{"id":237377,"date":"2026-02-11T08:00:58","date_gmt":"2026-02-11T08:00:58","guid":{"rendered":"https:\/\/osmosys.co\/uk\/?p=237377"},"modified":"2026-02-11T08:01:01","modified_gmt":"2026-02-11T08:01:01","slug":"devops-agentic-ai-enterprise-development","status":"publish","type":"post","link":"https:\/\/osmosys.co\/uk\/devops-agentic-ai-enterprise-development\/","title":{"rendered":"How Agentic AI Changes Enterprise Development: DevOps Beyond ChatGPT"},"content":{"rendered":"<div id=\"bsf_rt_marker\"><\/div>\n<p>Picture two enterprise teams working on the same problem: a legacy app that needs a platform upgrade, security fixes, and a cloud-ready release path.<\/p>\n\n\n\n<p><strong>Team A<\/strong> uses AI like a faster autocomplete. Helpful, but the work still happens in long bursts: someone writes an upgrade plan, someone else makes the changes, then the build breaks, and releases slip.<\/p>\n\n\n\n<p><strong>Team B<\/strong> treats AI like a junior collaborator inside the delivery system. An agent proposes an upgrade plan, applies changes, runs builds\/tests, opens a pull request, and leaves a summary for review\u2014while humans stay responsible for architecture, approvals, and release decisions.<\/p>\n\n\n\n<p>That difference is not \u201cmore AI.\u201d It\u2019s <strong><a href=\"https:\/\/osmosys.co\/blog\/agile-devops-delivery-microsoft-projects\/\">DevOps discipline<\/a><\/strong> applied to a new reality: AI that can take actions, not just answer questions.<\/p>\n\n\n\n<p>Microsoft and GitHub have been moving in this direction with Copilot \u201cagent mode\u201d and coding agents designed to work through issues and pull requests, run modernization steps, and produce reviewable outputs.<\/p>\n\n\n\n<p>This post breaks down what agentic AI is, why it\u2019s a DevOps topic, and how to adopt it in a way that improves delivery without creating a governance mess.<\/p>\n\n\n\n<figure class=\"wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio\"><div class=\"wp-block-embed__wrapper\">\n<iframe title=\"Build agents with knowledge, agentic RAG and Azure AI Search | BRK193\" width=\"1080\" height=\"608\" data-src=\"https:\/\/www.youtube.com\/embed\/lW47o2ss3Yg?feature=oembed\"  allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" class=\"lazyload\" data-load-mode=\"1\"><\/iframe>\n<\/div><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\">What \u201cagentic AI\u201d means (and why DevOps teams should care)<\/h2>\n\n\n\n<p>Most people think \u201cgenerative AI\u201d equals chat: you ask, it answers.<\/p>\n\n\n\n<p><strong>Agentic AI<\/strong> is different. The point isn\u2019t a better paragraph. The point is a system that can:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Work toward a goal over multiple steps<\/li>\n\n\n\n<li>Use tools (repos, CI, pipelines, ticketing)<\/li>\n\n\n\n<li>Create artifacts (PRs, upgrade plans, scripts)<\/li>\n\n\n\n<li>Ask for review when it\u2019s done, like a teammate<\/li>\n<\/ul>\n\n\n\n<p>Microsoft\u2019s own guidance around Copilot-driven modernization describes agents completing modernization tasks in the background, producing PRs and summaries that developers review.<\/p>\n\n\n\n<p>That\u2019s why this lands squarely in <strong>DevOps<\/strong>: once something can change code or infrastructure, you need the same controls you\u2019d apply to any contributor\u2014identity, permissions, review gates, traceability, and release safety.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Where agentic AI shows up in the Microsoft ecosystem today<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">1) GitHub Copilot agents for modernization work<\/h3>\n\n\n\n<p>Microsoft\u2019s .NET team published a step-by-step guide focused on modernizing .NET using GitHub Copilot agent mode: generate an upgrade plan, apply changes, fix build issues, validate tests, and produce a report for review.<\/p>\n\n\n\n<p>There\u2019s also Microsoft Learn guidance describing Copilot coding agents modernizing apps by working through delegated tasks and producing PRs.<\/p>\n\n\n\n<p>Practical takeaway: upgrades and migrations become a <strong>plan \u2192 apply \u2192 validate \u2192 review<\/strong> loop that fits naturally into a PR-based delivery model.