{
  "updated": "2026-10-25",
  "publisher": "Manifold AI Learning",
  "purpose": "Publisher-provided course-fit guidance. Check current official course and enrolment pages for availability and offer terms.",
  "approach": "I help experienced technology professionals move beyond Agentic demos and build production-ready systems.",
  "learning_paths_url": "https://manifoldailearning.com/agentic-ai-learning-paths",
  "bootcamp_choice_guidance": "Developer builds agent-development fluency through progressive projects; Enterprise engineers one integrated production-style system. Shared foundation bonuses do not make the core programmes interchangeable. Developer is not a required purchase before Enterprise. Compare core goals and skills; use included prep where sufficient. Recommend both only for a clear progression.",
  "products": [
    {
      "id": "agentic-ai-developer-bootcamp",
      "title": "Agentic AI Developer Bootcamp",
      "path": "/services/agentic-ai-developer-bootcamp",
      "url": "https://manifoldailearning.com/services/agentic-ai-developer-bootcamp",
      "summary": "Build agent-development fluency through progressive projects. Use the included Python and API preparation where needed. Choose by your implementation gap, not years of experience alone.",
      "format": "Live cohort · 10 January 2027 · Prep available now",
      "prerequisites": "Basic programming is helpful. The included Python Prep Module supports a foundation refresh. Practise Python and API calls before the advanced agent exercises.",
      "core_outcome": "Build hands-on agent-development fluency through progressive projects with models, tools, retrieval and agent frameworks.",
      "included_preparation": "Python and API preparation supports the main developer curriculum.",
      "choose_when": "Choose this when you need structured practice building and changing agent applications.",
      "enrolment_url": "https://pay.manifoldailearning.in/checkout?product=agentic-ai-developer-bootcamp&return_url=https%3A%2F%2Fmanifoldailearning.com%2Fservices%2Fagentic-ai-developer-bootcamp",
      "enrolment_type": "checkout",
      "experience": [
        {
          "id": "0-2",
          "label": "0–2 years",
          "benefit": "Build the programming and request-flow foundation behind a bounded agent. Practise Python and APIs first if programming is new.",
          "evidence": "Run a small agent, change a tool input and explain one error independently."
        },
        {
          "id": "2-5",
          "label": "2–5 years",
          "benefit": "Bring your API and backend experience into model calls, tools, state and validation.",
          "evidence": "Trace a request from client to model and tool, then demonstrate a validation or recovery check."
        },
        {
          "id": "5-8",
          "label": "5–8 years",
          "benefit": "Uncover implementation gaps behind architecture discussions. Focus on boundaries and failure behaviour rather than familiar coding basics.",
          "evidence": "Document a state transition, a tool failure and the change you made to handle it."
        },
        {
          "id": "8-12",
          "label": "8–12 years",
          "benefit": "Calibrate architecture against implementation. Start with System Design instead if you already build and debug agents.",
          "evidence": "Walk another engineer through a working agent and defend where the framework ends and your engineering begins."
        },
        {
          "id": "12-plus",
          "label": "12+ years",
          "benefit": "Choose this for direct implementation context. For a leadership-first goal, begin with System Design and revisit coding where it improves judgement.",
          "evidence": "Inspect a runnable workflow and ask specific questions about validation, failure boundaries and ownership."
        }
      ],
      "start_date": "2027-01-10T07:00:00+05:30"
    },
    {
      "id": "ai-architect",
      "title": "AI Architect System Design",
      "path": "/services/ai-system-design",
      "url": "https://manifoldailearning.com/services/ai-system-design",
      "summary": "Move from naming AI components to explaining why a design fits a real constraint. Use your experience to choose the depth of the decisions you practise.",
      "format": "Self-paced · Architecture decisions",
      "prerequisites": "Basic software design and API concepts are useful. If you have never built a small application, build that foundation before advanced architecture decisions.",
      "enrolment_url": "https://pay.manifoldailearning.in/checkout?product=ai-architect&return_url=https%3A%2F%2Fmanifoldailearning.com%2Fservices%2Fai-system-design",
      "enrolment_type": "checkout",
      "experience": [
        {
          "id": "0-2",
          "label": "0–2 years",
          "benefit": "Connect architecture concepts to a small application you have already built. Build your Python and API foundation first if it is missing.",
          "evidence": "Draw a request flow and explain why a simpler workflow might be enough."
        },
        {
          "id": "2-5",
          "label": "2–5 years",
          "benefit": "Compare model, retrieval and orchestration choices while owning an AI feature.",
          "evidence": "Write a design decision: requirement, alternatives, chosen approach and a test."
        },
        {
          "id": "5-8",
          "label": "5–8 years",
          "benefit": "Defend quality, latency, cost and failure-handling trade-offs at senior-engineer depth.",
          "evidence": "Document a bottleneck, its failure boundary and the evidence for a design change."
        },
        {
          "id": "8-12",
          "label": "8–12 years",
          "benefit": "Lead architecture conversations using a shared decision framework across application, model and operating boundaries.",
          "evidence": "Prepare a model-and-retrieval decision matrix and a review agenda for your team."
        },
        {
          "id": "12-plus",
          "label": "12+ years",
          "benefit": "Evaluate AI proposals against business constraints and delivery evidence. Challenge assumptions without prescribing every implementation detail.",
          "evidence": "Create a decision brief: problem, baseline, investment question, risk owner and acceptance test."
        }
      ]
    },
    {
      "id": "rag-system-design",
      "title": "Production RAG System Design",
      "path": "/services/prodrag",
      "url": "https://manifoldailearning.com/services/prodrag",
      "summary": "Go beyond a vector-search demo. Understand what is retrieved, why an answer is supported and how the service behaves.",
      "format": "Self-paced · Retrieval architecture",
      "prerequisites": "Basic Python and a small LLM application help you get more from retrieval architecture and debugging.",
      "enrolment_url": "https://pay.manifoldailearning.in/checkout?product=rag-system-design&return_url=https%3A%2F%2Fmanifoldailearning.com%2Fservices%2Fprodrag",
      "enrolment_type": "checkout",
      "experience": [
        {
          "id": "0-2",
          "label": "0–2 years",
          "benefit": "After basic Python and an LLM application, connect documents, retrieval and grounded answers.",
          "evidence": "Trace one question to its source and explain an unsupported answer."
        },
        {
          "id": "2-5",
          "label": "2–5 years",
          "benefit": "Investigate retrieval quality using the debugging and service-design experience you already have.",
          "evidence": "Compare retrieval choices on a small question set and record which failures each fixes."
