coverage, defects, risk and release confidence.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">An AI Delivery Lead has to think beyond the prompt itself\u2014toward <strong>model selection, retrieval, workflows, agents, governance, evaluation, adoption and measurable value<\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The library therefore organizes AI around <strong>real practitioner roles and situations<\/strong>, rather than treating every professional as simply an AI user.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">How I Designed the Library<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The prompts are intended to become part of the <strong>delivery workflow<\/strong>, not remain isolated chat interactions.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The basic usage is straightforward:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>1. Identify your role<\/strong><br>Find the practitioner section relevant to your responsibility.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>2. Identify the situation<\/strong><br>Start with the delivery problem or decision you are actually facing.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>3. Select the prompt<\/strong><br>Choose the prompt designed for that situation.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>4. Add context<\/strong><br>Provide the project, systems, evidence, constraints, thresholds, audience and other relevant information.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>5. Run and validate<\/strong><br>Do not blindly accept the output. Separate:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>FACT \u2192 INFERENCE \u2192 ASSUMPTION \u2192 RECOMMENDATION<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>6. Act<\/strong><br>Turn the validated output into a decision, escalation, action plan, requirement, design, governance artifact, communication\u2014or the next AI workflow.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">That final step is important.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>AI value is realized when output changes what happens next.<\/strong><\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">A Few Practical Examples<\/h3>\n\n\n\n<h4 class=\"wp-block-heading\">Technical Delivery Manager<\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">Instead of asking:<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p class=\"wp-block-paragraph\">\u201cSummarize my project status.\u201d<\/p>\n<\/blockquote>\n\n\n\n<p class=\"wp-block-paragraph\">A delivery leader can use AI to identify <strong>material exceptions, worsening trends, blocked dependencies and milestone threats<\/strong>, supported by evidence and with explicit handling of missing information.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The result moves from:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Status Summary \u2192 Delivery Intelligence \u2192 Decision \u2192 Action<\/strong><\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h4 class=\"wp-block-heading\">Business Analyst<\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">Instead of:<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p class=\"wp-block-paragraph\">\u201cCreate user stories from this requirement.\u201d<\/p>\n<\/blockquote>\n\n\n\n<p class=\"wp-block-paragraph\">AI can be used to distinguish confirmed business rules from inferred behaviour, identify ambiguity and contradictions, generate clarification questions, and structure the progression:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Requirement \u2192 Business Rules \u2192 User Stories \u2192 Acceptance Criteria \u2192 Test Scenarios<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This makes AI a <strong>requirements-engineering accelerator<\/strong>, rather than simply a documentation assistant.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h4 class=\"wp-block-heading\">Solution Architect<\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">Instead of asking:<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p class=\"wp-block-paragraph\">\u201cWhich architecture is better?\u201d<\/p>\n<\/blockquote>\n\n\n\n<p class=\"wp-block-paragraph\">The practitioner can ask AI to generate viable options and evaluate them against <strong>NFRs, cost, scalability, reliability, security, integration, operational complexity and delivery constraints<\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The resulting decision structure becomes:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Options \u2192 Evidence \u2192 Trade-offs \u2192 Risks \u2192 Recommendation \u2192 Decision<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">That is much closer to the way real architecture decisions are made.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h4 class=\"wp-block-heading\">Scrum Master \/ Agile Practitioner<\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">AI can also move Agile analysis beyond velocity reporting.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">For example, sprint data can be examined across <strong>commitment, completion, carry-over, blockers, scope change and quality signals<\/strong>, with evidence-backed causes and a specific improvement experiment.