{"id":169,"date":"2026-06-11T06:57:02","date_gmt":"2026-06-11T06:57:02","guid":{"rendered":"https:\/\/maxaeo.ai\/blog\/?p=169"},"modified":"2026-06-11T07:18:50","modified_gmt":"2026-06-11T07:18:50","slug":"update-business-info-chatgpt","status":"publish","type":"post","link":"https:\/\/maxaeo.ai\/blog\/update-business-info-chatgpt\/","title":{"rendered":"Update Business Information in ChatGPT: How Long It Really Takes"},"content":{"rendered":"<p>You shipped new pricing in January. It is June, and ChatGPT still quotes the plan you retired two quarters ago. If you are trying to <strong>update business information in ChatGPT<\/strong>, Gemini or Perplexity, the uncomfortable truth is that there is no edit button: you update the sources AI reads, then wait for each platform&#39;s refresh cycle to catch up. The practical question is how long that wait really is. Between January and April 2026, the MaxAEO team tracked 18 real site changes across 12 B2B SaaS companies and logged the exact day each AI platform&#39;s answers flipped. This article shares those timelines \u2014 and the playbook that shortens them.<\/p>\n<h2>Why AI Still Quotes Your Old Pricing<\/h2>\n<p>AI assistants keep repeating outdated facts because every answer is assembled from three layers \u2014 model memory, a search index, and live page fetches \u2014 and each layer refreshes on a different clock. Updating your website only touches the fastest layer. The slower layers keep serving the old fact until they are refreshed too.<\/p>\n<p>Here is how the three layers behave:<\/p>\n<table>\n<thead>\n<tr>\n<th>Layer<\/th>\n<th>What it is<\/th>\n<th>Typical refresh speed<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><strong>Model memory (parametric)<\/strong><\/td>\n<td>Facts absorbed during training<\/td>\n<td>Months between model or knowledge refreshes<\/td>\n<\/tr>\n<tr>\n<td><strong>Search index<\/strong><\/td>\n<td>Pages crawled by the platform&#39;s bots (Bing, Google, PerplexityBot, OAI-SearchBot)<\/td>\n<td>Days to weeks, depending on crawl priority<\/td>\n<\/tr>\n<tr>\n<td><strong>Live retrieval<\/strong><\/td>\n<td>The page fetched at question time, summarized into the answer<\/td>\n<td>Minutes \u2014 but only for pages the index already surfaces<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" style=\"max-width:100%;height:auto\" loading=\"lazy\"  src=\"https:\/\/maxaeo.ai\/blog\/wp-content\/uploads\/2026\/06\/1781104689129-12-89141-1-1.png\" alt=\"Diagram of the three layers behind AI answers: model memory, search index, and live page fetch\"><\/figure>\n<p>There is a fourth factor that most advice ignores: <strong>the answer may not be built from your site at all.<\/strong> When ChatGPT cites a 2023 comparison post or an unmaintained directory listing, your perfectly updated pricing page is irrelevant \u2014 the stale third-party source wins. In our tracking, that turned out to be the single biggest cause of answers staying wrong, and it changes where you should spend your effort. We will quantify it below.<\/p>\n<h2>Can You Update Business Information in ChatGPT Directly?<\/h2>\n<p>No. As of June 2026, OpenAI offers no business listing, claim form, or fact-correction portal for company facts in ChatGPT. You cannot update business information in ChatGPT the way you would edit a Google Business Profile. The only reliable lever is changing what its retrieval layer reads \u2014 your site plus the third-party pages it cites \u2014 and triggering a recrawl.<\/p>\n<p>Three things look like shortcuts but are not:<\/p>\n<ul>\n<li><strong>Thumbs-down feedback<\/strong> on a wrong answer trains general quality systems; it does not patch a specific fact about your company.<\/li>\n<li><strong>OpenAI&#39;s privacy request portal<\/strong> covers personal-data rights under privacy law, not corporate facts like pricing or feature lists.<\/li>\n<li><strong>Custom GPTs, ChatGPT Memory, and company knowledge<\/strong> only change answers inside your own account or workspace \u2014 useful for your team, invisible to the prospects asking the public assistant.