        },
        {
          "id": "5-8",
          "label": "5–8 years",
          "benefit": "Own retrieval, caching and guardrails as connected production decisions.",
          "evidence": "Write a retrieval design note with a baseline, a latency choice and a reproducible failure."
        },
        {
          "id": "8-12",
          "label": "8–12 years",
          "benefit": "Review retrieval across data, application and operating boundaries when specialist retrieval depth is your gap.",
          "evidence": "Defend an approach using relevance, freshness, cost and support constraints."
        },
        {
          "id": "12-plus",
          "label": "12+ years",
          "benefit": "Assess what the data can support and who owns an incorrect answer before scaling a retrieval initiative.",
          "evidence": "Prepare a review of supported answers, access assumptions, known gaps and a release decision."
        }
      ]
    },
    {
      "id": "testing-agentic-ai",
      "title": "AI Evals & Reliability",
      "path": "/services/testing-agentic-ai-systems",
      "url": "https://manifoldailearning.com/services/testing-agentic-ai-systems",
      "summary": "Turn a successful demonstration into repeatable evidence about quality, safety and reliability.",
      "format": "Self-paced · Test and defend quality",
      "prerequisites": "Basic Python and an LLM, RAG or agent workflow to inspect. Build a simple application first if you need implementation foundations.",
      "enrolment_url": "https://pay.manifoldailearning.in/checkout?product=testing-agentic-ai&return_url=https%3A%2F%2Fmanifoldailearning.com%2Fservices%2Ftesting-agentic-ai-systems",
      "enrolment_type": "checkout",
      "experience": [
        {
          "id": "0-2",
          "label": "0–2 years",
          "benefit": "With basic Python and an application to inspect, start classifying good and bad outputs.",
          "evidence": "Create examples with expected behaviour and label the failures you observe."
        },
        {
          "id": "2-5",
          "label": "2–5 years",
          "benefit": "Add repeatable checks to an AI feature instead of relying on a few impressive outputs.",
          "evidence": "Run a regression set before and after a change and explain the difference."
        },
        {
          "id": "5-8",
          "label": "5–8 years",
          "benefit": "Own release-readiness discussions through failure categories and acceptance criteria.",
          "evidence": "Write a release note connecting failures, thresholds and the decision to ship or hold."
        },
        {
          "id": "8-12",
          "label": "8–12 years",
          "benefit": "Coordinate evaluation across models, workflows and teams.",
          "evidence": "Create a review checklist with quality criteria, responsible owners and accepted risks."
        },
        {
          "id": "12-plus",
          "label": "12+ years",
          "benefit": "Question unsupported AI quality claims and connect evaluation to operating and business exposure.",
          "evidence": "Draft a decision memo separating measured behaviour, unresolved risks and accountable next actions."
        }
      ]
    },
    {
      "id": "agentic-ops-bootcamp",
      "title": "Agentic Ops Bootcamp",
      "path": "/agentic-ops-bootcamp",
      "url": "https://manifoldailearning.com/agentic-ops-bootcamp",
      "summary": "Build visibility into AI applications through traces, evaluation, dashboards and actionable alerts. Pre-release: full course available by 8 November 2026.",
      "format": "Pre-release · Full course by 8 November 2026",
      "prerequisites": "Basic Python, API calls and an AI workflow to inspect. Start with application foundations if you cannot yet follow a request through a system.",
      "enrolment_url": "https://pay.manifoldailearning.in/checkout?product=agentic-ops-bootcamp&return_url=https%3A%2F%2Fmanifoldailearning.com%2Fagentic-ops-bootcamp",
      "enrolment_type": "checkout",
      "experience": [
        {
          "id": "0-2",
          "label": "0–2 years",
          "benefit": "After basic Python and an AI request flow, learn to follow a run and locate a failure.",
          "evidence": "Show a workflow trace and identify the step that caused an error."
        },
        {
          "id": "2-5",
          "label": "2–5 years",
          "benefit": "Bring service-debugging experience into AI workflows.",
          "evidence": "Use a trace and evaluation result to explain why a workflow needs a change."
        },
        {
          "id": "5-8",
          "label": "5–8 years",
          "benefit": "Own operational behaviour beyond a working demo. Make dashboards answer useful failure questions.",
          "evidence": "Build a dashboard and document the action one alert should trigger."
        },
        {
          "id": "8-12",
          "label": "8–12 years",
          "benefit": "Connect architecture, release quality and operating ownership across teams.",
          "evidence": "Produce a monitoring and response plan with traces, quality signals and owners."
        },
        {
          "id": "12-plus",
          "label": "12+ years",
          "benefit": "Ask for operating evidence before scaling an AI initiative.",
          "evidence": "Review a dashboard with an owner, a failure scenario and the decision each important signal supports."
        }
      ],
      "release_date": "2026-11-08",
      "availability": "pre-release"
    },
    {
      "id": "agentic-interview",
      "title": "AI Interview Playbook",
      "path": "/services/agentic-interview",
      "url": "https://manifoldailearning.com/services/agentic-interview",
      "summary": "You may already know the material. Structure how you explain the problem, your decisions, trade-offs and evidence at the depth your target role needs.",
      "format": "Self-paced · Structure your answers",
      "prerequisites": "Bring concepts you have studied and projects or work you can honestly explain. This develops answer structure; it does not replace implementation practice.",
      "enrolment_url": "https://pay.manifoldailearning.in/checkout?product=agentic-interview&return_url=https%3A%2F%2Fmanifoldailearning.com%2Fservices%2Fagentic-interview",
      "enrolment_type": "checkout",
      "experience": [
        {
          "id": "0-2",
          "label": "0–2 years",
          "benefit": "Make your own contribution visible without presenting a tutorial as independent production experience.",
          "evidence": "Explain a project through the problem, your implementation, a failure and what you changed."
        },
        {
          "id": "2-5",
          "label": "2–5 years",
          "benefit": "Turn feature work into clear answers about request flow, choices and debugging.",
          "evidence": "Prepare a structured answer and a follow-up on an alternative you rejected."
        },
        {
          "id": "5-8",
          "label": "5–8 years",
          "benefit": "Show senior judgement through trade-offs, failure handling and ownership.",
          "evidence": "Defend a decision using constraints, alternatives, your contribution and system evidence."
        },
        {
          "id": "8-12",
          "label": "8–12 years",
          "benefit": "Connect architecture and delivery choices in answers shaped for staff, architect or lead responsibility.",
          "evidence": "Practise a cross-system discussion covering dependencies, quality and ownership."
