{"id":154,"date":"2026-08-18T05:04:36","date_gmt":"2026-08-18T05:04:36","guid":{"rendered":"https:\/\/www.akarnik.com\/blog\/ai-visibility-for-consultants"},"modified":"2026-08-18T05:04:36","modified_gmt":"2026-08-18T05:04:36","slug":"ai-visibility-for-consultants","status":"publish","type":"post","link":"https:\/\/www.akarnik.com\/blog\/ai-visibility-for-consultants","title":{"rendered":"AI Visibility for Consultants: The 7-Step System"},"content":{"rendered":"<p><em>Written by: Arjun Karnik, Growth Marketing Specialist<\/em><\/p>\n<h2 id=\"key-takeaways\">What Consultants Gain From This AI Visibility System<\/h2>\n<ul>\n<li>AI visibility now decides whether a consulting practice gets named inside ChatGPT, Perplexity, or Google AI Overviews, shifting value from clicks to mentions in synthesized answers.<\/li>\n<li>Buyers arrive pre-educated by AI assistants, so consultants whose names appear in those answers start sales calls on the shortlist while others may never get the call.<\/li>\n<li>The 7-step system \u2013 entity clarity, fan-out query mapping, buyer-language alignment, structured publishing, freshness loop, citation measurement, and defensive GEO \u2013 delivers measurable citations and impressions on Arjun Karnik\u2019s own site.<\/li>\n<li>Pages rewritten to match buyer language and fan-out queries extracted from ChatGPT earn citations within weeks, while control pages that retain jargon do not.<\/li>\n<li>Run the visibility audit first to see how the system maps to your practice \u2013 <a href=\"https:\/\/www.akarnik.com\/demo\" target=\"_blank\">book your visibility audit with Arjun Karnik<\/a>.<\/li>\n<\/ul>\n<h2>Why AI Is Reshaping Consulting Demand, Not Replacing It<\/h2>\n<p>Consulting remains essential, but the buyer journey has changed. Buyers who once arrived at a sales call with surface-level awareness now arrive pre-educated by an assistant. The consultant whose name appeared in that assistant&#8217;s answer starts the call on the shortlist. The consultant whose name did not appear may never get the call. Three signals visible inside any well-run SEO program confirm that this shift is already underway.<\/p>\n<figure style=\"text-align: center\"><a href=\"https:\/\/www.akarnik.com\/demo\" target=\"_blank\"><img decoding=\"async\" src=\"https:\/\/cdn.aigrowthmarketer.co\/1786472460824-bf9470f3f071.png\" alt=\"Line chart showing the scissors pattern over twelve months, with an impressions line rising while a clicks line falls away from it. Illustrative shape of the pattern, not data from a specific account.\" style=\"max-height: 500px\" loading=\"lazy\"><\/a><figcaption><em>Both lines start together. The content keeps getting read so impressions rise, the answer gets delivered on the results page so the click never happens. Most owners see only the falling line.<\/em><\/figcaption><\/figure>\n<ol>\n<li><strong>The Search Console scissors.<\/strong> Impressions climb while clicks fall. The content is being consumed to construct AI answers, yet it no longer sends traffic the way it used to. Similarweb clickstream data shows the zero-click rate for Google searches <a href=\"https:\/\/aigrowthagent.co\/articles\/ai-search-visibility-strategy\/\" target=\"_blank\">reached 68.01% in January through April 2026, up from 60.45% in 2024<\/a>. The buyer reads the answer where they asked it.<\/li>\n<li><strong>AI referrers that convert like referrals.<\/strong> Traffic arriving from chatgpt.com and its equivalents behaves nothing like cold search traffic. <a href=\"https:\/\/yesoptimist.com\/metrics-for-aeo-campaigns\" target=\"_blank\" rel=\"noindex nofollow\">Seer Interactive analysis showed ChatGPT-referred traffic converting at 15.9% compared with 1.76% for Google organic search<\/a>. An assistant recommended the practice, which functions like word of mouth.<\/li>\n<li><strong>Pre-educated prospects.<\/strong> Sales calls start further down the funnel. <a href=\"https:\/\/blog.andrewbyzov.com\/posts\/state-of-ai-search-for-b2b-saas-2026\" target=\"_blank\" rel=\"noindex nofollow\">Forrester&#8217;s 2026 Buyers&#8217; Journey Survey of nearly 18,000 global business buyers found that 94% used generative AI in their purchase process, with twice as many naming generative AI or conversational search as their most meaningful research source compared to any other source, including vendor websites and sales reps<\/a>.