{"id":2535,"date":"2025-12-01T05:01:12","date_gmt":"2025-12-01T05:01:12","guid":{"rendered":"https:\/\/resources.sozee.ai\/resources\/write-prompts-hyper-realistic-ai-humans\/"},"modified":"2026-09-02T10:47:41","modified_gmt":"2026-09-02T10:47:41","slug":"write-prompts-hyper-realistic-ai-humans","status":"publish","type":"post","link":"https:\/\/www.sozee.ai\/resources\/write-prompts-hyper-realistic-ai-humans\/","title":{"rendered":"How to Write Prompts for Ultra Realistic AI People"},"content":{"rendered":"<p><em>Last updated: August 21, 2026<\/em><\/p>\n<h2 id=\"key-takeaways\">Key Takeaways for Scaling Consistent AI Shoots<\/h2>\n<ul>\n<li>Traditional five-component prompts (Subject, Environment, Lighting &amp; Camera, Pose &amp; Expression, Technical Quality) create strong one-off images but break at scale because of anatomy drift and identity loss.<\/li>\n<li>Sozee&#8217;s Photo Control system replaces each prompt component with a lockable dimension, including Setting, Outfit, Shot Style, Expression, and Object, so you stop rewriting text for every image.<\/li>\n<li>Locking the character at the Cast stage and saving environments as reusable Settings prevents background mutation and keeps the same face, body, and world across an entire shoot.<\/li>\n<li>Photo Shoot converts one approved frame into a locked 10-image set in under five minutes, turning a single setup session into a full week of scheduled content.<\/li>\n<li><a href=\"https:\/\/app.sozee.ai\/sign-up\" target=\"_blank\"><strong>Lock your character and eliminate anatomy drift \u2014 start your first shoot now.<\/strong><\/a><\/li>\n<\/ul>\n<h2>Step 1: Defining the Subject with Sozee Setting<\/h2>\n<p>A traditional subject prompt specifies demographics, physical features, and skin characteristics in a single sentence: <em>&#8220;28-year-old South Korean woman, oval face, high cheekbones, natural makeup, visible skin pores, subtle facial asymmetry, fine peach fuzz.&#8221;<\/em> This language attempts to override the model&#8217;s default tendency toward retouched stock-photography averages.<\/p>\n<h3>Skin Texture and Imperfections in Plain Language<\/h3>\n<p>Realistic skin comes from observable language rather than aspirational language. <a href=\"https:\/\/aicraft.academy\/resources\/realistic-ai-skin-texture\" target=\"_blank\" rel=\"noindex nofollow\">Terms like &#8220;flawless,&#8221; &#8220;perfect,&#8221; and &#8220;porcelain&#8221; push results toward cosmetic retouching<\/a>, while phrases such as &#8220;fine texture,&#8221; &#8220;soft tonal variation,&#8221; &#8220;subtle under-eye detail,&#8221; &#8220;natural lip lines,&#8221; and &#8220;highlights that follow the light source&#8221; produce skin that reads as photographed rather than rendered. <a href=\"https:\/\/imagera.ai\/blog\/best-prompts-realistic-ai-images-2026\" target=\"_blank\" rel=\"noindex nofollow\">Effective imperfection keywords include visible skin pores, natural subsurface scattering, subtle facial asymmetry, fine peach fuzz, and flyaway hairs.<\/a><\/p>\n<p>Sozee eliminates this entire rewriting burden. In Sozee, the Setting control replaces this entire block. The character&#8217;s likeness, including face shape, skin tone, asymmetries, and identifying features, is locked at the Cast stage instead of being re-described in every prompt. The Setting dimension then places that locked subject into a defined environment while identity stays untouched. There is no imperfection block to rewrite because the face is already anchored.<\/p>\n<blockquote>\n<p><strong>Common Pitfall: Anatomy Drift and Plastic Skin<\/strong><\/p>\n<ul>\n<li>Anatomy drift occurs because <a href=\"https:\/\/flick.art\/blog\/img2img-consistent-character\" target=\"_blank\" rel=\"noindex nofollow\">AI diffusion models start each generation from new random static and match prompts to generalized versions of characters seen across millions of training images<\/a>. The same subject prompt therefore produces a different face in each session.<\/li>\n<li>Plastic skin often comes from lighting direction problems. <a href=\"https:\/\/aicraft.academy\/resources\/realistic-ai-skin-texture\" target=\"_blank\" rel=\"noindex nofollow\">Naming the key-light direction and softness while keeping specular highlights localized<\/a>, instead of spread unnaturally across the face, removes the waxy appearance.