        },
        {
          "id": "12-plus",
          "label": "12+ years",
          "benefit": "Support leadership discussions with technical explanations. Worker2Builder is the broader next step for role and resume positioning.",
          "evidence": "Prepare a narrative connecting the business problem, technical choices, risks, stakeholders and delivery evidence."
        }
      ]
    },
    {
      "id": "worker2builder-career-transition",
      "title": "Worker2Builder Career Transition",
      "path": "/worker2builder-career-transition-accelerator",
      "url": "https://manifoldailearning.com/worker2builder-career-transition-accelerator",
      "summary": "Build your next-role strategy around your actual experience. Self-paced weekly modules and exercises, with role-focused Q&A every two weeks.",
      "format": "Self-paced · Weekly release · Q&A every two weeks",
      "prerequisites": "Designed for working technology professionals. Bring real work or project evidence and a target responsibility; start with implementation foundations if you need your first application.",
      "enrolment_url": "https://pay.manifoldailearning.in/checkout?product=worker2builder-career-transition&return_url=https%3A%2F%2Fmanifoldailearning.com%2Fworker2builder-career-transition-accelerator",
      "enrolment_type": "checkout",
      "experience": [
        {
          "id": "0-2",
          "label": "0–2 years",
          "benefit": "Use this when you have work or project evidence to position. Start with the Developer path if the gap is building your first application.",
          "evidence": "Create an honest map separating your own contribution from the tutorial, course or team."
        },
        {
          "id": "2-5",
          "label": "2–5 years",
          "benefit": "Position engineering work for AI feature delivery with resume claims supported by evidence.",
          "evidence": "Build a target-role map and rewrite one resume example around your contribution and decisions."
        },
        {
          "id": "5-8",
          "label": "5–8 years",
          "benefit": "Show senior scope through ownership and defensible decisions rather than years of experience alone.",
          "evidence": "Prepare a project story and question bank showing a decision, a failure and your responsibility."
        },
        {
          "id": "8-12",
          "label": "8–12 years",
          "benefit": "Translate architecture, team or domain experience into a coherent next-role strategy.",
          "evidence": "Create positioning supported by cross-system judgement and delivery examples."
        },
        {
          "id": "12-plus",
          "label": "12+ years",
          "benefit": "Shape architecture or leadership positioning around actual scope. Director and Head roles also require people and business accountability.",
          "evidence": "Develop an evidence map: direction set, stakeholders aligned, risks handled and delivery decisions owned."
        }
      ]
    },
    {
      "id": "ai-project-portfolio-accelerator",
      "title": "AI Project Portfolio Accelerator",
      "path": "/ai-project-portfolio-accelerator",
      "url": "https://manifoldailearning.com/ai-project-portfolio-accelerator",
      "summary": "Make your judgement visible through implementation, decisions and ownership. This accelerator is self-paced.",
      "format": "Self-paced · Build evidence of your work",
      "prerequisites": "Basic Python and familiarity with an LLM application. Be ready to implement, document and explain your own work.",
      "enrolment_url": "https://pay.manifoldailearning.in/checkout?product=ai-project-portfolio-accelerator&return_url=https%3A%2F%2Fmanifoldailearning.com%2Fai-project-portfolio-accelerator",
      "enrolment_type": "checkout",
      "experience": [
        {
          "id": "0-2",
          "label": "0–2 years",
          "benefit": "Choose a bounded project you can run, change and explain before presenting enterprise-scale ownership.",
          "evidence": "Demonstrate the request flow, one change you made and a failure you can reproduce."
        },
        {
          "id": "2-5",
          "label": "2–5 years",
          "benefit": "Turn a working application into evidence of independent engineering decisions.",
          "evidence": "Prepare a runnable project with setup instructions, a design choice and a short demonstration."
        },
        {
          "id": "5-8",
          "label": "5–8 years",
          "benefit": "Show trade-offs and reliability evidence alongside implementation.",
          "evidence": "Add a decision log, failure analysis and evaluation evidence to your walkthrough."
        },
        {
          "id": "8-12",
          "label": "8–12 years",
          "benefit": "Demonstrate architecture judgement and delivery boundaries that another engineer can review.",
          "evidence": "Create an architecture defence covering assumptions, alternatives, evaluation and handoff."
        },
        {
          "id": "12-plus",
          "label": "12+ years",
          "benefit": "Connect project evidence to direction and accountability instead of relying on a demo alone.",
          "evidence": "Produce a case study connecting the problem, baseline, design review, risks and delivery evidence."
        }
      ]
    },
    {
      "id": "python-automation-mlops",
      "title": "Python Foundations & Automation",
      "path": "/services/python-automation-for-agentic-ai-mlops",
      "url": "https://manifoldailearning.com/services/python-automation-for-agentic-ai-mlops",
      "summary": "Build independence with Python, API calls and automation. This separate foundation is optional; Developer Bootcamp includes Python prep and Enterprise Mastery includes Python and LangChain foundation bonuses. Use the included preparation if it meets your needs.",
      "format": "Self-paced · Optional foundation",
      "prerequisites": "No prior AI course is required. Choose this if you need practice with Python, JSON, API calls and debugging; skip foundations you can already demonstrate.",
      "enrolment_url": "https://pay.manifoldailearning.in/checkout?product=python-automation-mlops&return_url=https%3A%2F%2Fmanifoldailearning.com%2Fservices%2Fpython-automation-for-agentic-ai-mlops",
      "enrolment_type": "checkout",
      "experience": [
        {
          "id": "0-2",
          "label": "0–2 years",
          "benefit": "Practise functions, JSON, API calls and debugging before agent frameworks. Allow practice time if programming itself is new.",
          "evidence": "Run an API-based script, inspect its output and explain one error."
        },
        {
          "id": "2-5",
          "label": "2–5 years",
          "benefit": "Close Python gaps that slow down an engineering workflow. Skip the course if you already automate and debug comfortably.",
          "evidence": "Replace a repetitive task with a script that validates inputs and handles a failure."
        },
        {
          "id": "5-8",
          "label": "5–8 years",
          "benefit": "Use this as targeted preparation for automation and ML/AI workflows instead of repeating foundations you already have.",
          "evidence": "Make a script understandable through clear inputs, error handling and run instructions."
        },
        {
          "id": "8-12",
          "label": "8–12 years",
          "benefit": "Choose it if Python is the missing link between your design and implementation; otherwise start with System Design.",
          "evidence": "Inspect an API workflow, make a change yourself and explain the failure boundary."