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The same underlying thinking can then be adapted across:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Scrum \u2192 Sprint<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>SAFe \u2192 PI \/ ART<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>XP \u2192 TDD \/ CI \/ Pairing \/ Refactoring<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Kanban \u2192 WIP \/ Cycle Time \/ Throughput \/ Aging<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This is why I included <strong>Agile methodology adapters<\/strong> rather than duplicating essentially the same prompt for every framework.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">From Prompting to AI Workforce Design<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">For me, this is where the concept becomes more interesting.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The prompt should not necessarily be the final destination.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A useful progression is:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Prompt \u2192 Prompt Chain \u2192 Workflow \u2192 Tool-enabled AI \u2192 Agent \u2192 Multi-Agent \u2192 Human + AI Operating Model<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Consider delivery-risk monitoring.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It could evolve from:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Delivery Data<\/strong><br>\u2193<br><strong>AI Triage<\/strong><br>\u2193<br><strong>Risk Analysis<\/strong><br>\u2193<br><strong>Dependency Investigation<\/strong><br>\u2193<br><strong>Decision Synthesis<\/strong><br>\u2193<br><strong>Human Approval<\/strong><br>\u2193<br><strong>Controlled Action<\/strong><br>\u2193<br><strong>Outcome Measurement<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The prompt becomes <strong>one component of a larger AI-enabled delivery architecture<\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This is also why the library includes an AI-native architecture perspective.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The question should not automatically be:<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p class=\"wp-block-paragraph\"><strong>\u201cWhich AI agent should we build?\u201d<\/strong><\/p>\n<\/blockquote>\n\n\n\n<p class=\"wp-block-paragraph\">It should first be:<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p class=\"wp-block-paragraph\"><strong>\u201cWhat is the simplest AI capability that can reliably achieve the required outcome?\u201d<\/strong><\/p>\n<\/blockquote>\n\n\n\n<p class=\"wp-block-paragraph\">Depending on the work, that could mean a fast model, reasoning model, retrieval, deterministic workflow, agent, multi-agent pattern\u2014or human-gated AI.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">Context Beats Clever Prompts<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">One of the strongest principles behind the library is that <strong>a sophisticated prompt cannot compensate for poor context<\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Instead of giving an AI system everything available and asking it to \u201cfind the risks,\u201d provide the relevant evidence:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Milestone data<\/li>\n\n\n\n<li>RAID<\/li>\n\n\n\n<li>Dependencies<\/li>\n\n\n\n<li>Delivery trends<\/li>\n\n\n\n<li>Historical risks<\/li>\n\n\n\n<li>Decision records<\/li>\n\n\n\n<li>Applicable constraints<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">Then ask it to reason over that evidence.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The principle is simple:<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p class=\"wp-block-paragraph\"><strong>Retrieve the right context\u2014not all the context.<\/strong><\/p>\n<\/blockquote>\n\n\n\n<p class=\"wp-block-paragraph\">This improves relevance while also helping manage cost, latency and decision quality.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">Prompt Quality Is Only One Part of the Equation<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">A production-oriented AI interaction should make five things clear:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>What outcome are we trying to achieve?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>What evidence does AI need?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>What rules should it apply?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>What exact output should it produce?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Where must a human validate or approve?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">That is why the library structures prompts around elements such as:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Context \u2192 Objective \u2192 Inputs \u2192 Constraints \u2192 Decision Rules \u2192 Sources \u2192 Output Contract \u2192 Validation \u2192 Escalation<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This turns prompting from an informal skill into a <strong>repeatable delivery practice<\/strong>.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">Who Is This For?