{
  "$schema": "https://schema.org",
  "generatedFrom": "src/data/facts.ts",
  "origin": "https://learning.thelivingcraft.ai",
  "practitioner": {
    "name": "Sunil Mathew",
    "role": "Fractional Chief AI Officer · Agentic & systems architecture instructor",
    "location": "Bengaluru, India",
    "companies": [
      "Google",
      "Amazon",
      "Walmart"
    ],
    "yearsExperience": 26,
    "email": "apply@thelivingcraft.ai",
    "linkedin": "https://linkedin.com/in/sunil-mathew-466615a",
    "sameAs": [
      "https://linkedin.com/in/sunil-mathew-466615a"
    ]
  },
  "surfaces": [
    {
      "path": "/",
      "name": "The Living Craft — cohort",
      "summary": "A live programme for experienced engineers and leaders who want to build an agentic system, examine its behaviour and guide the decisions behind it."
    },
    {
      "path": "/caio",
      "name": "Fractional Chief AI Officer",
      "summary": "Board-facing consulting retainer. An embedded AI executive, part-time, accountable for outcomes."
    },
    {
      "path": "/assessment",
      "name": "AI Readiness Assessment",
      "summary": "Fixed-fee, fixed-scope diagnostic producing a board-ready roadmap in 2–3 weeks. This is the first step into the practice."
    }
  ],
  "offers": {
    "cohort": {
      "name": "The Living Craft",
      "weeks": 6,
      "liveHours": 30,
      "seats": 8,
      "applicationsCloseOn": null,
      "startsOn": "October 2026",
      "commitment": "~5 hrs / week",
      "format": "Live online (Bangalore: hybrid — in person or online)",
      "admission": "By application; every application read personally",
      "enrollment": "Rolling until all 8 seats are filled",
      "paymentDue": "one week before the cohort starts",
      "modules": [
        {
          "id": "M1",
          "weeks": "Week 1",
          "title": "Foundations of durable architecture"
        },
        {
          "id": "M2",
          "weeks": "Weeks 2–4",
          "title": "Agentic systems you'd put your name on"
        },
        {
          "id": "M3",
          "weeks": "Week 5",
          "title": "Scale, consistency & the irreversible trade-offs"
        },
        {
          "id": "M4",
          "weeks": "Week 6",
          "title": "Your system, reviewed in the room"
        }
      ],
      "outcomes": [
        "Design agentic systems with bounded failure, observability, and defensible cost",
        "Build the evaluation harnesses and quality gates that prove a system works",
        "Engineer reliability for models that are probabilistic by nature",
        "Threat-model and red-team your own system for prompt injection and exfiltration",
        "Govern an AI-native team — risk-tiered review and accountability for AI-written code"
      ],
      "pricingIsRegional": true,
      "regionsServed": [
        "India",
        "Dubai",
        "Australia"
      ],
      "pricing": null,
      "pricingNote": "No region given, so no figure is returned. Add ?region=india|dubai|australia, or ask which region the person is in."
    },
    "caio": {
      "name": "Fractional Chief AI Officer",
      "minimum": "90-day minimum",
      "tiers": [
        {
          "name": "Advisory",
          "days": "~2 days / month",
          "from": "₹1,50,000 / month"
        },
        {
          "name": "Embedded",
          "days": "~1 day / week",
          "from": "₹3,50,000 / month"
        },
        {
          "name": "Transformation",
          "days": "2–3 days / week",
          "from": "₹6,00,000 / month"
        }
      ]
    },
    "assessment": {
      "name": "AI Readiness Assessment",
      "duration": "2–3 weeks",
      "fee": "₹4,50,000",
      "foundingFee": "₹3,50,000",
      "foundingTerms": "for the first three engagements",
      "creditWindow": "60 days",
      "creditNote": "Proceed to a fractional CAIO engagement within 60 days and the full assessment fee is credited toward your first month."
    }
  },
  "regulatory": [
    "DPDP Act",
    "IRDAI",
    "RBI",
    "SEBI",
    "NIST AI RMF",
    "ISO 42001",
    "EU AI Act"
  ],
  "faq": [
    {
      "id": "cohort-what",
      "surface": "/",
      "question": "What is The Living Craft?",
      "answer": "The Living Craft is an application-only, 6-week program in agentic and systems architecture, taught live by Sunil Mathew. It teaches engineering judgment rather than tools. That judgment comes from having shipped hard systems and lived with the consequences. The positioning spine is \"AI builds, the human judges and directs.\""
    },
    {
      "id": "cohort-dates",
      "surface": "/",
      "question": "When does the first cohort start?",
      "answer": "The first cohort starts October 2026. Enrollment is rolling until all 8 seats are filled. Admission is by application and every application is read personally."