        },
        {
          "id": "12-plus",
          "label": "12+ years",
          "benefit": "Treat this as an optional implementation refresh. Architecture and evaluation are usually a more useful direction-first entry.",
          "evidence": "Use one small automation to question how inputs, dependencies and failures are handled."
        }
      ]
    },
    {
      "id": "complete-mlops-bootcamp-bundle",
      "title": "Complete MLOps Bootcamp Bundle",
      "path": "/services/complete-mlops-bootcamp-bundle",
      "url": "https://manifoldailearning.com/services/complete-mlops-bootcamp-bundle",
      "summary": "Connect experimentation, packaging, serving and operational workflows when your gap is repeatable model delivery.",
      "format": "Self-paced recordings and implementation material",
      "prerequisites": "Python and basic machine learning knowledge are recommended before model packaging, deployment and operational workflows.",
      "enrolment_url": "https://pay.manifoldailearning.in/checkout?product=complete-mlops-bootcamp-bundle&return_url=https%3A%2F%2Fmanifoldailearning.com%2Fservices%2Fcomplete-mlops-bootcamp-bundle",
      "enrolment_type": "checkout",
      "experience": [
        {
          "id": "0-2",
          "label": "0–2 years",
          "benefit": "Build Python and basic ML foundations before deployment workflows.",
          "evidence": "Explain how a model artifact becomes an API another person can run."
        },
        {
          "id": "2-5",
          "label": "2–5 years",
          "benefit": "Move a local experiment towards a reproducible engineering workflow.",
          "evidence": "Package an experiment with its dependencies and demonstrate an inference request."
        },
        {
          "id": "5-8",
          "label": "5–8 years",
          "benefit": "Own reproducibility and deployment choices across the model lifecycle.",
          "evidence": "Prepare an experiment and deployment checklist with a failure and recovery action."
        },
        {
          "id": "8-12",
          "label": "8–12 years",
          "benefit": "Review the boundaries between data science, application teams and operations.",
          "evidence": "Write a handoff covering artifacts, serving assumptions, monitoring and responsible teams."
        },
        {
          "id": "12-plus",
          "label": "12+ years",
          "benefit": "Assess the operating maturity behind an ML initiative.",
          "evidence": "Create a readiness review covering reproducibility, deployment evidence and ongoing ownership."
        }
      ]
    },
    {
      "id": "generative-ai-nlp-bootcamp",
      "title": "Generative AI & NLP Engineering Bootcamp",
      "path": "/services/generative-ai-nlp-engineering-bootcamp",
      "url": "https://manifoldailearning.com/services/generative-ai-nlp-engineering-bootcamp",
      "summary": "Understand the model layer: text representations, neural networks, attention, transformers and adaptation.",
      "format": "Self-paced model and NLP engineering study",
      "prerequisites": "Python and basic machine learning knowledge are useful before deeper model and NLP topics.",
      "enrolment_url": "https://pay.manifoldailearning.in/checkout?product=generative-ai-nlp-bootcamp&return_url=https%3A%2F%2Fmanifoldailearning.com%2Fservices%2Fgenerative-ai-nlp-engineering-bootcamp",
      "enrolment_type": "checkout",
      "experience": [
        {
          "id": "0-2",
          "label": "0–2 years",
          "benefit": "Strengthen Python and ML basics before advanced model topics.",
          "evidence": "Explain tokenization and trace a small text example through a model workflow."
        },
        {
          "id": "2-5",
          "label": "2–5 years",
          "benefit": "Connect application code to the model behaviour it depends on.",
          "evidence": "Compare model-output choices and explain the behaviour you observed."
        },
        {
          "id": "5-8",
          "label": "5–8 years",
          "benefit": "Defend model and adaptation choices beyond framework vocabulary.",
          "evidence": "Write a model-choice note with assumptions, a baseline and an adaptation trade-off."
        },
        {
          "id": "8-12",
          "label": "8–12 years",
          "benefit": "Review the model layer as part of architecture rather than an interchangeable endpoint.",
          "evidence": "Explain how model structure, decoding and adaptation affect an application design."
        },
        {
          "id": "12-plus",
          "label": "12+ years",
          "benefit": "Challenge model-work proposals and distinguish model limitations from application problems.",
          "evidence": "Write a review brief separating the user problem, model limitation and evidence for adaptation."
        }
      ]
    },
    {
      "id": "agentic-ai-bootcamp",
      "title": "Agentic AI Enterprise Mastery Bootcamp",
      "path": "/services/agenticaibootcamp",
      "url": "https://manifoldailearning.com/services/agenticaibootcamp",
      "summary": "Connect architecture, tools, retrieval, evaluation and operations in one production-style build. Python and LangChain foundation bonuses help you prepare. No prior Developer Bootcamp purchase is required.",
      "format": "Live cohort · 7 November 2026 · Pay-in-2 pilot",
      "prerequisites": "Be ready to work with code and APIs. Included Python and LangChain foundations help refresh gaps before the integrated build. No previous Manifold course purchase is required.",
      "core_outcome": "Engineer one integrated production-style system across state, reliability, security, evaluation, deployment and operations.",
      "included_preparation": "Python and LangChain foundation bonuses prepare you for the integrated build; they do not include the full Developer Bootcamp.",
      "choose_when": "Choose this for production engineering when you can work with code and APIs. Use the included foundations to refresh gaps; no prior Manifold purchase is required.",
      "enrolment_url": "https://learn.manifoldailearning.com/web/checkout/6ad7012d8a2dbb12eaeb9b2d?purchaseNow=true",
      "enrolment_type": "checkout",
      "experience": [
        {
          "id": "0-2",
          "label": "0–2 years",
          "benefit": "Build application foundations first. Join the integrated build when you can trace an API call and make small changes independently.",
          "evidence": "Demonstrate a bounded workflow and explain its tools and a failure."
        },
        {
          "id": "2-5",
          "label": "2–5 years",
          "benefit": "Stretch from an individual feature towards the connected system around it.",
          "evidence": "Trace an end-to-end request and show how a failure is detected and handled."
        },
        {
          "id": "5-8",
          "label": "5–8 years",
          "benefit": "Practise interfaces and quality decisions a senior engineer must own.",
          "evidence": "Produce a system walkthrough with a design decision, regression evidence and an operational handoff."
        },
        {
          "id": "8-12",
          "label": "8–12 years",
          "benefit": "Validate architecture judgement against implementation and delivery evidence.",
          "evidence": "Defend boundaries, state, evaluation and support ownership using the same runnable system."
        },
        {
          "id": "12-plus",
          "label": "12+ years",
          "benefit": "Calibrate technical direction against how delivery actually works.",
          "evidence": "Review the architecture against traces, release evidence, ownership and a recovery plan."