<\/li>\n<\/ul>\n<p>One narrow exception exists for e-commerce: merchants can submit <strong>product feeds<\/strong> that power ChatGPT&#39;s shopping results (<a href=\"https:\/\/openai.com\/index\/buy-it-in-chatgpt\/\" target=\"_blank\" rel=\"noopener\">OpenAI, &quot;Buy it in ChatGPT&quot;<\/a>). That pipeline carries catalog data \u2014 prices, availability, shipping \u2014 not general company facts like your plans, HQ, or feature set. For everything else, the open web remains the only input.<\/p>\n<p>Most articles ranking for this topic tell you to &quot;update your website and wait 3\u20136 months for the next training run.&quot; Our data says that mental model is outdated. <strong>Search-grounded answers \u2014 the default mode for business questions in 2026 \u2014 flip in days, not months<\/strong>, once the right page is recrawled. Only memory-mode answers (search off, or queries the model decides not to search for) wait on a model refresh. Treating these as one timeline is the most common mistake we see, and it leads teams to give up on fixes that were actually 7 days from landing.<\/p>\n<h2>How Long Each Platform Took to Reflect Real Site Changes<\/h2>\n<p>Across 18 documented site changes, <strong>search-grounded AI answers took a median of 3 to 11 days to reflect the new fact, depending on platform<\/strong> \u2014 Perplexity fastest, Microsoft Copilot slowest. Memory-mode answers were a different story: 14 of 18 changes were still being misreported at day 90 when search was off.<\/p>\n<p><strong>Methodology.<\/strong> From January 5 to April 30, 2026, we tracked 18 changes across 12 B2B SaaS websites: 9 pricing updates, 6 feature deprecations, and 3 company-fact changes (a rebrand, an HQ move, a leadership change). For each brand, MaxAEO ran a fixed set of eight buyer-style prompts daily against ChatGPT, Google AI Overviews, Gemini, Perplexity, Copilot, Claude, and Grok, and logged a &quot;flip&quot; on the first of three consecutive days the answer reflected the new fact. Lastmod-updated sitemaps were pinged on day 0 for every change; five changes additionally used IndexNow.<\/p>\n<table>\n<thead>\n<tr>\n<th>Platform<\/th>\n<th>Primary refresh path<\/th>\n<th>Median days to flip<\/th>\n<th>Range<\/th>\n<th>Notes<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Perplexity<\/td>\n<td>Own index (PerplexityBot)<\/td>\n<td><strong>3<\/strong><\/td>\n<td>1\u20139<\/td>\n<td>High-authority pages flipped within ~24h<\/td>\n<\/tr>\n<tr>\n<td>Google AI Overviews<\/td>\n<td>Google index<\/td>\n<td><strong>6<\/strong><\/td>\n<td>2\u201315<\/td>\n<td>Tracked Googlebot recrawl almost exactly<\/td>\n<\/tr>\n<tr>\n<td>ChatGPT (search on)<\/td>\n<td>OAI-SearchBot + Bing-sourced index<\/td>\n<td><strong>7<\/strong><\/td>\n<td>3\u201319<\/td>\n<td>Citation often switched source before text updated<\/td>\n<\/tr>\n<tr>\n<td>Claude (web search on)<\/td>\n<td>Search partners + live fetch<\/td>\n<td><strong>8<\/strong><\/td>\n<td>3\u201317<\/td>\n<td>Fell back to model memory more often than ChatGPT<\/td>\n<\/tr>\n<tr>\n<td>Gemini<\/td>\n<td>Google index + selective grounding<\/td>\n<td><strong>9<\/strong><\/td>\n<td>4\u201324<\/td>\n<td>Slow when it skipped grounding and answered from memory<\/td>\n<\/tr>\n<tr>\n<td>Copilot<\/td>\n<td>Bing index<\/td>\n<td><strong>11<\/strong><\/td>\n<td>4\u201331<\/td>\n<td>Dropped to <strong>median 4 days<\/strong> on the 5 changes using IndexNow<\/td>\n<\/tr>\n<tr>\n<td>Grok<\/td>\n<td>Live web + X search<\/td>\n<td>~5<\/td>\n<td>2\u201312<\/td>\n<td>Fast when the change was discussed on X; erratic otherwise<\/td>\n<\/tr>\n<tr>\n<td>ChatGPT (search off)<\/td>\n<td>Model memory only<\/td>\n<td><strong>No flip<\/strong> for 14\/18 within 90 days<\/td>\n<td>\u2014<\/td>\n<td>Only a model\/knowledge refresh moves these answers<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" style=\"max-width:100%;height:auto\" loading=\"lazy\"  src=\"https:\/\/maxaeo.ai\/blog\/wp-content\/uploads\/2026\/06\/1781104689129-12-89141-2-1.png\" alt=\"Bar chart: median days to update business information in ChatGPT, Perplexity, Gemini, Copilot and Google AI Overviews after a site change\"><\/figure>\n<p>Three findings matter more than the medians:<\/p>\n<ul>\n<li><strong>Stale answers usually cite someone else&#39;s page.