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">2) \u201cControl plane\u201d thinking for agents<\/h3>\n\n\n\n<p>At Ignite, Microsoft talked about managing and securing agents with centralized control concepts (positioned as a way to run human-led, agent-operated work safely).<\/p>\n\n\n\n<p>You don\u2019t need the marketing language to take the lesson: if agents multiply, <strong>governance must scale<\/strong>.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">3) Data and privacy boundaries still matter<\/h3>\n\n\n\n<p>Microsoft\u2019s guidance for Copilot in Microsoft 365 emphasizes keeping prompts, retrieved data, and outputs within the service boundary and processing via Azure OpenAI (not consumer OpenAI services).<br>For GitHub Copilot specifically, GitHub documents governance-oriented positioning for Copilot Business and explains Copilot\u2019s data processing at a high level.<\/p>\n\n\n\n<p>Practical takeaway: treat \u201cwhat data the agent can see\u201d as an architectural decision, not a default.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">The DevOps shift: AI becomes a contributor, not a tool<\/h2>\n\n\n\n<p>If an agent can open PRs or propose infrastructure changes, DevOps teams should treat it like any other non-human actor:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>A distinct identity<\/li>\n\n\n\n<li>Least-privilege access<\/li>\n\n\n\n<li>Audit trails<\/li>\n\n\n\n<li>Approval gates<\/li>\n\n\n\n<li>Safe rollout patterns<\/li>\n<\/ul>\n\n\n\n<p>This is the difference between \u201cAI helped me write code\u201d and \u201cAI changed my system.\u201d<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img decoding=\"async\" data-src=\"https:\/\/osmosys.co\/wp-content\/uploads\/2026\/02\/2-1.png\" alt=\"Concept illustration of agentic AI inside a DevOps pipeline, where an AI agent upgrades code, runs tests, and generates a PR summary for developer review.\" class=\"wp-image-239686 lazyload\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" \/><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\">Three high-value use cases (that don\u2019t require a moonshot)<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Use case 1: Modernization PRs (framework upgrades, dependency refresh, security fixes)<\/h3>\n\n\n\n<p>This is the cleanest entry point because it produces a reviewable artifact: a PR.<\/p>\n\n\n\n<p>What the agent does (typical):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Analyze repo + target framework\/runtime<\/li>\n\n\n\n<li>Draft an upgrade plan<\/li>\n\n\n\n<li>Apply transformations<\/li>\n\n\n\n<li>Run build\/tests<\/li>\n\n\n\n<li>Document what changed and what still needs humans<\/li>\n<\/ul>\n\n\n\n<p>Microsoft\u2019s .NET modernization guidance is explicitly oriented around this workflow.<\/p>\n\n\n\n<p><strong>Where humans stay essential:<\/strong> architectural decisions, breaking change handling, release planning, and acceptance criteria.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Use case 2: Infrastructure-as-code assistance (scripts, pipelines, environment bootstrapping)<\/h3>\n\n\n\n<p>Many teams already use copilots to draft Terraform\/Bicep, YAML pipelines, and runbook scripts.<\/p>\n\n\n\n<p>The agentic twist is that it can produce the change as a PR, then iterate until checks pass\u2014if your pipeline is set up well.<\/p>\n\n\n\n<p><strong>Where humans stay essential:<\/strong> networking, identity, secret boundaries, and production safety.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Use case 3: \u201cOps hygiene\u201d work (runbooks, alerts, post-incident follow-ups)<\/h3>\n\n\n\n<p>Agentic workflows can help create or update:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Runbooks that match what the team actually does<\/li>\n\n\n\n<li>Post-incident action items turned into PRs (documentation, checks, guardrails)<\/li>\n<\/ul>\n\n\n\n<p>This only works if you already have a DevOps habit of writing down operational knowledge and keeping it current.