        }
      ],
      "start_date": "2026-11-07T07:00:00+05:30",
      "benefits": [
        "Live implementation across architecture, tools, retrieval, evaluation and operations.",
        "October cohort recordings for asynchronous learning.",
        "Two future cohort opportunities. Advanced RAG bonus activates after full payment."
      ],
      "payment_terms": "Pilot: 50% today and the remaining 50% within 20 days of enrolment. Select Flexi Pay at checkout; full payment is also available."
    },
    {
      "id": "nvidia-nca-genl",
      "title": "NVIDIA NCA-GENL Exam Prep",
      "path": "/services/nca-genl-exam-prep",
      "url": "https://manifoldailearning.com/services/nca-genl-exam-prep",
      "summary": "Consolidate foundational GenAI concepts after practical work. Exam preparation does not replace project evidence or include vendor exam fees.",
      "format": "Self-paced · Associate certification prep",
      "prerequisites": "Foundational GenAI concepts are useful. This is independent exam preparation; vendor exam registration and fees are separate.",
      "enrolment_url": "https://pay.manifoldailearning.in/checkout?product=nvidia-nca-genl&return_url=https%3A%2F%2Fmanifoldailearning.com%2Fservices%2Fnca-genl-exam-prep",
      "enrolment_type": "checkout",
      "experience": [
        {
          "id": "0-2",
          "label": "0–2 years",
          "benefit": "Use associate preparation as optional consolidation after basic hands-on work.",
          "evidence": "Connect a practice answer to an application and explain why the alternatives do not fit."
        },
        {
          "id": "2-5",
          "label": "2–5 years",
          "benefit": "Close conceptual gaps alongside delivery. Consider professional preparation later if your AI/ML experience meets official guidance.",
          "evidence": "Build a concept-gap list from practice results and test it against your work."
        },
        {
          "id": "5-8",
          "label": "5–8 years",
          "benefit": "Use this as a foundational check rather than the main evidence of senior engineering ability.",
          "evidence": "Identify a concept you cannot yet explain in a design discussion."
        },
        {
          "id": "8-12",
          "label": "8–12 years",
          "benefit": "Choose this for a foundational refresh, while keeping design and delivery evidence central.",
          "evidence": "Translate an exam topic into a model or workflow decision."
        },
        {
          "id": "12-plus",
          "label": "12+ years",
          "benefit": "Choose it for GenAI vocabulary if needed; leadership also requires decision quality and accountability.",
          "evidence": "Explain a concept through its usefulness, limitations and questions a team should answer."
        }
      ]
    },
    {
      "id": "ncp-aai",
      "title": "NVIDIA NCP-AAI Exam Prep",
      "path": "/services/nvidiancpaai",
      "url": "https://manifoldailearning.com/services/nvidiancpaai",
      "summary": "Professional preparation follows practical work. Check NVIDIA’s current AI/ML and production-project prerequisites; technology experience alone does not establish exam readiness.",
      "format": "Professional exam prep · Check official prerequisites",
      "prerequisites": "Practical AI/ML and project experience matter. Check NVIDIA’s current official prerequisites before planning the exam. Exam registration and fees are separate.",
      "enrolment_url": "https://pay.manifoldailearning.in/checkout?product=ncp-aai&return_url=https%3A%2F%2Fmanifoldailearning.com%2Fservices%2Fnvidiancpaai",
      "enrolment_type": "checkout",
      "experience": [
        {
          "id": "0-2",
          "label": "0–2 years",
          "benefit": "Usually a later step. Build Python, AI application and project experience before professional practice.",
          "evidence": "Identify the foundations and projects you need before assessing exam readiness."
        },
        {
          "id": "2-5",
          "label": "2–5 years",
          "benefit": "Consolidate architecture and delivery concepts after hands-on implementation.",
          "evidence": "Turn practice misses into a study plan connected to a working project."
        },
        {
          "id": "5-8",
          "label": "5–8 years",
          "benefit": "Validate breadth after you can defend implementation and release decisions.",
          "evidence": "Connect blueprint topics to a project, release decision and operating failure case."
        },
        {
          "id": "8-12",
          "label": "8–12 years",
          "benefit": "Use preparation as supporting validation for a hands-on architect or FDE direction.",
          "evidence": "Map your designs, evaluations and delivery decisions to the exam domains."
        },
        {
          "id": "12-plus",
          "label": "12+ years",
          "benefit": "Choose this for a hands-on architecture route when prerequisites fit. For management, prioritise decision briefs and review standards first.",
          "evidence": "Identify which topics strengthen judgement and which gaps need practical work before certification."
        }
      ]
    },
    {
      "id": "ai-interview-readiness-review",
      "title": "AI Clarity & Direction Session",
      "path": "/services/ai-interview-readiness",
      "url": "https://manifoldailearning.com/services/ai-interview-readiness",
      "summary": "Bring your current work, target responsibility and questions to one personal session. Use the conversation to prioritise a clearer next decision.",
      "format": "One personal 45-minute session · Book with support",
      "prerequisites": "Bring your background, goals and current questions. No coding prerequisite; the session prioritises decisions and next actions.",
      "enrolment_url": "https://pay.manifoldailearning.in/checkout?product=ai-interview-readiness-review&return_url=https%3A%2F%2Fmanifoldailearning.com%2Fservices%2Fai-interview-readiness",
      "enrolment_type": "checkout",
      "experience": [
        {
          "id": "0-2",
          "label": "0–2 years",
          "benefit": "Clarify which foundation to build before buying several advanced courses.",
          "evidence": "Bring your skills and a target role to work towards a short list of next actions."
        },
        {
          "id": "2-5",
          "label": "2–5 years",
          "benefit": "Connect your engineering background to an AI delivery direction.",
          "evidence": "Bring a role description and project example to prioritise the most useful gap."
        },
        {
          "id": "5-8",
          "label": "5–8 years",
          "benefit": "Identify whether the gap is architecture depth, delivery evidence or positioning.",
          "evidence": "Review a decision or project story and work towards a clearer preparation sequence."
        },
        {
          "id": "8-12",
          "label": "8–12 years",
          "benefit": "Explore the fit between architecture, field delivery and engineering leadership.",
          "evidence": "Discuss the responsibilities you want and the evidence they require."
        },
        {
          "id": "12-plus",
          "label": "12+ years",
          "benefit": "Separate a skills gap from a positioning or role-fit question.",
          "evidence": "Bring a target role, recent responsibilities and current plan to prioritise the next decision."
