{"id":1934,"date":"2026-01-23T09:46:31","date_gmt":"2026-01-23T04:16:31","guid":{"rendered":"https:\/\/www.getpanto.ai\/blog\/?p=1934"},"modified":"2026-01-27T11:26:33","modified_gmt":"2026-01-27T05:56:33","slug":"death-of-manual-qa-ai-mobile-app-testing","status":"publish","type":"post","link":"https:\/\/www.getpanto.ai\/blog\/death-of-manual-qa-ai-mobile-app-testing","title":{"rendered":"Will Manual QA Survive the Age of Agentic AI?"},"content":{"rendered":"\n<p><a href=\"https:\/\/www.getpanto.ai\/blog\/mobile-app-testing-ai-top-bugs#the-top-5-mobile-app-bugs-plaguing-development-tea\">Mobile apps<\/a> dominate today\u2019s digital economy. More than 76 percent of US adults shop on smartphones, and for many businesses, the mobile app is the primary customer touchpoint. Quality is no longer a nice to have. It is existential.<\/p>\n\n\n\n<p>Industry research reinforces this reality. A Tricentis study found that 42 percent of companies consider <a href=\"https:\/\/www.getpanto.ai\/blog\/ai-qa-automation-code-review-quality#the-future-toward-autonomous-quality\">mobile app quality<\/a> critical to competitive advantage, while 39 percent link it directly to user retention. Poor mobile experiences translate directly into churn, negative reviews, and lost revenue.<\/p>\n\n\n\n<p>Yet despite this pressure, most mobile teams still rely heavily on <strong>manual QA<\/strong> to validate releases. As AI agents enter software testing, a fundamental question emerges.<\/p>\n\n\n\n<p><strong>Will manual QA survive, or is agentic AI testing set to replace it?<\/strong><\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n<h2 class=\"wp-block-heading\" id=\"definition-manual-qa-vs-ai-testing\"><span class=\"ez-toc-section\" id=\"definition-manual-qa-vs-ai-testing\"><\/span><strong>Definition: Manual QA vs AI Testing<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<p><a href=\"https:\/\/www.getpanto.ai\/blog\/ai-vs-traditional-qa-mobile-testing#traditional-mobile-qa-is-broken-heres-why\"><strong>Manual QA<\/strong> <\/a>refers to human testers executing test cases by interacting with an application directly, validating functionality, usability, and visual behavior without automated scripts.<\/p>\n\n\n\n<p><strong>AI testing<\/strong>, particularly <strong>agentic AI testing<\/strong>, uses autonomous software agents that analyze applications, generate test scenarios, execute them independently, and adapt based on outcomes using machine learning and computer vision.<\/p>\n\n\n\n<p>This article examines manual QA vs <a href=\"https:\/\/www.getpanto.ai\/blog\/vibe-debugging-best-practices#understanding-the-vibe-debugging-workflow\">AI debugging <\/a>through the lens of mobile development and explores what QA looks like by 2030.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n<h3 class=\"wp-block-heading\" id=\"the-current-role-of-manual-qa-in-mobile-testing\"><span class=\"ez-toc-section\" id=\"the-current-role-of-manual-qa-in-mobile-testing\"><\/span><strong>The Current Role of Manual QA in Mobile Testing<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n<p>Manual QA remains foundational in many mobile teams today.<\/p>\n\n\n\n<p>Human testers excel at:<\/p>\n\n\n\n<p><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Exploratory testing<br><\/li>\n\n\n\n<li>Usability and UX validation<br><\/li>\n\n\n\n<li>New feature validation<br><\/li>\n\n\n\n<li>Subjective judgment calls that require empathy<br><\/li>\n<\/ul>\n\n\n\n<p>Testers emulate real user behavior, notice visual inconsistencies, and explore unexpected flows. These strengths explain why manual QA persists even in <a href=\"https:\/\/www.getpanto.ai\/products\/self-healing-test-automation\">teams with automation<\/a>.<\/p>\n\n\n\n<p>However, manual QA carries structural limitations that become acute as teams scale.<\/p>\n\n\n<h3 class=\"wp-block-heading\" id=\"structural-limitations-of-manual-qa\"><span class=\"ez-toc-section\" id=\"structural-limitations-of-manual-qa\"><\/span><strong>Structural Limitations of Manual QA<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Speed constraints<br><\/strong> Manual testing is slow by nature. Navigating dozens of screens across devices takes time that <a href=\"https:\/\/www.getpanto.ai\/blog\/integrating-sast-into-your-cicd-pipeline-a-step-by-step-guide\">CI\/CD pipelines<\/a> do not have.