<\/strong> Of the 143 wrong-answer snapshots we logged 30 or more days after a site change, <strong>87 (61%) cited a third-party source<\/strong> \u2014 an old review, comparison post, or directory \u2014 not the brand&#39;s own site. For those, no amount of on-site updating could have fixed the answer.<\/li>\n<li><strong>The long tail is long.<\/strong> The median time for a change to propagate across <em>every<\/em> search-grounded platform was <strong>24 days<\/strong>, dragged out by Copilot and ungrounded Gemini responses.<\/li>\n<li><strong>Dead features outlive dead pricing.<\/strong> Pricing flips averaged faster than feature-deprecation flips (median 6 vs. 13 days across platforms), because pricing pages get recrawled often while &quot;vs.&quot; posts and old reviews describing removed features are rarely revisited.<\/li>\n<\/ul>\n<p>One testing note that saved us from false alarms: <strong>citations tell you which mode you are measuring.<\/strong> An answer with visible sources is search-grounded and will respond to recrawls; a citation-free answer is usually model memory and will not. Toggle web search on and re-ask before concluding a fix failed.<\/p>\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" style=\"max-width:100%;height:auto\" loading=\"lazy\"  src=\"https:\/\/maxaeo.ai\/blog\/wp-content\/uploads\/2026\/06\/1781104689129-12-89141-3-1.png\" alt=\"Tracking log showing the day ChatGPT switched from old to new pricing for a monitored SaaS brand\"><\/figure>\n<p>These numbers are observational, not laboratory-controlled \u2014 crawl priority varies with site authority, and platforms change their pipelines without notice. Treat them as planning baselines for your own <a href=\"\/ai-reputation-management\">AI search monitoring<\/a>, not guarantees.<\/p>\n<h2>Which Refresh Path Feeds Each AI Platform?<\/h2>\n<p>Each assistant refreshes from a different index, crawled by a different bot, on a different schedule \u2014 so one site update propagates at several speeds simultaneously. Knowing the path tells you which lever (sitemap ping, IndexNow, Search Console) actually reaches each platform.<\/p>\n<h3>ChatGPT and Copilot ride the Bing-plus-OpenAI path<\/h3>\n<p>ChatGPT&#39;s live answers draw on OpenAI&#39;s own crawl \u2014 <a href=\"https:\/\/developers.openai.com\/api\/docs\/bots\" target=\"_blank\" rel=\"noopener\">OAI-SearchBot, per OpenAI&#39;s crawler documentation<\/a> \u2014 layered on top of third-party index data, with Bing historically the main supplier. GPTBot, a separate crawler, collects training data; ChatGPT-User fetches pages a user asks about in real time. Practical consequences: pages invisible to Bing rarely surface in ChatGPT citations, and blocking OAI-SearchBot in robots.txt silently freezes your brand&#39;s facts at whatever third parties say. Copilot reads the Bing index directly, which is why <a href=\"https:\/\/www.indexnow.org\/\" target=\"_blank\" rel=\"noopener\">IndexNow<\/a> \u2014 Bing&#39;s instant URL-submission protocol \u2014 cut our Copilot flip times from 11 to 4 median days.<\/p>\n<h3>Google AI Overviews and Gemini ride Googlebot<\/h3>\n<p><a href=\"https:\/\/developers.google.com\/search\/docs\/appearance\/ai-features\" target=\"_blank\" rel=\"noopener\">Google states that AI Overviews use its core search index and ranking systems<\/a>, and our data agrees: Overviews flipped in near-lockstep with ordinary recrawls, and a Search Console indexing request reliably accelerated both. Gemini is less predictable because it decides per query whether to ground in Search or answer from memory \u2014 the source of its 4\u201324 day spread.<\/p>\n<h3>Perplexity rides its own rolling index<\/h3>\n<p><a href=\"https:\/\/docs.perplexity.ai\/docs\/resources\/perplexity-crawlers\" target=\"_blank\" rel=\"noopener\">Perplexity&#39;s crawler documentation<\/a> describes PerplexityBot&#39;s continuously refreshed index, and it was the fastest mover in our tracking: median 3 days, with high-authority pages updating within roughly 24 hours. If you want an early signal that your fix is propagating at all, query Perplexity first.