        }
      ]
    },
    {
      "id": "nachiketh-1-1-strategy",
      "title": "1-on-1 Strategy Session",
      "path": "/nachiketh-murthy-1-1-strategy-session",
      "url": "https://manifoldailearning.com/nachiketh-murthy-1-1-strategy-session",
      "summary": "Clarify direction and priorities around your actual experience. Personal guidance shapes next actions; it does not replace doing the work.",
      "format": "Private strategy session; confirm scheduling availability",
      "prerequisites": "Bring your background, goals and questions. Personal guidance helps prioritise action; practical progress still requires your own work.",
      "enrolment_url": "https://pay.manifoldailearning.in/checkout?product=nachiketh-1-1-strategy&return_url=https%3A%2F%2Fmanifoldailearning.com%2Fnachiketh-murthy-1-1-strategy-session",
      "enrolment_type": "checkout",
      "experience": [
        {
          "id": "0-2",
          "label": "0–2 years",
          "benefit": "Choose a manageable starting point before advanced study.",
          "evidence": "Bring your background and questions to shape a practical first sequence."
        },
        {
          "id": "2-5",
          "label": "2–5 years",
          "benefit": "Connect engineering experience to a useful AI learning and project direction.",
          "evidence": "Identify the most important gap for a role or project goal."
        },
        {
          "id": "5-8",
          "label": "5–8 years",
          "benefit": "Review architecture, delivery evidence and positioning against your next responsibility.",
          "evidence": "Bring a project story to prioritise technical or communication gaps."
        },
        {
          "id": "8-12",
          "label": "8–12 years",
          "benefit": "Compare architecture, field delivery and team leadership against your strengths.",
          "evidence": "Discuss examples of your current scope and the responsibility you want."
        },
        {
          "id": "12-plus",
          "label": "12+ years",
          "benefit": "Prioritise direction, technical judgement and evidence for broader leadership.",
          "evidence": "Bring a decision brief or role goal to identify actions that fit your responsibilities."
        }
      ]
    },
    {
      "id": "forward-deployed-ai-engineer-residency",
      "title": "Forward Deployed AI Engineer Residency",
      "path": "/forward-deployed-ai-engineer-residency",
      "url": "https://manifoldailearning.com/forward-deployed-ai-engineer-residency",
      "summary": "A later applied stage for hands-on customer delivery. Access is through Diamond Membership; experience-pathway bundles do not include FDE.",
      "format": "Diamond-exclusive applied residency; confirm current intake availability",
      "prerequisites": "A later applied stage for learners with implementation and architecture foundations. Diamond-exclusive access; experience-pathway bundles do not include FDE. Confirm intake availability before enrolment.",
      "enrolment_url": "https://manifoldailearning.com/diamond-membership#pricing",
      "enrolment_type": "application",
      "experience": [
        {
          "id": "0-2",
          "label": "0–2 years",
          "benefit": "Treat FDE as a longer-term direction after coding, APIs and AI project foundations.",
          "evidence": "First show you can run and change an application and explain a failure independently."
        },
        {
          "id": "2-5",
          "label": "2–5 years",
          "benefit": "Build independent delivery and architecture evidence before broader customer ownership.",
          "evidence": "Demonstrate a working feature, clear requirement and defensible design choice."
        },
        {
          "id": "5-8",
          "label": "5–8 years",
          "benefit": "Extend senior engineering into customer discovery and useful solution delivery.",
          "evidence": "Prepare a scoped use case with a baseline, acceptance test and working evidence."
        },
        {
          "id": "8-12",
          "label": "8–12 years",
          "benefit": "Connect architecture judgement, implementation and customer context.",
          "evidence": "Show a discovery-to-delivery story covering constraints, trade-offs and operating ownership."
        },
        {
          "id": "12-plus",
          "label": "12+ years",
          "benefit": "Choose this for hands-on field delivery. Management-first goals need a different balance of people, business and technical evidence.",
          "evidence": "Explain how you would validate a problem, guide a build and own its delivery evidence."
        }
      ]
    },
    {
      "id": "claude-associate-foundations-prep",
      "title": "Claude Associate Foundations Prep",
      "path": "/services/claude-associate-foundations-prep",
      "url": "https://manifoldailearning.com/services/claude-associate-foundations-prep",
      "summary": "Use structured study and practice to find gaps in foundational Claude concepts and exam reasoning. Exam preparation is separate from implementation experience and vendor exam registration.",
      "format": "Self-paced independent exam preparation; available now",
      "prerequisites": "Choose the certification level that matches your application and architecture experience. Independent preparation; vendor exam registration and fees are separate.",
      "enrolment_url": "https://pay.manifoldailearning.in/checkout?product=claude-associate-foundations-prep&return_url=https%3A%2F%2Fmanifoldailearning.com%2Fservices%2Fclaude-associate-foundations-prep",
      "enrolment_type": "checkout",
      "experience": [
        {
          "id": "0-2",
          "label": "0–2 years",
          "benefit": "Connect foundational Claude concepts and exam reasoning to a small application rather than relying on recall alone.",
          "evidence": "Explain a practice answer and connect the concept to an example you can run or inspect."
        },
        {
          "id": "2-5",
          "label": "2–5 years",
          "benefit": "Apply engineering experience to foundational Claude concepts and exam reasoning and use practice to choose what to study next.",
          "evidence": "Create a gap list from practice questions and connect a topic to a project decision."
        },
        {
          "id": "5-8",
          "label": "5–8 years",
          "benefit": "Use foundational Claude concepts and exam reasoning to test whether you can explain alternatives and failure cases at senior-engineer depth.",
          "evidence": "Explain a scenario answer through constraints, rejected alternatives and what you would validate."
        },
        {
          "id": "8-12",
          "label": "8–12 years",
          "benefit": "Calibrate architecture reasoning through foundational Claude concepts and exam reasoning. Keep design and delivery evidence alongside credentials.",
          "evidence": "Prepare a scenario review connecting the answer to boundaries, quality criteria and a verification step."
        },
        {
          "id": "12-plus",
          "label": "12+ years",
          "benefit": "Choose foundational Claude concepts and exam reasoning for a hands-on architecture goal. For management, prioritise decision quality over collecting exams.",
          "evidence": "Use a practice scenario to frame the questions, risks and evidence a technical review needs."