<\/li>\n<\/ol>\n<p>These three signals point to the same shift. Visibility now means being named in the answer, not just ranked in the list. The system below is the operational response to that shift, built and tested on Arjun&#8217;s own site to move a consulting practice from invisible to cited.<\/p>\n<figure style=\"text-align: center\"><a href=\"https:\/\/www.akarnik.com\/demo\" target=\"_blank\"><img decoding=\"async\" src=\"https:\/\/cdn.aigrowthmarketer.co\/1786472409902-31baebe3e87f.png\" alt=\"Bar chart showing the share of B2B software buyers who start research with an AI chatbot more often than Google, rising from 29 percent in April 2025 to 51 percent in March 2026. Source: G2, 1,076 B2B software buyers and decision-makers.\" style=\"max-height: 500px\" loading=\"lazy\"><\/a><figcaption><em>In under a year the starting point for B2B software research crossed over. More buyers now begin with a chatbot than with Google.<\/em><\/figcaption><\/figure>\n<h2>The 7-Step AI Visibility System for Consulting Practices<\/h2>\n<p>This system is what Arjun runs in his public test lab under his own name, documented with Search Console numbers and decay curves. Each step carries its own job. Skipping any one of them breaks the chain.<\/p>\n<figure style=\"text-align: center\"><a href=\"https:\/\/www.akarnik.com\/demo\" target=\"_blank\"><img decoding=\"async\" src=\"https:\/\/cdn.aigrowthmarketer.co\/1786472438102-dfd59b5fabac.png\" alt=\"Bar chart showing 75 percent of pages cited by AI assistants were updated within the last year and 25 percent were older. Source: Seer Interactive, July 2026, 7,683 pages and 47,097 citations across ChatGPT, Gemini and Perplexity.\" style=\"max-height: 500px\" loading=\"lazy\"><\/a><figcaption><em>Three quarters of cited pages were updated inside a year, and the consistently cited ones averaged under six months. The page you refresh beats the page you write.<\/em><\/figcaption><\/figure>\n<ol>\n<li><strong>Entity clarity.<\/strong> Define the practice with one consistent name, description, service category, and founder bio across the website, social profiles, directories, and schema markup. <a href=\"https:\/\/beamtrace.com\/blog\/ai-visibility-optimization\" target=\"_blank\" rel=\"noindex nofollow\">Ahrefs analysis of 75,000 brands found that brand mentions across the web correlate with AI visibility at 0.664, significantly higher than the 0.218 correlation for backlinks<\/a>. The machine must know who the practice is before it can recommend it.<\/li>\n<li><strong>Fan-out query mapping.<\/strong> A single buyer prompt triggers dozens of hidden retrieval queries underneath. <a href=\"https:\/\/betteraisearch.com\/tactics\/fan-out-queries-geo\" target=\"_blank\" rel=\"noindex nofollow\">Pages ranking for AI fan-out sub-queries are 161% more likely to be cited than those ranking only for main keywords, and pages ranking for main query plus 1+ fan-out queries achieve a 51% citation rate<\/a>. Fan-out queries come directly from ChatGPT rather than from keyword tools, because the target is the machine&#8217;s questions, not the human&#8217;s typed phrase.<\/li>\n<li><strong>Buyer-language alignment.<\/strong> URLs, titles, H1s, and H2s are rewritten to match the language buyers use, not the jargon practitioners use. On Arjun&#8217;s own site, relabelling a jargon page to buyer language produced citations within weeks of that specific change.<\/li>\n<li><strong>Structured publishing at machine cadence.<\/strong> An AI article engine on a site subfolder publishes structured pages at a cadence a human team cannot match, using AI Growth Agent at 5 to 8 autonomous actions per day. <a href=\"https:\/\/aigrowthagent.co\/articles\/ai-search-visibility-strategy\/\" target=\"_blank\">76.4% of pages cited by ChatGPT were updated within the prior 30 days<\/a>. That cadence matters because freshness acts as a primary ranking signal. Query language sits in URLs, titles, and H1s so retrieval systems can match questions to answers, and schema on every page lets the machine extract facts without guessing.<\/li>\n<li><strong>Freshness loop.<\/strong> Impression-decay tripwires monitor performance and automatically queue an update when a page starts falling. In Arjun&#8217;s tests, pages dropped 78% to 99% in two months without maintenance. <a href=\"https:\/\/aigrowthagent.co\/articles\/best-perplexity-ai-seo-tools\/\" target=\"_blank\">Content freshness accounts for 40% of Perplexity&#8217;s ranking signal, and pages under 30 days old receive 3.2\u00d7 more citations than older content<\/a>. The loop runs without anyone auditing a spreadsheet.<\/li>\n<li><strong>Citation measurement.