<\/li>\n<\/ul>\n<h2>Step 2: Locking the Environment as a Sozee Setting<\/h2>\n<p>A traditional environment prompt layers location, time of day, and atmospheric detail: <em>&#8220;minimalist Tokyo apartment, late afternoon, warm light catching dust particles in the air, wet pavement visible through floor-to-ceiling windows.&#8221;<\/em> <a href=\"https:\/\/elements.envato.com\/learn\/prompts-for-realistic-ai-images\" target=\"_blank\" rel=\"noindex nofollow\">Specifying light interaction with surfaces, such as &#8220;warm light catching dust particles in the air,&#8221; produces physically accurate light behavior<\/a> that generic location terms cannot achieve.<\/p>\n<h3>Negative Prompts That Remove Synthetic Artifacts<\/h3>\n<p>Negative prompts for environment work remove the artifacts that signal synthetic generation: <em>&#8220;no watermark, no oversaturated colors, no lens distortion, no floating objects, no inconsistent shadows, no background repetition.&#8221;<\/em> Adding environmental imperfections to positive prompts, such as <a href=\"https:\/\/miraflow.ai\/blog\/how-to-make-ai-images-look-like-real-photos-prompt-tricks\" target=\"_blank\" rel=\"noindex nofollow\">steam rising from a mug, crumbs on counters, dust particles in light beams<\/a>, adds lived-in texture that makes scenes feel captured rather than rendered.<\/p>\n<p>In Sozee, the Setting control stores a reusable environment built from up to four reference photos. The room is read as a whole, so it stays the same room across every image in the set. Background mutation, which is the most common failure mode when scaling prompt-based workflows, disappears because the environment becomes an asset instead of a re-described string.<\/p>\n<blockquote>\n<p><strong>Common Pitfall: Background Mutation<\/strong><\/p>\n<ul>\n<li>Re-prompting an environment from text produces a statistically similar but never identical background, which breaks visual continuity across a content set.<\/li>\n<li>Saving the environment as a Sozee Setting locks the space permanently, so every image in a shoot shares the same room without re-description.<\/li>\n<\/ul>\n<h2>Step 3: Turning Lighting &amp; Camera into a Shot Style<\/h2>\n<p>Camera and lens specification is <a href=\"https:\/\/imagera.ai\/blog\/best-prompts-realistic-ai-images-2026\" target=\"_blank\" rel=\"noindex nofollow\">the single highest-leverage addition to any prompt for realistic AI images<\/a>. A production-grade camera prompt reads: <em>&#8220;shot on Canon EOS R5, 85mm f\/1.8, single large octabox softbox at 45 degrees camera left, catchlights in eyes, Kodak Portra 400 emulation, natural film grain at ISO 800.&#8221;<\/em><\/p>\n<h3>Camera Lens Prompts That Shape Portraits<\/h3>\n<p><a href=\"https:\/\/miraflow.ai\/blog\/how-to-make-ai-images-look-like-real-photos-prompt-tricks\" target=\"_blank\" rel=\"noindex nofollow\">Specifying a camera body, lens type, and focal length applies correct optical characteristics including depth of field and bokeh<\/a>, which produces more photorealistic results than generic subject descriptions. <a href=\"https:\/\/imagera.ai\/blog\/best-prompts-realistic-ai-images-2026\" target=\"_blank\" rel=\"noindex nofollow\">Using &#8220;85mm f\/1.8&#8221; produces classic portrait compression and creamy background blur<\/a>, while <a href=\"https:\/\/imagera.ai\/blog\/best-prompts-realistic-ai-images-2026\" target=\"_blank\" rel=\"noindex nofollow\">Kodak Portra 400 film stock emulation produces warm skin tones, organic grain, and lifted shadows.<\/a> Adding <a href=\"https:\/\/miraflow.ai\/blog\/how-to-make-ai-images-look-like-real-photos-prompt-tricks\" target=\"_blank\" rel=\"noindex nofollow\">subtle optical flaws such as chromatic aberration at high-contrast edges, gentle vignetting, and lens flare<\/a> signals real-camera capture and prevents the artificial plastic look.<\/p>\n<p>In Sozee, the Shot Style control encodes framing, focal length character, lighting mood, and film treatment as a selectable dimension. Creators choose a shot style once and apply it across an entire set instead of rewriting camera language for each image.