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">What practitioners warn about (and why it\u2019s useful)<\/h2>\n\n\n\n<p>In DevOps communities, two consistent warnings show up:<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>Over-dependence without understanding<\/strong> (teams fear losing fundamentals)<\/li>\n\n\n\n<li><strong>Agent sprawl<\/strong> (too many AI entry points, unclear ownership, unclear controls) \u2014 the governance concern, not the AI concern<\/li>\n<\/ol>\n\n\n\n<p>You don\u2019t need to agree with every comment to extract the pattern: the risk isn\u2019t \u201cAI exists.\u201d The risk is <strong>unowned automation<\/strong>.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">A practical rollout model for agentic AI in DevOps<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Step 1: Choose one workflow with clean boundaries<\/h3>\n\n\n\n<p>Good pilot candidates:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Upgrade one service to a newer runtime<\/li>\n\n\n\n<li>Refresh dependencies for one repo<\/li>\n\n\n\n<li>Add test coverage for a known brittle module<\/li>\n<\/ul>\n\n\n\n<p>Avoid first:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Broad refactors across many repos<\/li>\n\n\n\n<li>Production incident automation that can trigger changes without review<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">Step 2: Define what the agent can access<\/h3>\n\n\n\n<p>Write it down:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Repos: which ones, and why<\/li>\n\n\n\n<li>Environments: dev only at first<\/li>\n\n\n\n<li>Data: what it can and cannot see (especially logs, tickets, customer data)<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">Step 3: Make \u201creview\u201d non-negotiable<\/h3>\n\n\n\n<p>If the agent opens PRs, use the same rules you\u2019d use for a new engineer:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Required reviewers<\/li>\n\n\n\n<li>Branch protections<\/li>\n\n\n\n<li>Mandatory CI checks<\/li>\n\n\n\n<li>Security scanning gates<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">Step 4: Create a failure-safe path<\/h3>\n\n\n\n<p>Plan for:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Partial PRs that don\u2019t compile<\/li>\n\n\n\n<li>Changes that pass tests but violate conventions<\/li>\n\n\n\n<li>Hidden breaking changes<\/li>\n<\/ul>\n\n\n\n<p>The point of DevOps is not \u201cnever fail.\u201d It\u2019s \u201crecover predictably.\u201d<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Step 5: Instrument outcomes<\/h3>\n\n\n\n<p>Use delivery metrics as guardrails, not vanity.<\/p>\n\n\n\n<p>DORA\u2019s guidance defines common delivery performance measures like deployment frequency, change lead time, change fail rate, and recovery time.<br>Track them at the service level, not as a leaderboard.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Step 6: Scale with governance, not enthusiasm<\/h3>\n\n\n\n<p>Once the pilot works:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Expand to a second repo<\/li>\n\n\n\n<li>Standardize prompts\/patterns<\/li>\n\n\n\n<li>Add a lightweight \u201cagent registry\u201d (who owns it, what it touches, how it\u2019s monitored)<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Implementation checklist (copy\/paste)<\/h2>\n\n\n\n<p>Use this as your \u201cwe can do this safely\u201d baseline:<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li>Define one pilot repo and one target outcome (upgrade, deps refresh, tests, pipeline change).<\/li>\n\n\n\n<li>Enable branch protections and required reviews before agents create PRs.<\/li>\n\n\n\n<li>Confirm CI checks are meaningful (tests, lint, security scan).<\/li>\n\n\n\n<li>Use least-privilege permissions for the agent identity.<\/li>\n\n\n\n<li>Restrict secrets access; never allow plaintext secrets in prompts or files.<\/li>\n\n\n\n<li>Add a clear PR template for agent-generated changes (goal, approach, test evidence, known risks).<\/li>\n\n\n\n<li>Require the agent to run builds\/tests and attach results where possible.<\/li>\n\n\n\n<li>Define \u201cstop conditions\u201d (what triggers human takeover).<\/li>\n\n\n\n<li>Log and audit agent actions (PRs opened, files changed, pipelines triggered).<\/li>\n\n\n\n<li>Decide how you\u2019ll measure success (see next section).<\/li>\n\n\n\n<li>Document what data the agent can access and what it must not touch.<\/li>\n\n\n\n<li>Run a post-pilot review and update the playbook.