<br><\/li>\n\n\n\n<li><strong>Human error<\/strong><strong><br><\/strong> Repetitive testing leads to fatigue and oversight. Even experienced testers miss edge cases under pressure.<br><\/li>\n\n\n\n<li><strong>Coverage gaps<\/strong><strong><br><\/strong> No human team can simultaneously test hundreds of device and OS combinations.<br><\/li>\n\n\n\n<li><strong>High operational cost<br><\/strong> <a href=\"https:\/\/www.getpanto.ai\/blog\/ai-driven-mobile-qa-testing-metrics#2-coverage-metrics\">Scaling coverage<\/a> requires hiring more testers, not improving efficiency.<br><\/li>\n<\/ul>\n\n\n\n<p>In modern CI and CD environments, these limitations create release friction.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n<h3 class=\"wp-block-heading\" id=\"why-manual-qa-breaks-down-in-cicd-pipelines\"><span class=\"ez-toc-section\" id=\"why-manual-qa-breaks-down-in-cicd-pipelines\"><\/span><strong>Why Manual QA Breaks Down in CI\/CD Pipelines<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n<p>Continuous integration assumes fast, repeatable validation. Manual QA fundamentally conflicts with this assumption.<\/p>\n\n\n<h4 class=\"wp-block-heading\" id=\"key-bottlenecks\"><strong>Key Bottlenecks<\/strong><\/h4>\n\n\n<p><strong>Slow feedback loops<br><\/strong> Manual <a href=\"https:\/\/www.getpanto.ai\/blog\/ai-powered-testing#the-ai-testing-revolution-core-capabilities-transf\">QA testing<\/a> introduces delays between code completion and validation. Developers wait hours or days for results.<\/p>\n\n\n\n<p><strong>Limited parallelism<br><\/strong> Human testers cannot match the parallel execution possible in <a href=\"https:\/\/www.getpanto.ai\/blog\/device-farms-for-mobile-testing\">device farms<\/a> or cloud infrastructure.<\/p>\n\n\n\n<p><strong>Context switching cost<\/strong><strong><br><\/strong> Delayed feedback forces developers to revisit old code, increasing cognitive load and fix time.<\/p>\n\n\n\n<p><strong>Collaboration friction<\/strong><strong><br><\/strong> Agile teams stall while waiting for test completion, reducing overall velocity.<\/p>\n\n\n\n<p>As <a href=\"https:\/\/www.getpanto.ai\/blog\/browserstack-alternatives\">BrowserStack<\/a> notes, manual testing in Agile pipelines is tedious and creates a time gap between development and release readiness.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n<h2 class=\"wp-block-heading\" id=\"the-rise-of-agentic-ai-testing\"><span class=\"ez-toc-section\" id=\"the-rise-of-agentic-ai-testing\"><\/span><strong>The Rise of Agentic AI Testing<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<p><a href=\"https:\/\/www.getpanto.ai\/blog\/vibe-debugging-ai-qa-testing#the-role-of-ai-in-qa-and-testing\">AI driven testing<\/a> is evolving beyond scripted automation into <strong>agentic systems<\/strong> that behave more like digital QA teammates.<\/p>\n\n\n<h3 class=\"wp-block-heading\" id=\"what-is-an-ai-testing-agent\"><span class=\"ez-toc-section\" id=\"what-is-an-ai-testing-agent\"><\/span><strong>What Is an AI Testing Agent?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n<p>An A<a href=\"https:\/\/www.getpanto.ai\/\">I testing agent<\/a> is autonomous software that:<\/p>\n\n\n\n<p><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Observes application behavior<br><\/li>\n\n\n\n<li>Decides what actions to take<br><\/li>\n\n\n\n<li>Learns from outcomes<br><\/li>\n\n\n\n<li>Adapts test strategies over time<br><\/li>\n<\/ul>\n\n\n\n<p>Unlike <a href=\"https:\/\/www.getpanto.ai\/blog\/ai-vs-traditional-qa-mobile-testing\">traditional automation<\/a>, agents are not bound to predefined scripts.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n<h3 class=\"wp-block-heading\" id=\"how-agentic-ai-testing-works\"><span class=\"ez-toc-section\" id=\"how-agentic-ai-testing-works\"><\/span><strong>How Agentic AI Testing Works<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n<h4 class=\"wp-block-heading\" id=\"1-application-understanding\"><strong>1. Application Understanding<\/strong><\/h4>\n\n\n<p>Agents map UI elements using computer vision and semantic analysis. Screens, buttons, inputs, and <a href=\"https:\/\/www.getpanto.ai\/blog\/automated-mobile-qa-ai-testing#evolution-from-unit-testing-to-holistic-user-journ\">user flows<\/a> are identified without manual locators.