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">I built the library for the broader technology delivery ecosystem:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Delivery &amp; Program Leadership<\/strong><br>TDM \u00b7 PM \u00b7 Program Manager \/ TPM \u00b7 PMO \/ Transformation Lead<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Agile &amp; Product<\/strong><br>Scrum Master \u00b7 Agile Practitioner \u00b7 Product Manager \/ Product Owner \u00b7 Business Analyst<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Engineering &amp; Architecture<\/strong><br>Technical Lead \u00b7 Solution Architect \u00b7 Cloud Architect \u00b7 Infrastructure Architect \u00b7 Enterprise Architect \u00b7 Security Architect \u00b7 Data Architect<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Operations &amp; Quality<\/strong><br>DevOps \/ SRE \/ Platform Engineer \u00b7 QA \/ Test Lead \u00b7 Service Delivery \/ IT Operations<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Customer &amp; Engagement<\/strong><br>Customer \/ Engagement \/ Presales<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>AI Delivery &amp; Architecture<\/strong><br>AI Product Manager \u00b7 AI Architect \u00b7 AI Delivery Lead<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The intent is to establish a <strong>common AI-assisted delivery language across roles<\/strong>, while respecting the different decisions, responsibilities and controls associated with each profession.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">The Bigger Idea<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The real value of this library is <strong>not 206 prompts<\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The prompts are the practical entry point.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The larger objective is to help professionals learn how to connect:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Role + Situation + Context + AI Capability + Workflow + Human Judgment + Business Outcome<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">That is the shift I believe organizations need to make.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Not:<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p class=\"wp-block-paragraph\"><strong>\u201cWhat can AI do?\u201d<\/strong><\/p>\n<\/blockquote>\n\n\n\n<p class=\"wp-block-paragraph\">But:<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p class=\"wp-block-paragraph\"><strong>\u201cWhat outcome am I responsible for, what decision drives it, and what part of that work can AI reliably accelerate?\u201d<\/strong><\/p>\n<\/blockquote>\n\n\n\n<p class=\"wp-block-paragraph\">From there, choose the appropriate:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Prompt \u2192 Model \u2192 Context \u2192 Workflow \u2192 Agent \u2192 Human Decision<\/strong><\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">My Pocket Principle<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The future of AI-enabled delivery will not belong simply to professionals who know how to use AI.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It will increasingly favor professionals who can <strong>design the interaction between AI capability, enterprise context, delivery workflows and human judgment<\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">That is the purpose behind the <strong>AI Delivery Prompt Pocket Library<\/strong>.<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p class=\"wp-block-paragraph\"><strong>Right Role. Right Situation. Right Prompt. Right Context. Right Decision. Right Outcome.<\/strong><\/p>\n<\/blockquote>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>AI-powered delivery is not about generating more.<br>It is about deciding better, executing faster and realizing more value.<\/strong><\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">&#x1f4d8; Get the AI Delivery Prompt Pocket Library<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">I\u2019m sharing the micro-eBook as a practical reference for delivery, Agile, engineering, architecture, operations, PMO and AI practitioners.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Download the book here: <\/strong><a href=\"https:\/\/chandankar.com\/blog\/download\/69\/?tmstv=1787938088\">AI Delivery Prompt Pocket Library PDF<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">#AI #GenerativeAI #AIDelivery #AITools #PromptEngineering #ProjectManagement #TechnicalDelivery #PMO #Agile #ProductManagement #Architecture #Engineering #AIOps #DigitalTransformation #AILeadership #FutureOfWork<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n","protected":false},"excerpt":{"rendered":"<p>AI Delivery Is Moving Beyond Prompting &#8211; From generic AI assistance to role-specific delivery capability The biggest challenge with AI in IT delivery is no longer access to AI. It is knowing where AI fits, what context it needs, what output should be produced, how that output should be validated, and where human judgment must [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-60","post","type-post","status-publish","format-standard","hentry","category-general"],"_links":{"self":[{"href":"https:\/\/chandankar.com\/blog\/wp-json\/wp\/v2\/posts\/60","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/chandankar.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/chandankar.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/chandankar.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/chandankar.com\/blog\/wp-json\/wp\/v2\/comments?post=60"}],"version-history":[{"count":5,"href":"https:\/\/chandankar.com\/blog\/wp-json\/wp\/v2\/posts\/60\/revisions"}],"predecessor-version":[{"id":75,"href":"https:\/\/chandankar.com\/blog\/wp-json\/wp\/v2\/posts\/60\/revisions\/75"}],"wp:attachment":[{"href":"https:\/\/chandankar.com\/blog\/wp-json\/wp\/v2\/media?parent=60"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/chandankar.com\/blog\/wp-json\/wp\/v2\/categories?post=60"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/chandankar.com\/blog\/wp-json\/wp\/v2\/tags?post=60"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}