<\/li>\n<\/ol>\n\n\n\n<h2 class=\"wp-block-heading\">Success metrics that make sense (without chasing vanity)<\/h2>\n\n\n\n<p>Start simple. A useful scorecard includes:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Delivery flow:<\/strong> change lead time trends (service-level)<\/li>\n\n\n\n<li><strong>Release safety:<\/strong> change fail rate and recovery time trends<\/li>\n\n\n\n<li><strong>Engineering productivity signals:<\/strong> fewer repeated \u201cupgrade toil\u201d tasks, fewer manual fix loops<\/li>\n\n\n\n<li><strong>Quality signals:<\/strong> test pass rate stability, reduced regression patterns<\/li>\n\n\n\n<li><strong>Governance signals:<\/strong> % agent PRs that pass review without policy exceptions, audit completeness<\/li>\n<\/ul>\n\n\n\n<p>If metrics get gamed, they stop being metrics. Keep them tied to outcomes and learning.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Region angle: ANZ, US, and Canada considerations<\/h2>\n\n\n\n<p>Agentic AI adoption looks similar across regions, but the <strong>risk questions<\/strong> change based on how you handle data and accountability.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>ANZ (Australia):<\/strong> The Privacy Act and Australian Privacy Principles are a common reference point when personal information is involved.<\/li>\n\n\n\n<li><strong>Canada:<\/strong> PIPEDA is the federal private-sector privacy law for personal information in commercial activities.<\/li>\n\n\n\n<li><strong>US:<\/strong> Many organizations operate across a patchwork of federal sector rules and state privacy laws, which often pushes teams toward stronger governance-by-default patterns.<\/li>\n<\/ul>\n\n\n\n<p>This is not legal advice. The practical DevOps takeaway is consistent: <strong>control what agents can access, log what they do, and keep humans accountable for approvals.<\/strong><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Suggested feature image (simple, minimal, no logos)<\/h2>\n\n\n\n<p>A clean diagram-style visual:<\/p>\n\n\n\n<p><strong>Title:<\/strong> \u201cAgentic AI in the DevOps Loop\u201d<br><strong>Visual:<\/strong> A circular flow: Plan \u2192 Code \u2192 Build \u2192 Test \u2192 Release \u2192 Monitor<br>Overlay a \u201cPR gate\u201d box between Code and Build with labels: \u201cAgent proposes PR\u201d \/ \u201cHuman reviews\u201d \/ \u201cCI checks\u201d<br>Alt text: \u201cDevOps workflow with agentic AI proposing pull requests and humans approving changes.\u201d<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Run a safe pilot, not a big-bang program<\/h2>\n\n\n\n<p>If you want to test agentic AI without turning it into a platform rewrite:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Pick one modernization target (one repo, one outcome).<\/li>\n\n\n\n<li>Put it behind your existing DevOps gates.<\/li>\n\n\n\n<li>Measure outcomes with delivery and stability metrics.<\/li>\n<\/ul>\n\n\n\n<p><strong>Osmosys can run an \u201cAgentic DevOps Pilot\u201d workshop<\/strong>: a short assessment of your current delivery setup (repos, CI\/CD, environments, controls), followed by a guided pilot where an agent produces reviewable PRs for a defined modernization task.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><a href=\"https:\/\/osmosys.co\/book-a-demo-2\/\"><img decoding=\"async\" data-src=\"https:\/\/osmosys.co\/wp-content\/uploads\/2026\/02\/3-1.png\" alt=\"Minimal flowchart of enterprise DevOps governance for AI agents: least-privilege access, audit logs, review gates, and monitored deployments across environments.\" class=\"wp-image-239687 lazyload\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" \/><\/a><\/figure>\n\n\n\n<p>Internal reading (recommended):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Agile and DevOps Delivery for Microsoft Projects (Osmosys)<\/li>\n\n\n\n<li>AI Governance Checklist for Dynamics 365 + Power Platform (Osmosys)<\/li>\n\n\n\n<li>Trust by Design: Data Governance for Cloud + AI (Osmosys)<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h2 class=\"wp-block-heading\">FAQs<\/h2>\n\n\n<div id=\"rank-math-faq\" class=\"rank-math-block\">\n<div class=\"rank-math-list \">\n<div id=\"faq-question-1770707903637\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \">What does DevOps look like when AI agents can write code?