<\/p>\n\n\n<h4 class=\"wp-block-heading\" id=\"2-action-selection\"><strong>2. Action Selection<\/strong><\/h4>\n\n\n<p>Instead of following scripts, agents choose actions based on learned behavior. They explore paths likely to expose bugs, including edge cases.<\/p>\n\n\n<h4 class=\"wp-block-heading\" id=\"3-reinforcement-learning\"><strong>3. Reinforcement Learning<\/strong><\/h4>\n\n\n<p>Advanced agents learn from failures and successes, refining future test strategies.<\/p>\n\n\n<h4 class=\"wp-block-heading\" id=\"4-self-healing\"><strong>4. Self Healing<\/strong><\/h4>\n\n\n<p>When UI changes, agents adapt rather than fail, updating internal models automatically.<\/p>\n\n\n\n<p>This autonomy distinguishes agentic testing from traditional <a href=\"https:\/\/www.getpanto.ai\/blog\/playwright-vs-maestro\">automation frameworks<\/a>.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<!-- Centered Wrapper -->\n<div style=\"\n  max-width:1200px;\n  margin:0 auto;\n  padding:0 16px;\n\">\n  <!-- Hero Banner: Vibe Debugging -->\n  <div style=\"\n    display:inline-flex;\n    gap:32px;\n    align-items:center;\n    padding:32px;\n    background:linear-gradient(135deg, #ECFEFF 0%, #F0FDFA 100%);\n    border-radius:4px;\n    border:1px solid #99F6E4;\n    box-shadow:0 16px 32px rgba(13,148,136,0.1);\n    margin:40px 0;\n    flex-wrap:wrap;\n    font-family:'Montserrat', -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Arial, sans-serif;\n  \">\n\n    <!-- LEFT: Product Image -->\n    <div style=\"\n      flex:0 0 420px;\n    \">\n      <img decoding=\"async\" \n        src=\"https:\/\/www.getpanto.ai\/blog\/wp-content\/uploads\/2025\/11\/panto-ai-image-3.png\" \n        alt=\"Vibe Debugging Example\"\n        style=\"\n          width:100%;\n          height:auto;\n          display:block;\n          border-radius:4px;\n        \"\n      \/>\n    <\/div>\n\n    <!-- RIGHT: Value Proposition -->\n    <div style=\"\n      flex:1;\n      display:flex;\n      flex-direction:column;\n      justify-content:center;\n    \">\n      <h1 style=\"\n        font-size:30px;\n        line-height:1.2;\n        margin:0 0 12px;\n        font-weight:800;\n        color:#0F172A;\n        text-align:center;\n      \">Everything After Vibe Coding\n      <\/h1>\n\n      <p style=\"\n        font-size:14px;\n        line-height:1.55;\n        color:#334155;\n        margin:0 0 16px;\n        max-width:520px;\n      \">\n        Panto AI helps developers find, explain, and fix bugs faster with AI-assisted QA\u2014reducing downtime and preventing regressions.\n      <\/p>\n\n      <!-- Feature List -->\n      <ul style=\"\n        list-style:none;\n        padding:0;\n        margin:0 0 20px;\n      \">\n        <li style=\"display:flex; gap:10px; margin-bottom:10px; font-size:15px; color:#0F172A;\">\n          <span style=\"color:#0d9488; font-weight:700;\">\u2713<\/span>\n          Explain bugs in natural language\n        <\/li>\n        <li style=\"display:flex; gap:10px; margin-bottom:10px; font-size:15px; color:#0F172A;\">\n          <span style=\"color:#0d9488; font-weight:700;\">\u2713<\/span>\n          Create reproducible test scenarios in minutes\n        <\/li>\n        <li style=\"display:flex; gap:10px; font-size:15px; color:#0F172A;\">\n          <span style=\"color:#0d9488; font-weight:700;\">\u2713<\/span>\n          Run scripts and track issues with zero AI hallucinations\n        <\/li>\n      <\/ul>\n\n      <!-- CTA -->\n      <a href=\"https:\/\/www.getpanto.ai\"\n         style=\"\n          display:block;\n          width:100%;\n          max-width:520px;\n          padding:14px 0;\n          background:linear-gradient(135deg, #0d9488, #14b8a6);\n          color:#ffffff;\n          font-size:16px;\n          font-weight:700;\n          text-align:center;\n          border-radius:4px;\n          text-decoration:none;\n          box-shadow:0 8px 20px rgba(13,148,136,0.3);\n         \">\n        Try Panto \u2192 \n      <\/a>\n\n    <\/div>\n  <\/div>\n<\/div>\n\n\n\n\n\n\n<h3 class=\"wp-block-heading\" id=\"market-momentum-behind-ai-testing\"><span class=\"ez-toc-section\" id=\"market-momentum-behind-ai-testing\"><\/span><strong>Market Momentum Behind AI Testing<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n<p>The shift is not theoretical. Market data confirms it.