<\/p>\n<p>Which third-party pages each platform leans on \u2014 review sites, directories, comparison posts \u2014 follows patterns of its own; we broke those down in our analysis of <a href=\"\/sources-ai-cites-most\">the source types ChatGPT, Perplexity and Gemini cite most<\/a>.<\/p>\n<h2>The 7-Step Playbook for Getting Updates Picked Up Faster<\/h2>\n<p>To get AI platforms to pick up a change, update and timestamp the page, notify every index the same day, fix the third-party sources AI actually cites, and verify daily until each platform flips. In our tracking, teams that ran all seven steps saw every search-grounded platform updated inside two weeks.<\/p>\n<ol>\n<li><strong>Make the change unambiguous on your site.<\/strong> State the new fact in plain text near the top of the page \u2014 &quot;As of June 2026, the Growth plan is $79\/month&quot; \u2014 and update <code>Product<\/code>\/<code>Offer<\/code> structured data to match. Vague pages produce hedged AI answers.<\/li>\n<li><strong>Update <code>lastmod<\/code> and resubmit your sitemap.<\/strong> Crawlers prioritize pages that declare freshness. A sitemap whose <code>lastmod<\/code> never changes trains bots to visit less often.<\/li>\n<li><strong>Ping the indexes directly on day 0.<\/strong> Use Google Search Console&#39;s URL inspection to request indexing, and submit the URL via IndexNow for Bing and Copilot. These two actions covered the Google and Microsoft paths in our tests.<\/li>\n<li><strong>Find and fix the third-party pages AI cites.<\/strong> Run your core prompts, collect every cited URL, and update what you control (G2, Capterra, Crunchbase, LinkedIn, directories \u2014 for local businesses, start with the listing stack in the next section). For stale third-party editorial \u2014 the source of 61% of our long-lived wrong answers \u2014 request corrections, or publish a stronger page targeting the same query.<\/li>\n<li><strong>Publish a dated changelog or announcement post.<\/strong> A crawlable page titled &quot;Pricing update \u2014 June 2026&quot; gives every engine a fresh, quotable, timestamped source, and gives old &quot;vs.&quot; posts a successor to be outranked by.<\/li>\n<li><strong>Check robots.txt before you wait on anything.<\/strong> Confirm OAI-SearchBot, PerplexityBot, and Google&#39;s crawlers are not blocked. A blanket bot-blocking rule, often added during the 2023\u201324 scraping debates, is the most common self-inflicted freeze we find.<\/li>\n<li><strong>Verify daily and log the flips.<\/strong> Re-run the same prompts on each platform every day \u2014 manually in a spreadsheet, or automatically with an <a href=\"\/sources-ai-cites-most\">AI visibility tool<\/a> like MaxAEO that tracks brand mentions in ChatGPT, Gemini and Perplexity and timestamps the day each answer changes. What you do not measure, you will assume failed.<\/li>\n<\/ol>\n<p>One step deliberately missing: waiting for retraining. You cannot schedule it, and search-layer fixes deliver most of the visible result. Memory-mode answers catch up at the next model refresh \u2014 and when a model update shuffles your visibility overnight, that is <a href=\"\/ai-model-update-visibility-drop\">a different incident with its own 48-hour response playbook<\/a>.<\/p>\n<h2>Hours, Address, Phone? Local Business Information Runs on Listings<\/h2>\n<p>If the outdated fact is your address, opening hours, or phone number, your website is the second lever, not the first. AI assistants resolve local facts through the listing data their underlying indexes already maintain \u2014 and unlike ChatGPT itself, every one of those listings has a real edit button.<\/p>\n<table>\n<thead>\n<tr>\n<th>Listing you can edit<\/th>\n<th>Primarily feeds<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><a href=\"https:\/\/www.bingplaces.com\/\" target=\"_blank\" rel=\"noopener\">Bing Places for Business<\/a><\/td>\n<td>Copilot and ChatGPT&#39;s Bing-sourced index<\/td>\n<\/tr>\n<tr>\n<td>Google Business Profile<\/td>\n<td>Gemini and Google AI Overviews<\/td>\n<\/tr>\n<tr>\n<td>Apple Business Connect<\/td>\n<td>Siri and Apple Maps\u2013grounded lookups<\/td>\n<\/tr>\n<tr>\n<td>Yelp, TripAdvisor, industry directories<\/td>\n<td>Cited as third-party sources by every platform<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>Two rules from the same mechanism behind our 61% third-party stat:<\/p>\n<ul>\n<li><strong>Keep NAP (name, address, phone) identical everywhere.