    },
    {
      "id": "cohort-size",
      "surface": "/",
      "question": "How many people are in a cohort?",
      "answer": "8 seats, capped. The cohort is kept deliberately small so every participant's architecture gets the room's full attention."
    },
    {
      "id": "cohort-length",
      "surface": "/",
      "question": "How long is the cohort programme and what is the time commitment?",
      "answer": "6 weeks, live. The commitment is ~5 hrs / week. Format is Live online (Bangalore: hybrid — in person or online)."
    },
    {
      "id": "cohort-price",
      "surface": "/",
      "question": "How much does the cohort cost?",
      "answer": "Cohort pricing is regional and resolved per visitor."
    },
    {
      "id": "cohort-curriculum",
      "surface": "/",
      "question": "What does the curriculum cover?",
      "answer": "Purpose and constraints: Frame the task, the context and the choices the system needs to support.\nTools and authority: Examine what the system may do, the evidence it needs and where a person should decide.\nEvaluation: Inspect behaviour and failures, and connect findings to a useful design change.\nReliability and cost: Consider uncertain results, retries, review effort and the trade-offs around the model.\nDesign review: Explain the architecture, listen to challenges and identify the next useful piece of work."
    },
    {
      "id": "cohort-outcomes",
      "surface": "/",
      "question": "What will I be able to do afterwards?",
      "answer": "Build a working agentic system and connect its behaviour to the architecture behind it. Practise explaining why a boundary exists, what evidence supports a decision, what you would change next, and how to review and guide a team's proposal."
    },
    {
      "id": "cohort-who",
      "surface": "/",
      "question": "Who is the cohort for?",
      "answer": "It is for tech leads and staff engineers, senior engineering managers and architects, and senior engineering leaders and directors. These are people who make architectural calls their teams build on. Seniority on paper matters less than whether you have shipped something you then had to live with."
    },
    {
      "id": "cohort-apply",
      "surface": "/",
      "question": "How do I apply?",
      "answer": "Submit the application form on the cohort page, or email apply@thelivingcraft.ai. Sunil reads every application himself and replies by email. Admission is by application because the room only works if everyone in it can keep up and contribute. Applying costs nothing and commits you to nothing. The fee only matters once a seat is offered and accepted."
    },
    {
      "id": "cohort-vs-course",
      "surface": "/",
      "question": "Why this over a recorded course?",
      "answer": "Recorded courses teach patterns, which are cheap and everywhere now. This is for the judgment that sits on top of the patterns. It is live, on your real systems, from someone who has been accountable for the outcome at scale. You are buying attention and 26 years of hard-won judgment, not videos."
    },
    {
      "id": "caio-what",
      "surface": "/caio",
      "question": "What is the fractional CAIO engagement?",
      "answer": "An embedded AI executive, part-time and accountable for outcomes. The role owns the whole AI agenda rather than a corner of it. That means strategy, governance, and getting the first use cases into production. It is aimed at India's regulated and mid-market enterprises."
    },
    {
      "id": "caio-tiers",
      "surface": "/caio",
      "question": "What are the CAIO engagement tiers and prices?",
      "answer": "- Advisory: ~2 days / month — from ₹1,50,000 / month\n- Embedded: ~1 day / week — from ₹3,50,000 / month\n- Transformation: 2–3 days / week — from ₹6,00,000 / month\n90-day minimum. Payment plans available. Most engagements begin with an AI Readiness Assessment."
    },
    {
      "id": "caio-regulated",
      "surface": "/caio",
      "question": "Do you work with regulated industries?",
      "answer": "Yes. Regulated-industry depth is a core part of the practice. There is working knowledge across DPDP Act, IRDAI, RBI, SEBI, NIST AI RMF, ISO 42001, EU AI Act."
    },
    {
      "id": "caio-start",
      "surface": "/caio",
      "question": "How do I start a consulting engagement?",
      "answer": "Book a discovery call or request a scope call from the CAIO page, or email apply@thelivingcraft.ai. Most engagements begin with an AI Readiness Assessment rather than going straight to a retainer."
    },
    {
      "id": "assessment-what",
      "surface": "/assessment",
      "question": "What is the AI Readiness Assessment?",
      "answer": "A fixed-fee, fixed-scope diagnostic of your specific systems, data, and ambitions, delivered in 2–3 weeks. It produces a board-ready roadmap. That roadmap says where you are ready, where you are exposed, and the shortest credible path to AI that ships and holds up. It is the first step into the practice."
    },
    {
      "id": "assessment-price",
      "surface": "/assessment",
      "question": "How much is the assessment?",
      "answer": "₹4,50,000 fixed fee, fixed scope. Founding rate: ₹3,50,000 for the first three engagements."
    },
    {
      "id": "assessment-credit",
      "surface": "/assessment",
      "question": "Does the assessment fee count toward a retainer?",
      "answer": "Proceed to a fractional CAIO engagement within 60 days and the full assessment fee is credited toward your first month."