<\/p>\n\n\n\n<p><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/www.getpanto.ai\/blog\/ai-powered-testing#traditional-vs-ai-powered-testing-the-performance\">The AI-powered testing<\/a> market grew from USD 414.7M in 2022 and is projected to reach USD 1.63B by 2030 at 18.4 percent CAGR.<br><\/li>\n\n\n\n<li>The broader AI agent market is forecast to grow from USD 5.1B in 2024 to USD 47.1B by 2030.<br><\/li>\n\n\n\n<li>QA skill profiles are shifting rapidly, with AI and ML proficiency rising sharply among testers.<br><\/li>\n<\/ul>\n\n\n\n<p>These trends signal a structural change, not a tooling fad.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n<h3 class=\"wp-block-heading\" id=\"manual-qa-vs-agentic-ai-testing-a-comparison\"><span class=\"ez-toc-section\" id=\"manual-qa-vs-agentic-ai-testing-a-comparison\"><\/span><strong>Manual QA vs Agentic AI Testing: A Comparison<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><tbody><tr><td><strong>Dimension<\/strong><\/td><td><strong>Manual QA<\/strong><\/td><td><strong>Agentic AI Testing<\/strong><\/td><\/tr><tr><td>Speed<\/td><td>Slow<\/td><td>Near real time<\/td><\/tr><tr><td>Coverage<\/td><td>Limited<\/td><td>Broad and combinatorial<\/td><\/tr><tr><td>Scalability<\/td><td>Linear with headcount<\/td><td>Scales with compute<\/td><\/tr><tr><td>Maintenance<\/td><td>Human intensive<\/td><td>Self adapting<\/td><\/tr><tr><td>CI\/CD fit<\/td><td>Poor<\/td><td>Native<\/td><\/tr><tr><td>Cost efficiency<\/td><td>Low at scale<\/td><td>High at scale<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>Manual QA provides depth in narrow areas. Agentic AI provides breadth and speed.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n<h2 class=\"wp-block-heading\" id=\"what-mobile-testing-looks-like-in-2030\"><span class=\"ez-toc-section\" id=\"what-mobile-testing-looks-like-in-2030\"><\/span><strong>What Mobile Testing Looks Like in 2030<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<p>By 2030, QA evolves into <strong>Quality Engineering<\/strong>.<\/p>\n\n\n<h3 class=\"wp-block-heading\" id=\"1-expected-characteristics\"><span class=\"ez-toc-section\" id=\"1-expected-characteristics\"><\/span><strong>1. Expected Characteristics<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n<p><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>AI driven risk scoring <a href=\"https:\/\/www.getpanto.ai\/products\/ai-code-review\/sca\">highlights high risk<\/a> modules daily<br><\/li>\n\n\n\n<li>Autonomous agents generate and execute tests continuously<br><\/li>\n\n\n\n<li>Tests are scheduled dynamically based on cost and infrastructure availability<br><\/li>\n\n\n\n<li>Developers receive real time quality feedback in IDEs<br><\/li>\n\n\n\n<li>Production monitoring feeds back into <a href=\"https:\/\/www.getpanto.ai\/blog\/ai-test-case-generation\">test generation<\/a><br><\/li>\n\n\n\n<li>Human testers act as quality strategists, not click operators<br><\/li>\n<\/ul>\n\n\n\n<p>Testing becomes continuous, adaptive, and data driven.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n<h3 class=\"wp-block-heading\" id=\"2-organizational-impact\"><span class=\"ez-toc-section\" id=\"2-organizational-impact\"><\/span><strong>2. Organizational Impact<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n<h4 class=\"wp-block-heading\" id=\"skills-evolution\"><strong>Skills Evolution<\/strong><\/h4>\n\n\n<p>Manual testing skills remain relevant, but AI literacy becomes essential. QA engineers shift toward analysis, orchestration, and <a href=\"https:\/\/www.getpanto.ai\/blog\/ai-governance-replacing-manual-code-audits\">code governance<\/a>.<\/p>\n\n\n<h4 class=\"wp-block-heading\" id=\"cost-structure\"><strong>Cost Structure<\/strong><\/h4>\n\n\n<p>Upfront investment in AI infrastructure is offset by long term efficiency gains and reduced manual overhead.<\/p>\n\n\n<h4 class=\"wp-block-heading\" id=\"speed-to-market\"><strong>Speed to Market<\/strong><\/h4>\n\n\n<p>Validation cycles shrink dramatically, enabling more frequent releases with lower risk.