<\/strong> Citations are tracked across ChatGPT, Google AI Overviews, Perplexity, and Gemini, alongside AI referrers in analytics and impression and decay curves in Google Search Console. Share of answer replaces rank position as the headline metric. Measured impact forms a floor, not a ceiling, because buyers often copy an answer, type a name directly into a browser bar, and land in analytics as direct traffic.<\/li>\n<li><strong>Defensive GEO.<\/strong> What AI currently says about the practice is audited and corrected before any growth work begins. A wrong AI answer hurts more than no answer. The visibility audit across all four surfaces is what reveals the problem in the first place.<\/li>\n<\/ol>\n<h2>Best AI Visibility Approaches for Consultants in 2026<\/h2>\n<p>Five approaches exist for solving this visibility problem. All five break on some combination of volume, structure, and freshness. The table below reveals a pattern: every approach except a dedicated GEO platform fails to deliver all three requirements at once, and without all three, citations do not materialize. AI Growth Agent results are attributed separately and are not Arjun&#8217;s numbers.<\/p>\n<table>\n<thead>\n<tr>\n<th>Approach<\/th>\n<th>Volume<\/th>\n<th>Structure &amp; freshness<\/th>\n<th>Where it breaks<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Do it yourself<\/td>\n<td>Low, founder time is the binding constraint<\/td>\n<td>Inconsistent, no refresh loop<\/td>\n<td>Fails the volume and freshness math, one person cannot publish and refresh at machine cadence<\/td>\n<\/tr>\n<tr>\n<td>Traditional SEO agencies<\/td>\n<td>Moderate, retainer-paced<\/td>\n<td>Optimized for rankings, not citations, no fan-out mapping<\/td>\n<td>Optimizing for lists buyers no longer read; <a href=\"https:\/\/aigrowthagent.co\/articles\/ai-search-visibility-strategy\/\" target=\"_blank\">80% of LLM citations come from pages that do not rank in Google&#8217;s top 100<\/a><\/td>\n<\/tr>\n<tr>\n<td>Human content agencies<\/td>\n<td>Low, about $10,000\/month for 7\u201310 articles, no refresh<\/td>\n<td>Well-written but unstructured and unrefreshed<\/td>\n<td>The machine ignores prose that lacks schema, fan-out alignment, and a maintenance loop<\/td>\n<\/tr>\n<tr>\n<td>Cheap one-shot AI content<\/td>\n<td>High, but publish-and-forget<\/td>\n<td>No structure, no question mapping, no maintenance<\/td>\n<td><a href=\"https:\/\/aigrowthagent.co\/articles\/best-perplexity-ai-seo-tools\/\" target=\"_blank\">The Semrush AI Visibility Study found that AI citations change 40 to 60% month over month<\/a>, so volume without freshness turns into slop<\/td>\n<\/tr>\n<tr>\n<td>AI Growth Agent (GEO platform)<\/td>\n<td>High, 5\u20138 autonomous actions\/day<\/td>\n<td>Fan-out mapping, schema on everything, impression-decay tripwires<\/td>\n<td>AI Growth Agent clients average <a href=\"https:\/\/aigrowthagent.co\/articles\/ai-search-visibility-strategy\/\" target=\"_blank\">more than 12,000 additional AI citations and a 20% or greater lift in impressions across the first twelve weeks<\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><a href=\"https:\/\/www.akarnik.com\/demo\" target=\"_blank\"><strong>Find out which approach fits your practice \u2013 book a consultation<\/strong><\/a><\/p>\n<h2>How Consultants Track and Prove AI Citations<\/h2>\n<p>Three metrics form the core of an AI visibility measurement framework. Each metric is tracked per platform rather than blended across engines, because <a href=\"https:\/\/thesmarketers.com\/blogs\/measure-ai-search-visibility\" target=\"_blank\" rel=\"noindex nofollow\">only 11% of domains are cited simultaneously by both ChatGPT and Perplexity<\/a>.<\/p>\n<ol>\n<li><strong>Citation share.<\/strong> This is the percentage of tracked prompts where a domain is cited as a source, which functions as the AI-era version of share of voice. <a href=\"https:\/\/leadsources.io\/glossary\/brand-citation-frequency\" target=\"_blank\" rel=\"noindex nofollow\">Average citation rates across B2B brands sit at 18\u201332%, with category leaders achieving 40%+ and brands below 15% performing substantially worse<\/a>.<\/li>\n<li><strong>Mention rate.<\/strong> This is the percentage of tracked prompts where the brand name appears, cited or not. Separating mention rate from citation share reveals whether the issue is entity clarity or content authority. <a href=\"https:\/\/averi.ai\/how-to\/how-to-measure-geo-ai-citation-metrics-framework\" target=\"_blank\" rel=\"noindex nofollow\">ChatGPT mentions brands 3.2x more often than it provides clickable citations<\/a>, so tracking only citations understates brand presence.