<\/p>\n<figure style=\"text-align: center;\"><a href=\"https:\/\/app.sozee.ai\/sign-up\" target=\"_blank\"><img src=\"https:\/\/cdn.aigrowthmarketer.co\/1762997925636-7453a7a8b2ad.png\" alt=\"Sozee AI Platform\" style=\"max-height: 500px;\" loading=\"lazy\" decoding=\"async\"><\/a><figcaption><em>Sozee AI Platform<\/em><\/figcaption><\/figure>\n<blockquote>\n<p><strong>Common Pitfall: Flat or Plastic Results<\/strong><\/p>\n<ul>\n<li><a href=\"https:\/\/elements.envato.com\/learn\/prompts-for-realistic-ai-images\" target=\"_blank\" rel=\"noindex nofollow\">Vague quality modifiers such as &#8220;8K,&#8221; &#8220;ultra-realistic,&#8221; and &#8220;high quality&#8221; have no measurable impact on photorealism<\/a>. Specific lens and light direction details drive realistic output instead.<\/li>\n<li><a href=\"https:\/\/aicraft.academy\/resources\/realistic-ai-skin-texture\" target=\"_blank\" rel=\"noindex nofollow\">Strong frontal beauty light erases facial structure<\/a>. Side lighting and backlighting create depth and reveal surface detail that reads as photographic.<\/li>\n<\/ul>\n<h2>Step 4: Directing Pose &amp; Expression with Sozee Expression<\/h2>\n<p>A traditional pose and expression prompt specifies body language and micro-gesture: <em>&#8220;young woman mid-laugh, hand raised near mouth, slight head tilt, shoulders relaxed, weight shifted to left hip.&#8221;<\/em> <a href=\"https:\/\/miraflow.ai\/blog\/how-to-make-ai-images-look-like-real-photos-prompt-tricks\" target=\"_blank\" rel=\"noindex nofollow\">Prompting subjects mid-action or mid-gesture rather than in static poses produces more authentic, less artificial expressions and body language.<\/a><\/p>\n<p>In Sozee, the Expression control replaces this block entirely. Creators select or describe the emotional register, such as candid, confident, playful, or direct, and the system applies it to the locked character. Identity drift no longer appears because expression language no longer mixes into the subject description.<\/p>\n<blockquote>\n<p><strong>Common Pitfall: Stiff or Inconsistent Expressions<\/strong><\/p>\n<ul>\n<li>Static pose language such as &#8220;standing, facing camera, smiling&#8221; defaults to the model&#8217;s most averaged interpretation of those terms, which produces expressions that read as posed rather than captured.<\/li>\n<li>Mixing expression language into a subject prompt can overwrite identity details and push the face toward whatever demographic the model associates with that emotional state.<\/li>\n<\/ul>\n<h2>Step 5: Managing Technical Quality with Sozee Object<\/h2>\n<p>A traditional technical quality block adds props, accessories, and scene anchors alongside quality flags: <em>&#8220;holding a ceramic latte cup, leather tote bag on left shoulder, 4K resolution, no CGI artifacts, no oversaturation, no plastic skin.&#8221;<\/em> <a href=\"https:\/\/elements.envato.com\/learn\/prompts-for-realistic-ai-images\" target=\"_blank\" rel=\"noindex nofollow\">Texture and imperfection terms such as material wear, film grain, and photographic noise help break the too-perfect default that makes AI images look synthetic.<\/a><\/p>\n<p>In Sozee, the Object control handles props, up to four per set, as reusable library assets. A sponsor&#8217;s product, a branded accessory, or a scene prop drops into the Object slot and appears consistently across every image in the shoot. Output resolution up to 4K is set once in the output control panel instead of being appended to every prompt.<\/p>\n<blockquote>\n<p><strong>Common Pitfall: Oversaturated or CGI Artifacts<\/strong><\/p>\n<ul>\n<li>Appending &#8220;4K, ultra-detailed, masterpiece&#8221; to a prompt does not improve technical quality. It signals to the model to prioritize sharpness over photographic realism and often produces the CGI look creators are trying to avoid.<\/li>\n<li>Setting resolution and aspect ratio as output parameters, separate from the creative prompt, keeps the generative model focused on realism rather than technical maximalism.<\/li>\n<\/ul>\n<p><a href=\"https:\/\/app.sozee.ai\/sign-up\" target=\"_blank\"><strong>Stop appending quality flags to every prompt \u2014 lock your technical settings once and reuse them across every shoot.