        }
      ]
    },
    {
      "id": "claude-developer-foundations-prep",
      "title": "Claude Developer Foundations Prep",
      "path": "/services/claude-developer-foundations-prep",
      "url": "https://manifoldailearning.com/services/claude-developer-foundations-prep",
      "summary": "Use structured study and practice to find gaps in developer decisions and application-level exam reasoning. Exam preparation is separate from implementation experience and vendor exam registration.",
      "format": "Self-paced independent exam preparation; available now",
      "prerequisites": "Choose the certification level that matches your application and architecture experience. Independent preparation; vendor exam registration and fees are separate.",
      "enrolment_url": "https://pay.manifoldailearning.in/checkout?product=claude-developer-foundations-prep&return_url=https%3A%2F%2Fmanifoldailearning.com%2Fservices%2Fclaude-developer-foundations-prep",
      "enrolment_type": "checkout",
      "experience": [
        {
          "id": "0-2",
          "label": "0–2 years",
          "benefit": "Connect developer decisions and application-level exam reasoning to a small application rather than relying on recall alone.",
          "evidence": "Explain a practice answer and connect the concept to an example you can run or inspect."
        },
        {
          "id": "2-5",
          "label": "2–5 years",
          "benefit": "Apply engineering experience to developer decisions and application-level exam reasoning and use practice to choose what to study next.",
          "evidence": "Create a gap list from practice questions and connect a topic to a project decision."
        },
        {
          "id": "5-8",
          "label": "5–8 years",
          "benefit": "Use developer decisions and application-level exam reasoning to test whether you can explain alternatives and failure cases at senior-engineer depth.",
          "evidence": "Explain a scenario answer through constraints, rejected alternatives and what you would validate."
        },
        {
          "id": "8-12",
          "label": "8–12 years",
          "benefit": "Calibrate architecture reasoning through developer decisions and application-level exam reasoning. Keep design and delivery evidence alongside credentials.",
          "evidence": "Prepare a scenario review connecting the answer to boundaries, quality criteria and a verification step."
        },
        {
          "id": "12-plus",
          "label": "12+ years",
          "benefit": "Choose developer decisions and application-level exam reasoning for a hands-on architecture goal. For management, prioritise decision quality over collecting exams.",
          "evidence": "Use a practice scenario to frame the questions, risks and evidence a technical review needs."
        }
      ]
    },
    {
      "id": "claude-architect-foundations-prep",
      "title": "Claude Architect Foundations Prep",
      "path": "/services/claude-architect-foundations-prep",
      "url": "https://manifoldailearning.com/services/claude-architect-foundations-prep",
      "summary": "Use structured study and practice to find gaps in foundation-level architecture choices and design reasoning. Exam preparation is separate from implementation experience and vendor exam registration.",
      "format": "Self-paced independent exam preparation; available now",
      "prerequisites": "Choose the certification level that matches your application and architecture experience. Independent preparation; vendor exam registration and fees are separate.",
      "enrolment_url": "https://pay.manifoldailearning.in/checkout?product=claude-architect-foundations-prep&return_url=https%3A%2F%2Fmanifoldailearning.com%2Fservices%2Fclaude-architect-foundations-prep",
      "enrolment_type": "checkout",
      "experience": [
        {
          "id": "0-2",
          "label": "0–2 years",
          "benefit": "Build application foundations first; use architecture preparation once you can explain a working request flow.",
          "evidence": "Identify the implementation and design foundations needed before architecture-level scenarios."
        },
        {
          "id": "2-5",
          "label": "2–5 years",
          "benefit": "Apply engineering experience to foundation-level architecture choices and design reasoning and use practice to choose what to study next.",
          "evidence": "Create a gap list from practice questions and connect a topic to a project decision."
        },
        {
          "id": "5-8",
          "label": "5–8 years",
          "benefit": "Use foundation-level architecture choices and design reasoning to test whether you can explain alternatives and failure cases at senior-engineer depth.",
          "evidence": "Explain a scenario answer through constraints, rejected alternatives and what you would validate."
        },
        {
          "id": "8-12",
          "label": "8–12 years",
          "benefit": "Calibrate architecture reasoning through foundation-level architecture choices and design reasoning. Keep design and delivery evidence alongside credentials.",
          "evidence": "Prepare a scenario review connecting the answer to boundaries, quality criteria and a verification step."
        },
        {
          "id": "12-plus",
          "label": "12+ years",
          "benefit": "Choose foundation-level architecture choices and design reasoning for a hands-on architecture goal. For management, prioritise decision quality over collecting exams.",
          "evidence": "Use a practice scenario to frame the questions, risks and evidence a technical review needs."
        }
      ]
    },
    {
      "id": "claude-architect-professional-prep",
      "title": "Claude Architect Professional Prep",
      "path": "/services/claude-architect-professional-prep",
      "url": "https://manifoldailearning.com/services/claude-architect-professional-prep",
      "summary": "Use structured study and practice to find gaps in professional architecture scenarios and trade-offs. Exam preparation is separate from implementation experience and vendor exam registration.",
      "format": "Self-paced independent exam preparation; available now",
      "prerequisites": "Choose the certification level that matches your application and architecture experience. Independent preparation; vendor exam registration and fees are separate.",
      "enrolment_url": "https://pay.manifoldailearning.in/checkout?product=claude-architect-professional-prep&return_url=https%3A%2F%2Fmanifoldailearning.com%2Fservices%2Fclaude-architect-professional-prep",
      "enrolment_type": "checkout",
      "experience": [
        {
          "id": "0-2",
          "label": "0–2 years",
          "benefit": "Build application foundations first; use architecture preparation once you can explain a working request flow.",
          "evidence": "Identify the implementation and design foundations needed before architecture-level scenarios."
        },
        {
          "id": "2-5",
          "label": "2–5 years",
          "benefit": "Build practical and architectural evidence before using professional scenarios to assess gaps.",
          "evidence": "Create a gap list from practice questions and connect a topic to a project decision."
        },
        {
          "id": "5-8",
          "label": "5–8 years",
          "benefit": "Use professional architecture scenarios and trade-offs to test whether you can explain alternatives and failure cases at senior-engineer depth.",
          "evidence": "Explain a scenario answer through constraints, rejected alternatives and what you would validate."
        },
        {
          "id": "8-12",
          "label": "8–12 years",
          "benefit": "Calibrate architecture reasoning through professional architecture scenarios and trade-offs. Keep design and delivery evidence alongside credentials.",
          "evidence": "Prepare a scenario review connecting the answer to boundaries, quality criteria and a verification step."
        },
        {
          "id": "12-plus",
          "label": "12+ years",
          "benefit": "Choose professional architecture scenarios and trade-offs for a hands-on architecture goal. For management, prioritise decision quality over collecting exams.",
          "evidence": "Use a practice scenario to frame the questions, risks and evidence a technical review needs."