<\/li>\n<li><strong>AI referral conversion rate.<\/strong> Sessions arriving from chatgpt.com, perplexity.ai, and gemini.google.com are segmented in GA4 and measured against conversion goals. <a href=\"https:\/\/megaoneai.com\/blog\/ai-search-traffic-5x-conversion\/\" target=\"_blank\" rel=\"noindex nofollow\">Observed AI referral conversion rates average 14.2% (up to 16.8% by platform) in IT and technology sectors, compared with 2.8% for traditional Google organic traffic<\/a>.<\/li>\n<\/ol>\n<p>Unlabeled copy-and-paste behavior means measured impact understates real impact. A buyer reads an AI answer, copies a name, and types it into a browser, which lands in analytics as direct traffic. Whatever is measured functions as a floor.<\/p>\n<figure style=\"text-align: center\"><a href=\"https:\/\/www.akarnik.com\/demo\" target=\"_blank\"><img decoding=\"async\" src=\"https:\/\/cdn.aigrowthmarketer.co\/1786472616931-9a13bc7984c5.png\" alt=\"Bar chart showing 2.5 percent of downstream brand visits after an AI mention carry a trackable referral parameter while 97.5 percent arrive untraceable. Source: Profound, analysis of more than 2 million AI conversations, January to June 2026.\" style=\"max-height: 500px\" loading=\"lazy\"><\/a><figcaption><em>Buyers read an answer, then type your name into a browser. That visit lands as direct or branded search, so whatever you measure here is a floor and never a ceiling.<\/em><\/figcaption><\/figure>\n<h3>7-Question AI Visibility Audit for Consulting Practices<\/h3>\n<p>This quick audit turns the measurement framework into a checklist you can run against your own practice.<\/p>\n<ol>\n<li>Does your practice name appear in ChatGPT, Perplexity, Google AI Overviews, and Gemini when a buyer asks the category question you answer best?<\/li>\n<li>Are AI crawlers (GPTBot, PerplexityBot, Google-Extended) unblocked in your robots.txt?<\/li>\n<li>Do your URLs, title tags, and H1s use the exact language buyers type into AI assistants, or the jargon your industry uses internally?<\/li>\n<li>Does every key page carry Organization, FAQ, or HowTo schema markup?<\/li>\n<li>Have any of your top-performing pages gone more than 60 days without a substantive update?<\/li>\n<li>Is chatgpt.com segmented as a distinct traffic source in your analytics, and do you know its conversion rate?<\/li>\n<li>Do you know what AI assistants currently say about your practice, including whether any of it is wrong?<\/li>\n<\/ol>\n<h2>Real Positioning Rewrites That Unlocked AI Citations<\/h2>\n<p>The following three examples come from tests on Arjun&#8217;s own site. Each shows a before-and-after title rewrite and the citation outcome observed.<\/p>\n<ol>\n<li><strong>Before:<\/strong> &#8220;Generative Engine Optimization: An Overview.&#8221; <strong>After:<\/strong> &#8220;How to Get Your Business Recommended by AI Search.&#8221; The slug, title, H1, and H2s were all realigned to buyer questions. Citations followed within weeks of that specific change on Arjun&#8217;s own site.<\/li>\n<li><strong>Before:<\/strong> &#8220;GEO Content Architecture Principles.&#8221; <strong>After:<\/strong> &#8220;Why Doesn&#8217;t AI Mention My Business and How to Fix It.&#8221; Rewriting to the exact pain phrase buyers type into assistants moved the page into the candidate pool for fan-out queries it had previously missed entirely.<\/li>\n<li><strong>Before:<\/strong> &#8220;Fan-Out Query Methodology.&#8221; <strong>After:<\/strong> &#8220;My Competitor Shows Up in ChatGPT and I Don&#8217;t: What to Do.&#8221; Pages rewritten to match extracted ChatGPT fan-out queries earned citations on Arjun&#8217;s own site while control pages held back from the rewrite did not.<\/li>\n<\/ol>\n<p>The pattern across all three examples is consistent. Jargon blocks visibility at the moment the machine matches a question to an answer, and buyer language removes that barrier.<\/p>\n<h2>What Arjun\u2019s Test Lab Shows on His Own Site<\/h2>\n<p>Every result below was measured on Arjun&#8217;s own site, run via AI Growth Agent. His numbers and AI Growth Agent&#8217;s published case studies are never blended.<\/p>\n<ul>\n<li><strong>Fan-out citation test.<\/strong> Pages rewritten to match fan-out queries extracted directly from ChatGPT earned citations, while control pages held back from the rewrite did not. The variable was query-language alignment, isolated by the control.