<\/strong><\/a><\/p>\n<h2>Locking Likeness Across an Entire Shoot<\/h2>\n<p>The five-component prompt formula produces one good image. Photo Shoot produces a locked, coherent set of up to ten from that single approved frame. Identity, outfit, and environment stay fixed, while angle, pose, and expression move. The result is a month of content from one setup session.<\/p>\n<figure style=\"text-align: center;\"><a href=\"https:\/\/app.sozee.ai\/sign-up\" target=\"_blank\"><img src=\"https:\/\/sozee.ai\/wp-content\/uploads\/2025\/11\/Sozee-60-Seconds-To-Generate-Content-White.gif\" alt=\"GIF of Sozee Platform Generating Images Based On Inputs From Creator on a White Background\" style=\"max-height: 500px;\" loading=\"lazy\" decoding=\"async\"><\/a><figcaption><em>GIF of Sozee Platform Generating Images Based On Inputs From Creator on a White Background<\/em><\/figcaption><\/figure>\n<p>This production advantage matters because the market is moving toward persistent character operations at scale. <a href=\"https:\/\/futuremarketinsights.com\/reports\/virtual-influencer-market\" target=\"_blank\" rel=\"noindex nofollow\">The virtual influencer market is projected to reach USD 13.2 billion in 2026, growing at a 41.5% CAGR<\/a>, driven by demand for persistent character operations where brands reuse approved identity assets across recurring campaigns. <a href=\"https:\/\/futuremarketinsights.com\/reports\/virtual-influencer-market\" target=\"_blank\" rel=\"noindex nofollow\">Human avatars are projected to represent 68.0% of type demand in 2026<\/a>, reflecting the need for realistic AI-generated personas with stable faces that support recurring branded campaigns. The production bottleneck is not demand. The bottleneck is the absence of a repeatable system for locking likeness at scale.<\/p>\n<p><a href=\"https:\/\/elements.envato.com\/learn\/trends-ai-generated-images-photography\" target=\"_blank\" rel=\"noindex nofollow\">In 2026, reference-based workflows that preserve faces, body proportions, and stylistic details with enough fidelity to support campaigns and serial visual content<\/a> represent the direction the entire industry is moving. Sozee&#8217;s Photo Shoot delivers that workflow inside the generation step instead of bolting it on afterward.<\/p>\n<p>Every Setting, Outfit, and Object built in one shoot becomes a reusable asset for the next. This creates a compounding efficiency effect because the second shoot is faster than the first when you reuse established assets, and the tenth is faster still. The practical impact shows up in concrete success metrics: one approved frame becomes a locked 10-image set in under five minutes, and a week of scheduled posts requires zero re-prompting.<\/p>\n<h2>Advanced Workflow: Using the Agent to Configure Shoots<\/h2>\n<p>Creators who prefer not to configure five dimensions manually can hand the setup to Sozee&#8217;s Agent. The Agent takes a half-formed idea such as &#8220;I need a lifestyle set for a skincare sponsor, outdoor, warm tones, three looks&#8221; and interviews the creator into a finished configuration, asking only about the gaps.<\/p>\n<p>The Agent first resolves which character is being shot, then walks through the missing context, including Setting, Outfit, Shot Style, Expression, Object, and output specifications. Every step offers three exits: pick from the existing library, generate a new asset on the spot, or let the Agent decide. When the conversation ends, the Agent writes directly into the prompt bar and the Photo Control panel. The shoot then sits one tap from Generate.<\/p>\n<figure style=\"text-align: center;\"><a href=\"https:\/\/app.sozee.ai\/sign-up\" target=\"_blank\"><img src=\"https:\/\/cdn.aigrowthmarketer.co\/1762997859947-4a2e298c7c02.png\" alt=\"Creator Onboarding For Sozee AI\" style=\"max-height: 500px;\" loading=\"lazy\" decoding=\"async\"><\/a><figcaption><em>Creator Onboarding<\/em><\/figcaption><\/figure>\n<p>This behavior reflects the broader 2026 shift in AI systems toward <a href=\"https:\/\/dev.classmethod.jp\/en\/articles\/talked-about-the-recent-prompting-kr\" target=\"_blank\" rel=\"noindex nofollow\">context engineering over prompt engineering, where structure, format, and provided context matter more than specific wording or weighted phrases.<\/a> The Agent encodes that structure so creators never have to manage it manually.<\/p>\n<h2>Frequently Asked Questions<\/h2>\n<h3>How do you maintain consistent AI character generation across multiple images?