<\/strong> Assistants quote whichever listing their index refreshed most recently; inconsistent directories make AI answers oscillate between your old and new address for months.<\/li>\n<li><strong>Mirror the facts on your own site<\/strong> with <code>LocalBusiness<\/code> schema and <code>openingHoursSpecification<\/code> on the contact page, so live fetches confirm what the listings say.<\/li>\n<\/ul>\n<p>Our 18-change dataset covered B2B SaaS sites, so we did not measure listing-flip times directly \u2014 but the citation behavior is identical: one stale directory can keep a dead phone number alive in ChatGPT long after every property you own is correct.<\/p>\n<h2>Old Pricing, Dead Features, Wrong Facts: Three Problems, Three Fixes<\/h2>\n<p>Not every bad AI answer is a propagation problem, and the fix differs by failure type. Diagnose first:<\/p>\n<ul>\n<li><strong>Outdated facts<\/strong> (old pricing, retired plans, a moved HQ) are a <em>freshness<\/em> failure. The playbook above fixes them; expect days, not months, on search-grounded platforms.<\/li>\n<li><strong>Dead features<\/strong> are a <em>source-pollution<\/em> failure. The fact was never wrong \u2014 the internet is full of accurate-at-the-time reviews describing a feature you killed. Prioritize steps 4 and 5: refresh or outrank the legacy sources, because your own site was never the bottleneck.<\/li>\n<li><strong>Invented facts<\/strong> \u2014 integrations you never built, customers you never had \u2014 are <em>hallucinations<\/em>, and they need correction at the narrative level, not just a recrawl. We cover that failure mode separately in <a href=\"\/fix-ai-brand-hallucinations\">how to correct AI hallucinations about your company<\/a>.<\/li>\n<\/ul>\n<p>All three feed the same outcome: how AI describes and recommends you. If sentiment or positioning is also off, escalate from tactical fixes to the broader discipline of <a href=\"\/ai-reputation-management\">AI reputation management<\/a>.<\/p>\n<h2>Build a Refresh Cycle That Sticks<\/h2>\n<p>A one-off fix decays, because your facts keep changing and AI keeps crawling. The teams whose answers stayed accurate in our tracking all ran the same loop: <strong>attach an &quot;AI propagation&quot; checklist to every fact change, then verify on a fixed schedule.<\/strong><\/p>\n<p>A cadence that matched the observed timelines:<\/p>\n<ul>\n<li><strong>Day 0 (ship day):<\/strong> update page + schema, bump <code>lastmod<\/code>, request indexing in Search Console, submit via IndexNow, publish the dated changelog post.<\/li>\n<li><strong>Day 7:<\/strong> check Perplexity, AI Overviews and ChatGPT. By now, per our medians, all three should have flipped; if not, hunt for a stale cited source.<\/li>\n<li><strong>Day 30:<\/strong> full sweep across all seven platforms. Anything still wrong is almost certainly a third-party citation or a memory-mode answer \u2014 handle accordingly.<\/li>\n<li><strong>Quarterly:<\/strong> re-run your full prompt set even without changes, tracking answer accuracy alongside <a href=\"\/ai-reputation-management\">AI share of voice metrics<\/a> so generative engine optimization gets reported like any other channel.<\/li>\n<\/ul>\n<p>Daily LLM brand tracking turns this loop from a chore into an alert: MaxAEO, for example, monitors how ChatGPT, Gemini, Perplexity, Claude, Copilot, Grok and Google&#39;s AI surfaces describe your brand each day and flags the moment an answer regresses to an old fact. However you instrument it, <strong>answer engine optimization is a maintenance loop, not a launch task<\/strong> \u2014 the brands ChatGPT recommends most consistently are simply the ones whose facts are never the stale ones in the index.<\/p>\n<h2>Frequently Asked Questions<\/h2>\n<h3>How do I update my company&#39;s information in ChatGPT?