<\/h3>\n<div class=\"rank-math-answer \">\n\n<p>DevOps stays the same in principle\u2014version control, CI checks, reviews, controlled releases\u2014but you treat the agent like a contributor with identity, permissions, and audit trails.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-1770707917818\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \">Is agentic AI the same as ChatGPT?<\/h3>\n<div class=\"rank-math-answer \">\n\n<p>No. Chat-style tools respond to prompts. Agentic AI can execute multi-step work toward a goal, using tools like repos and CI to produce artifacts such as pull requests.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-1770708003931\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \">Where should teams start with agentic AI in DevOps?<\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Start with PR-based modernization tasks (dependency updates, framework upgrades, test additions). These create reviewable changes and fit naturally into existing delivery controls.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-1770708017675\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \">What\u2019s the biggest risk with agentic AI adoption?<\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Unowned automation: agents with unclear access, unclear approvals, and no monitoring. The fix is governance-by-default\u2014least privilege, review gates, and audit logs.<\/p>\n\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n<ul class=\"wp-block-social-links has-large-icon-size is-layout-flex wp-block-social-links-is-layout-flex\"><li class=\"wp-social-link wp-social-link-instagram  wp-block-social-link\"><a href=\"https:\/\/www.instagram.com\/osmosysindia\/\" class=\"wp-block-social-link-anchor\" target=\"_blank\" rel=\"noopener\"><svg width=\"24\" height=\"24\" viewBox=\"0 0 24 24\" version=\"1.1\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M12,4.622c2.403,0,2.688,0.009,3.637,0.052c0.877,0.04,1.354,0.187,1.671,0.31c0.42,0.163,0.72,0.358,1.035,0.673 c0.315,0.315,0.51,0.615,0.673,1.035c0.123,0.317,0.27,0.794,0.31,1.671c0.043,0.949,0.052,1.234,0.052,3.637 s-0.009,2.688-0.052,3.637c-0.04,0.877-0.187,1.354-0.31,1.671c-0.163,0.42-0.358,0.72-0.673,1.035 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Team A uses AI like a faster autocomplete. Helpful, but the work still happens in long bursts: someone writes an upgrade plan, someone else makes the changes, then the build breaks, [&hellip;]<\/p>\n","protected":false},"author":44,"featured_media":237378,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"off","_et_pb_old_content":"","_et_gb_content_width":"","_lmt_disableupdate":"","_lmt_disable":"","jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[75,82],"tags":[144,140,83,171,164,172],"class_list":["post-237377","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai","category-devops","tag-agentic-ai","tag-azure","tag-devops","tag-github-copilot","tag-governance","tag-modernization"],"modified_by":"mounika","jetpack_featured_media_url":"https:\/\/osmosys.co\/uk\/wp-content\/uploads\/sites\/6\/2026\/02\/1-1.png","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/osmosys.co\/uk\/wp-json\/wp\/v2\/posts\/237377","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/osmosys.co\/uk\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/osmosys.co\/uk\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/osmosys.co\/uk\/wp-json\/wp\/v2\/users\/44"}],"replies":[{"embeddable":true,"href":"https:\/\/osmosys.co\/uk\/wp-json\/wp\/v2\/comments?post=237377"}],"version-history":[{"count":1,"href":"https:\/\/osmosys.co\/uk\/wp-json\/wp\/v2\/posts\/237377\/revisions"}],"predecessor-version":[{"id":237379,"href":"https:\/\/osmosys.co\/uk\/wp-json\/wp\/v2\/posts\/237377\/revisions\/237379"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/osmosys.co\/uk\/wp-json\/wp\/v2\/media\/237378"}],"wp:attachment":[{"href":"https:\/\/osmosys.co\/uk\/wp-json\/wp\/v2\/media?parent=237377"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/osmosys.co\/uk\/wp-json\/wp\/v2\/categories?post=237377"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/osmosys.co\/uk\/wp-json\/wp\/v2\/tags?post=237377"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}