<\/h3>\n<p>Consistent AI character generation requires locking the character&#8217;s identity before any scene variation begins. The anatomy drift problem described in Step 1 appears because traditional prompts cannot anchor identity across sessions. The reliable solution is to anchor identity in a fixed reference, either a trained likeness from uploaded photos or a generated character with locked parameters, and apply that anchor to every new image rather than re-describing the character in each prompt. Sozee handles this at the Cast stage, where the face, body proportions, and identifying features are locked once, and Photo Control then varies Setting, Outfit, Shot Style, Expression, and Object without touching identity. Photo Shoot extends this by building a coherent set of up to ten images from one approved frame, with identity, outfit, and environment held constant across the entire set.<\/p>\n<h3>What are the best negative prompts for realistic humans in 2026?<\/h3>\n<p>Effective negative prompts for realistic humans in 2026 target the specific artifacts that signal synthetic generation rather than applying generic quality flags. A production-grade negative prompt removes watermarks, oversaturated colors, lens distortion, floating or disconnected objects, inconsistent shadows, background repetition, plastic or waxy skin, CGI sheen, symmetrical facial features, and retouching artifacts. Environment-specific negatives add no repeated textures, no impossible geometry, and no mismatched light sources. The most important principle is specificity, because &#8220;no plastic skin&#8221; is more effective than &#8220;realistic&#8221; when it names the artifact rather than the desired quality. In Sozee&#8217;s workflow, many of these negatives become unnecessary because the system&#8217;s output controls and locked likeness remove the underlying causes of those artifacts at the generation level.<\/p>\n<h3>How do camera lens prompts improve AI portraits?<\/h3>\n<p>Camera lens prompts improve AI portraits by instructing the model to simulate the optical behavior of a real lens instead of defaulting to an idealized, optically perfect render. Specifying a focal length such as 85mm triggers portrait compression and background separation, while specifying an aperture such as f\/1.8 produces shallow depth of field and bokeh. Adding a camera body like Canon EOS R5 or Fujifilm GFX 100S signals full-frame sensor characteristics including high dynamic range and natural noise behavior. Film stock references such as Kodak Portra 400 apply warm skin-flattering color science with organic grain. Subtle optical flaws, including chromatic aberration at high-contrast edges, gentle vignetting, and lens flare, complete the effect by mimicking the imperfections that distinguish a real photograph from a render. In Sozee, Shot Style encodes these decisions as a selectable dimension, so the optical character of a shoot is set once and applied consistently across every image in the set.<\/p>\n<h3>How do you add natural skin texture and imperfections without prompt engineering?<\/h3>\n<p>Natural skin texture in AI portraits, as discussed in Step 1, comes from replacing aspirational language with observable physical description. In Sozee, this manual engineering becomes unnecessary because skin texture is a property of the locked character established at the Cast stage rather than a block of language re-entered with every prompt. The character&#8217;s observable skin qualities, including pore visibility, asymmetry, and tonal variation, carry through every generation automatically. This removes the need for imperfection engineering entirely and keeps skin behavior consistent across shoots.<\/p>\n<h3>Can you scale a single approved frame into a full week of content?<\/h3>\n<p>Sozee&#8217;s Photo Shoot feature takes one approved image and builds a locked, coherent set of up to ten around it. Identity, outfit, and environment remain fixed, while angle, pose, and expression vary across the set. Each image in the set becomes a distinct, usable asset rather than a minor variation of the same frame. Combined with the Scheduler, which connects Instagram, TikTok, X, Facebook, Reddit, and Fanvue per character, a single Photo Shoot session produces enough assets to populate a full week of posts across multiple platforms without re-prompting, re-casting, or re-building the environment. For micro-influencers managing sponsorship deliverables, the Object slot accepts the sponsor&#8217;s product directly, so a full campaign set with multiple settings, looks, and expressions featuring the branded item can be delivered in an afternoon instead of a full shoot day.