<\/li>\n<li><strong>Content decay without maintenance.<\/strong> In Arjun&#8217;s tests, pages dropped 78% to 99% in two months without updates. This matches the direction of independent research: Seer Interactive analyzed 47,097 AI citations across 7,683 pages in ChatGPT, Gemini, and Perplexity between March and June 2026 and found that 75% of cited pages had been updated within the last year, with consistently cited pages averaging under six months since their last update.<\/li>\n<li><strong>Subfolder impressions.<\/strong> The GEO subfolder went from zero to the only source of new impressions on the entire domain in 60 days, measured in Google Search Console.<\/li>\n<li><strong>New article performance.<\/strong> New articles reached thousands of monthly Google impressions within weeks of publication.<\/li>\n<li><strong>Buyer-language test.<\/strong> Relabelling a jargon page to buyer language produced citations within weeks of that specific change on Arjun&#8217;s own site.<\/li>\n<\/ul>\n<p>The system being documented is the same system producing the visibility. Asking an AI assistant about generative engine optimization reveals who gets cited, which creates a self-verifying test no other option in this space currently offers.<\/p>\n<h2>Conclusion and Next Step for Your Practice<\/h2>\n<p>Rankings hold while clicks fall because buyers now ask assistants instead of scanning lists. That shift creates a new competitive axis, where consultants who earn citations in AI answers start sales calls on the shortlist, and those who do not may never get the call. The 7-step system \u2013 entity clarity, fan-out query mapping, buyer-language alignment, structured publishing, freshness loop, citation measurement, and defensive GEO \u2013 provides a repeatable path to earning those citations, built on the operational requirements the comparison table highlighted: volume, structure, and freshness delivered together. The window for outsized gains is open now, and answers gain incumbency, so early citations become tomorrow&#8217;s record.<\/p>\n<p><a href=\"https:\/\/www.akarnik.com\/demo\" target=\"_blank\"><strong>Start with the visibility audit to map the system to your practice<\/strong><\/a><\/p>\n<h2>Frequently Asked Questions<\/h2>\n<h3>What is the difference between AI visibility and traditional SEO for consultants?<\/h3>\n<p>Traditional SEO optimizes for a position on a ranked list of links. A buyer types a query, receives ten results, and chooses among them. Authority in that system comes from backlinks and domain authority accumulated over time. AI visibility optimizes for citation inside a machine-generated answer. A buyer asks an assistant a question and receives one synthesized response. Authority in this system comes from topical coverage, structured content, entity clarity, and freshness, not from link accumulation. The success metric shifts from rank position to citation share, mention rate, and share of answer. The two systems share technical foundations such as crawlability, schema, and quality content, yet they optimize toward different targets and measure different outcomes. A consultant can hold strong traditional rankings while being absent from AI-generated answers, because most LLM citations come from pages outside traditional top rankings (as noted in the comparison table earlier).<\/p>\n<h3>How long does it take for a consultant to start appearing in AI-generated answers?<\/h3>\n<p>The timeline unfolds in three phases. Coverage and impressions in Google Search Console typically appear within weeks of publishing structured, buyer-language-aligned content. On Arjun&#8217;s site, new articles reached thousands of monthly Google impressions within weeks of publication, and the GEO subfolder became the only source of new impressions on the domain within 60 days. Citations in AI assistants typically follow in one to three months as the retrieval layer indexes and begins pulling from the new content. Compounding, where topical authority accumulates and citation share grows across a broader question set, usually begins after month three. This timeline assumes technical plumbing is in place from the start, with AI crawlers unblocked, schema implemented, and pages machine-parseable; without those foundations, downstream content investment does not produce citations regardless of quality.<\/p>\n<h3>Why do impressions go up in Search Console while revenue stays flat or falls?