        }
      ]
    },
    {
      "id": "claude-certification-full-pack",
      "title": "Claude Certification Full Pack",
      "path": "/claude-certification-full-pack",
      "url": "https://manifoldailearning.com/claude-certification-full-pack",
      "summary": "Use structured study and practice to find gaps in the progression across four current Claude exam-preparation courses. Exam preparation is separate from implementation experience and vendor exam registration.",
      "format": "Self-paced independent exam preparation; available now",
      "prerequisites": "Choose the certification level that matches your application and architecture experience. Independent preparation; vendor exam registration and fees are separate.",
      "enrolment_url": "https://pay.manifoldailearning.in/checkout?product=claude-certification-full-pack&return_url=https%3A%2F%2Fmanifoldailearning.com%2Fclaude-certification-full-pack",
      "enrolment_type": "checkout",
      "experience": [
        {
          "id": "0-2",
          "label": "0–2 years",
          "benefit": "Start with associate material and practical application work; progress to architecture as your evidence grows.",
          "evidence": "Explain a practice answer and connect the concept to an example you can run or inspect."
        },
        {
          "id": "2-5",
          "label": "2–5 years",
          "benefit": "Apply engineering experience to the progression across four current Claude exam-preparation courses and use practice to choose what to study next.",
          "evidence": "Create a gap list from practice questions and connect a topic to a project decision."
        },
        {
          "id": "5-8",
          "label": "5–8 years",
          "benefit": "Use the progression across four current Claude exam-preparation courses to test whether you can explain alternatives and failure cases at senior-engineer depth.",
          "evidence": "Explain a scenario answer through constraints, rejected alternatives and what you would validate."
        },
        {
          "id": "8-12",
          "label": "8–12 years",
          "benefit": "Calibrate architecture reasoning through the progression across four current Claude exam-preparation courses. Keep design and delivery evidence alongside credentials.",
          "evidence": "Prepare a scenario review connecting the answer to boundaries, quality criteria and a verification step."
        },
        {
          "id": "12-plus",
          "label": "12+ years",
          "benefit": "Choose the progression across four current Claude exam-preparation courses for a hands-on architecture goal. For management, prioritise decision quality over collecting exams.",
          "evidence": "Use a practice scenario to frame the questions, risks and evidence a technical review needs."
        }
      ]
    },
    {
      "id": "diamond-membership",
      "title": "Diamond Membership",
      "path": "/diamond-membership",
      "url": "https://manifoldailearning.com/diamond-membership",
      "summary": "A longer-term learning platform with the eligible course catalogue, future standard courses and Diamond-exclusive FDE. Optional Founder Access adds five private guidance sessions within 12 months.",
      "format": "Application-based membership; confirm current inclusions and availability",
      "prerequisites": "Choose a suitable first course or experience pathway for your immediate goal. Consider Diamond when you want sustained access across several areas.",
      "enrolment_url": "https://manifoldailearning.com/diamond-membership#pricing",
      "enrolment_type": "application",
      "experience": []
    }
  ],
  "pathways": [
    {
      "id": "0-2",
      "label": "0–2 years",
      "name": "AI Builder Launch",
      "roles": [
        "Junior AI Application Developer",
        "Software Engineer · LLM Applications",
        "Junior AI Evaluation Engineer"
      ],
      "included_courses": [
        "Agentic AI Developer Bootcamp",
        "AI Interview Playbook",
        "NVIDIA NCA-GENL Exam Prep"
      ],
      "sequence": [
        {
          "title": "Python foundations & automation",
          "url": "https://manifoldailearning.com/services/python-automation-for-agentic-ai-mlops",
          "why": "Use Developer Bootcamp’s included Python and API prep first. Choose this separate course only if you want additional programming and automation practice.",
          "evidence": "Run a small API call and explain a failure.",
          "optional": true,
          "included": false
        },
        {
          "title": "Agentic AI Developer Bootcamp",
          "url": "https://manifoldailearning.com/services/agentic-ai-developer-bootcamp",
          "why": "Build the application before worrying about advanced architectures. Connect models, tools, state and a real workflow.",
          "evidence": "Run a working agent and make one change independently.",
          "optional": false,
          "included": true
        },
        {
          "title": "AI Interview Playbook",
          "url": "https://manifoldailearning.com/services/agentic-interview",
          "why": "Turn your project experience into answers that show your contribution and reasoning.",
          "evidence": "Explain the request flow and one failure case.",
          "optional": false,
          "included": true
        },
        {
          "title": "NVIDIA NCA-GENL Exam Prep",
          "url": "https://manifoldailearning.com/services/nca-genl-exam-prep",
          "why": "Use associate-level NVIDIA preparation to consolidate concepts after practical work. Certification is optional.",
          "evidence": "Map concepts to your project, then assess exam readiness.",
          "optional": true,
          "included": true
        }
      ],
      "url": "https://manifoldailearning.com/agentic-ai-learning-paths#experience-0-2",
      "enrolment_url": "https://pay.manifoldailearning.in/checkout?product=pathway-ai-builder-launch&return_url=https%3A%2F%2Fmanifoldailearning.com%2Fagentic-ai-learning-paths%23experience-0-2"
    },
    {
      "id": "2-5",
      "label": "2–5 years",
      "name": "AI Engineer Progression",
      "roles": [
        "Agentic AI Engineer",
        "Generative AI Application Engineer",
        "AI Integration Engineer"
      ],
      "included_courses": [
        "Agentic AI Developer Bootcamp",
        "AI Architect System Design",
        "Production RAG System Design",
        "AI Interview Playbook",
        "NVIDIA NCP-AAI Exam Prep"
      ],
      "sequence": [
        {
          "title": "Agentic AI Developer Bootcamp",
          "url": "https://manifoldailearning.com/services/agentic-ai-developer-bootcamp",
          "why": "Add agent implementation to the APIs, databases and tests you already know. Skip this stage if you can already demonstrate it.",
          "evidence": "Trace a request from client to model, tool and response.",
          "optional": false,
          "included": true
        },
        {
          "title": "AI Architect System Design",
          "url": "https://manifoldailearning.com/services/ai-system-design",
          "why": "Learn to compare model, retrieval and workflow choices once you have a working implementation.",
          "evidence": "Write a design decision with a simpler alternative.",
          "optional": false,
          "included": true
        },
        {
          "title": "Production RAG System Design",
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          "why": "Make release decisions using repeatable tests and failure categories.",
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          "included": true
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          "included": true
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          "included": true
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}