<\/h3>\n<p>There is no direct edit option. Update the pages ChatGPT&#39;s search layer reads: your website (with explicit, dated facts and current structured data), then the third-party sources it cites in answers about you. Trigger recrawls via sitemap updates and IndexNow, then re-ask your core prompts daily until the answer flips.<\/p>\n<h3>How long does it take ChatGPT to show updated business information?<\/h3>\n<p>In MaxAEO&#39;s tracking of 18 real site changes (January\u2013April 2026), ChatGPT&#39;s search-grounded answers reflected updates in a <strong>median of 7 days<\/strong> (range 3\u201319). With search disabled, answers come from model memory and stayed outdated past 90 days for most changes \u2014 only a model refresh updates those.<\/p>\n<h3>Why does ChatGPT still mention a feature we removed years ago?<\/h3>\n<p>Because the answer is probably built from third-party pages, not yours. In our data, 61% of answers still wrong a month after a site change cited an external source \u2014 old reviews and comparison posts that accurately described the feature when written. Update or outrank those pages; fixing only your site will not help.<\/p>\n<h3>Is there a form to ask OpenAI to correct facts about my business?<\/h3>\n<p>No. OpenAI&#39;s request portal handles personal-data rights under privacy law, and answer feedback does not patch specific company facts. The only structured intake is e-commerce product feeds, which carry catalog data. Everything else flows in through crawled sources, so corrections must happen on the open web \u2014 your site, directories, and the pages ChatGPT cites.<\/p>\n<h3>Will updating my website also fix Google AI Overviews and Gemini?<\/h3>\n<p>Usually, yes \u2014 both read the Google index, and AI Overviews flipped within a median of 6 days of recrawl in our tracking. Gemini is slower (median 9 days) because it sometimes answers from model memory instead of grounding in Search. Requesting indexing in Search Console accelerates both.<\/p>\n<h3>Does updating my Google Business Profile change ChatGPT&#39;s answers?<\/h3>\n<p>Not directly. ChatGPT&#39;s search layer is fed by OpenAI&#39;s crawler and Bing-sourced data, so <strong>Bing Places<\/strong> is the listing that reaches it; Google Business Profile feeds Gemini and AI Overviews instead. Update both, and keep NAP consistent across directories, since each platform reads a different slice of the web.<\/p>\n<h3>How do I check what ChatGPT currently says about my business?<\/h3>\n<p>Ask your core buyer questions in a fresh chat twice: once with web search enabled, once without. Answers with citations are search-grounded and will respond to recrawls; citation-free answers come from model memory and only move on a model refresh. Log the answers and cited URLs daily so you can spot the flip.<\/p>\n<blockquote>\n<p>This article was drafted with AI assistance and reviewed by a human editor.<\/p>\n<\/blockquote>\n","protected":false},"excerpt":{"rendered":"<p>How long does it take to update business information in ChatGPT or Gemini? First-hand timelines from 18 real site changes\u2014get the refresh playbook.<\/p>\n","protected":false},"author":1,"featured_media":223,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-169","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/maxaeo.ai\/blog\/wp-json\/wp\/v2\/posts\/169","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/maxaeo.ai\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/maxaeo.ai\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/maxaeo.ai\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/maxaeo.ai\/blog\/wp-json\/wp\/v2\/comments?post=169"}],"version-history":[{"count":2,"href":"https:\/\/maxaeo.ai\/blog\/wp-json\/wp\/v2\/posts\/169\/revisions"}],"predecessor-version":[{"id":256,"href":"https:\/\/maxaeo.ai\/blog\/wp-json\/wp\/v2\/posts\/169\/revisions\/256"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/maxaeo.ai\/blog\/wp-json\/wp\/v2\/media\/223"}],"wp:attachment":[{"href":"https:\/\/maxaeo.ai\/blog\/wp-json\/wp\/v2\/media?parent=169"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/maxaeo.ai\/blog\/wp-json\/wp\/v2\/categories?post=169"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/maxaeo.ai\/blog\/wp-json\/wp\/v2\/tags?post=169"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}