<\/h3>\n<p>This pattern, often called the Search Console scissors, signals that a practice&#8217;s content has shifted from driving clicks to feeding AI answers. The content is read and consumed by AI retrieval systems to construct generated responses, yet it no longer sends visitors to the site because the buyer reads the answer inside the assistant instead of clicking through. The buyer journey now runs from AI answer to brand search or direct URL entry and then to visit, which does not leave a clean click trail in analytics. The content still does its job, but it does not produce the click that traditional reporting expects. The correct response is to instrument for citations and AI referral traffic instead of grading the channel on a metric it no longer produces. AI-referred sessions, when they arrive, convert at materially higher rates than cold organic traffic, as <a href=\"https:\/\/megaoneai.com\/blog\/ai-search-traffic-5x-conversion\/\" target=\"_blank\" rel=\"noindex nofollow\">observed AI referral conversion rates average 14.2% (up to 16.8% by platform) in IT and technology sectors compared with 2.8% for traditional Google organic traffic<\/a>, because those visitors arrive pre-educated by the answer that named the practice.<\/p>\n<h3>What does \u201cimpressions up, clicks down\u201d actually mean for a consulting practice&#8217;s pipeline?<\/h3>\n<p>This pattern means the practice is being used as a source by AI systems but is not yet being named in the answers those systems generate for buyers. The content is visible enough to be retrieved and consumed in the background, but not structured, fresh, or buyer-language-aligned enough to earn the citation that puts the practice name in front of the buyer. Pipeline impact becomes invisible rather than absent, because buyers encounter the practice&#8217;s ideas through AI answers that do not attribute them, while competitors whose content is structured for citation get named instead. The fix is not more content. The fix is restructuring existing content to earn citations by aligning URLs, titles, and H1s to fan-out query language, adding schema, and running a freshness loop so the retrieval layer moves the practice from background source to named recommendation.<\/p>\n<h3>Can a small consulting practice compete with larger firms for AI citations?<\/h3>\n<p>Relevance and freshness beat tenure in AI retrieval systems. A larger firm with a decade of domain authority and a stale content library loses citation share to a smaller practice publishing and refreshing at cadence, because the game resets weekly. AI retrieval systems match a question to the best available answer, not to the longest-established domain. This structure differs from traditional SEO, where accumulated domain authority creates a durable moat. The practical strategy for a smaller practice is to target specific fan-out queries, situations, comparisons, and contexts first, where a precise, fresh, structured answer beats a broad, stale one, and then compound toward head-term coverage as topical authority grows. A competitive citation share for B2B brands in 2026 sits between 5% and 15% aggregate across major AI engines, with 20% or above signaling category leadership, and a focused small practice can reach that range on its core topic cluster faster than a large firm can refresh a sprawling content library.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Get your consulting practice cited in ChatGPT, Perplexity &amp; Google AI Overviews. Arjun Karnik&#8217;s 7-step system turns AI into your referral engine.<\/p>\n","protected":false},"author":118,"featured_media":153,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-154","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/www.akarnik.com\/blog\/wp-json\/wp\/v2\/posts\/154","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.akarnik.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.akarnik.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/www.akarnik.com\/blog\/wp-json\/wp\/v2\/comments?post=154"}],"version-history":[{"count":0,"href":"https:\/\/www.akarnik.com\/blog\/wp-json\/wp\/v2\/posts\/154\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.akarnik.com\/blog\/wp-json\/wp\/v2\/media\/153"}],"wp:attachment":[{"href":"https:\/\/www.akarnik.com\/blog\/wp-json\/wp\/v2\/media?parent=154"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.akarnik.com\/blog\/wp-json\/wp\/v2\/categories?post=154"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.akarnik.com\/blog\/wp-json\/wp\/v2\/tags?post=154"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}