<\/p>\n<h2>Conclusion<\/h2>\n<p>The five-component prompt formula, covering Subject, Environment, Lighting &amp; Camera, Pose &amp; Expression, and Technical Quality, works as a starting point for a single image but not as a production system. Every component requires re-engineering each session, and none of it prevents anatomy drift, background mutation, or identity loss when you scale to a weekly content calendar.<\/p>\n<p>Sozee&#8217;s Photo Control system replaces that fragile stack with five locked dimensions. Setting locks the environment. Outfit locks the look. Shot Style locks the optical character. Expression locks the emotional register. Object anchors the props. Underneath all five dimensions, likeness stays locked, which means the same face and the same body appear in every frame, every set, and every week. Photo Shoot compounds the output, and the Agent removes the setup friction entirely.<\/p>\n<p>The virtual influencer market growth discussed earlier shows that platform demand for consistent, brand-ready content is not slowing. Creators who build a repeatable production system now will outpace those still re-rolling prompts next quarter.<\/p>\n<p><a href=\"https:\/\/app.sozee.ai\/sign-up\" target=\"_blank\"><strong>Build your repeatable production system \u2014 sign up for Sozee and run your first locked shoot in minutes.<\/strong><\/a><\/p>\n<section data-read-next=\"true\">\n<h2>Read Next<\/h2>\n<ul>\n<li><a href=\"https:\/\/sozee.ai\/resources\/get-realistic-human-features-ai\" target=\"_blank\">How to Get Realistic Human Features in AI Images: 6 Steps<\/a><\/li>\n<li><a href=\"https:\/\/sozee.ai\/resources\/create-photorealistic-ai-images-creators\" target=\"_blank\">How to Create Photorealistic AI Images: A Creator&#8217;s Guide<\/a><\/li>\n<li><a href=\"https:\/\/sozee.ai\/resources\/best-prompts-realistic-ai-photos\" target=\"_blank\">Best Prompts for Realistic AI Generated Photos of Creators<\/a><\/li>\n<li><a href=\"https:\/\/sozee.ai\/resources\/prompt-customization-hyper-realistic-ai\" target=\"_blank\">Master Prompt-Based Customization for Hyper-Realistic AI<\/a><\/li>\n<li><a href=\"https:\/\/sozee.ai\/resources\/generate-realistic-ai-faces-guide\" target=\"_blank\">How to Generate Realistic AI Faces in 2026<\/a><\/li>\n<\/ul>\n<\/section>\n","protected":false},"excerpt":{"rendered":"<p>Learn the 5-step prompt formula for ultra realistic AI people. Sozee locks likeness, skin texture &#038; lighting across every shot. Start today.<\/p>\n","protected":false},"author":2,"featured_media":28999,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2,13],"tags":[45],"class_list":["post-2535","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-photos","category-prompts","tag-prompts-tag"],"_links":{"self":[{"href":"https:\/\/www.sozee.ai\/resources\/wp-json\/wp\/v2\/posts\/2535","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.sozee.ai\/resources\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.sozee.ai\/resources\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.sozee.ai\/resources\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.sozee.ai\/resources\/wp-json\/wp\/v2\/comments?post=2535"}],"version-history":[{"count":3,"href":"https:\/\/www.sozee.ai\/resources\/wp-json\/wp\/v2\/posts\/2535\/revisions"}],"predecessor-version":[{"id":40799,"href":"https:\/\/www.sozee.ai\/resources\/wp-json\/wp\/v2\/posts\/2535\/revisions\/40799"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.sozee.ai\/resources\/wp-json\/wp\/v2\/media\/28999"}],"wp:attachment":[{"href":"https:\/\/www.sozee.ai\/resources\/wp-json\/wp\/v2\/media?parent=2535"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.sozee.ai\/resources\/wp-json\/wp\/v2\/categories?post=2535"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.sozee.ai\/resources\/wp-json\/wp\/v2\/tags?post=2535"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}