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n<h3 class=\"wp-block-heading\" id=\"where-panto-ai-fits-conceptually\"><span class=\"ez-toc-section\" id=\"where-panto-ai-fits-conceptually\"><\/span><strong>Where <\/strong><a href=\"https:\/\/www.getpanto.ai\/\"><strong>Panto AI<\/strong><\/a><strong> Fits Conceptually<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n<p>Some platforms are positioning themselves around agent driven QA that integrates tightly with <a href=\"https:\/\/www.getpanto.ai\/blog\/how-panto-ais-cross-file-dependency-analysis-is-transforming-tech-teams-development-workflows\">developer workflows<\/a>.<\/p>\n\n\n\n<p>The core idea is not replacing humans, but removing friction between code changes and quality validation. AI agents operate continuously, while humans guide strategy and interpret critical failures.<\/p>\n\n\n\n<p>This hybrid model reflects where the industry is heading.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n<h3 class=\"wp-block-heading\" id=\"key-takeaways\"><span class=\"ez-toc-section\" id=\"key-takeaways\"><\/span><strong>Key Takeaways<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n<p><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/www.getpanto.ai\/blog\/best-qa-automation-tools#traditional-qa-automation-vs-ai-qa-automation\">Traditional or manual QA<\/a> is not disappearing, but its role is shrinking<br><\/li>\n\n\n\n<li>Agentic AI testing addresses scale, speed, and coverage gaps<br><\/li>\n\n\n\n<li>The future of QA is hybrid, not purely human or purely automated<br><\/li>\n\n\n\n<li>Teams that delay adoption risk slower releases and higher costs<br><\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n<h3 class=\"wp-block-heading\" id=\"conclusion-preparing-for-an-agent-driven-future\"><span class=\"ez-toc-section\" id=\"conclusion-preparing-for-an-agent-driven-future\"><\/span><strong>Conclusion: Preparing for an Agent Driven Future<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n<p>The era of manual QA as the primary <a href=\"https:\/\/www.getpanto.ai\/blog\/ai-qa-automation-code-review-quality#metrics-that-matter-quantifying-the-quality-loop\">quality gate<\/a> is ending. By 2030, QA becomes an intelligence driven discipline supported by autonomous agents.<\/p>\n\n\n\n<p>The choice facing engineering leaders is not whether AI will enter QA, but how deliberately it will be integrated.<\/p>\n\n\n\n<p><strong>Teams that invest early in <\/strong><a href=\"https:\/\/www.getpanto.ai\/\"><strong>platforms going for agentic testing<\/strong><\/a><strong> and skill transformation will ship faster, with higher confidence, and lower operational drag.<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Mobile apps dominate today\u2019s digital economy. More than 76 percent of US adults shop on smartphones, and for many businesses, the mobile app is the primary customer touchpoint. Quality is no longer a nice to have. It is existential. Industry research reinforces this reality. A Tricentis study found that 42 percent of companies consider mobile [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":1936,"comment_status":"open","ping_status":"open","sticky":false,"template":"wp-custom-template-panto-blogs-v3","format":"standard","meta":{"footnotes":""},"categories":[110],"tags":[],"class_list":["post-1934","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-vibe-debugging"],"_links":{"self":[{"href":"https:\/\/www.getpanto.ai\/blog\/wp-json\/wp\/v2\/posts\/1934","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.getpanto.ai\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.getpanto.ai\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.getpanto.ai\/blog\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.getpanto.ai\/blog\/wp-json\/wp\/v2\/comments?post=1934"}],"version-history":[{"count":0,"href":"https:\/\/www.getpanto.ai\/blog\/wp-json\/wp\/v2\/posts\/1934\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.getpanto.ai\/blog\/wp-json\/wp\/v2\/media\/1936"}],"wp:attachment":[{"href":"https:\/\/www.getpanto.ai\/blog\/wp-json\/wp\/v2\/media?parent=1934"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.getpanto.ai\/blog\/wp-json\/wp\/v2\/categories?post=1934"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.getpanto.ai\/blog\/wp-json\/wp\/v2\/tags?post=1934"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}