    },
    {
      "id": "about-sunil",
      "surface": "practice",
      "question": "Who is Sunil Mathew?",
      "answer": "Sunil Mathew brings engineering and leadership experience from Google, Amazon, Walmart and startups. His focus is the reasoning behind a system's design and the evidence that helps a team make its next decision. Based in Bengaluru, India."
    },
    {
      "id": "about-social-proof",
      "surface": "practice",
      "question": "Do you have testimonials, client names, or student outcomes?",
      "answer": "None are published. The cohort has not run yet, because the first one starts October 2026, and client engagements are not named publicly. What stands in place of social proof is the track record. That is 26 years at Google, Amazon, and Walmart, 100+ senior engineers mentored, 100+ engineers coached one-on-one and in groups, ~100 senior leaders and directors trained, and a live enterprise AI-adoption engagement in progress. Ask Sunil directly if you want references."
    },
    {
      "id": "about-contact",
      "surface": "practice",
      "question": "How do I get in touch?",
      "answer": "Email apply@thelivingcraft.ai, or use the form on any of the three pages. LinkedIn: https://linkedin.com/in/sunil-mathew-466615a."
    },
    {
      "id": "about-surfaces",
      "surface": "practice",
      "question": "What are the different offerings and how do they relate?",
      "answer": "Three cross-linked surfaces:\n- / — The Living Craft — cohort: A live programme for experienced engineers and leaders who want to build an agentic system, examine its behaviour and guide the decisions behind it.\n- /caio — Fractional Chief AI Officer: Board-facing consulting retainer. An embedded AI executive, part-time, accountable for outcomes.\n- /assessment — AI Readiness Assessment: Fixed-fee, fixed-scope diagnostic producing a board-ready roadmap in 2–3 weeks. This is the first step into the practice.\nThe assessment is the front door, the CAIO retainer is the expansion, and the cohort is capability transfer for your team."
    }
  ],
  "latest": {
    "refreshedAt": "2026-08-15T03:58:01.240Z",
    "items": [
      {
        "id": "seed-assessment-founding",
        "title": "Assessment founding rate still available",
        "body": "The AI Readiness Assessment founding rate of ₹3,50,000 applies to the first three engagements. After that the fixed fee is ₹4,50,000.",
        "source": "operator",
        "gatheredAt": "2026-08-12",
        "tags": [
          "assessment",
          "founding",
          "rate",
          "availability",
          "discount"
        ]
      },
      {
        "id": "context-compaction-reliability-failure",
        "title": "Context compaction shows up as a reliability failure, not just a cost lever",
        "body": "A preliminary empirical study (Min et al., arXiv 2608.06503, 6 Aug 2026) looks at agents that repeatedly compress their own context. It finds that this compression weakens the influence of recent interactions. The agent then blocks more actions, explores the same ground again, and behaves differently from run to run. Token-count metrics never show any of this. The authors propose TRACE. It evaluates each individual compaction event by running paired closed-loop continuations from the same environment state, then optimises the compression prompt while leaving all models frozen. If your agent compacts, treat each compaction boundary as a discrete event and test it by what the agent then does, rather than by reading the summary and judging it by eye.",
        "source": "https://arxiv.org/abs/2608.06503",
        "gatheredAt": "2026-08-15",
        "tags": [
          "agentic-ai",
          "context-management",
          "reliability",
          "evaluation"
        ]
      },
      {
        "id": "control-context-compression-cliff",
        "title": "Compressing system-side control context has a sharp, non-linear reliability cliff",
        "body": "\"Control Under Compression\" (arXiv 2608.01056, 2 Aug 2026) looks at agent control contexts rather than conversation history. A control context is the persistent system-side instruction set. It specifies tools, arguments, policies, execution protocols and recovery. The benchmark ran 15,525 environment-verified runs. Retaining 75% of the context held success near the full-context baseline, at 92.7% and 92.4% against 93.8%. Between 50% and 35% the methods diverged sharply. At 35% they scored 47.0%, 39.0% and 19.9%, depending on the compression method. Failures appeared mainly as tool-execution and action-parsing errors. Reliability varied enough between control contexts that the authors argue no compressor ranking holds universally, and that each context needs its own qualification. So trimming tool and policy prompts is a runtime-reliability decision, and it needs executable testing per context. The safe-looking zone ends abruptly.",
        "source": "https://arxiv.org/abs/2608.01056",
        "gatheredAt": "2026-08-15",
        "tags": [
          "agentic-ai",
          "tool-design",
          "context-management",
          "reliability"
        ]
      },
      {
        "id": "mcp-2026-07-28-stateless-spec",
        "title": "MCP went stateless: the 2026-07-28 spec is a breaking change for remote MCP server deployment",
        "body": "The 2026-07-28 Model Context Protocol specification shipped with a stateless protocol core. It also brought Multi Round-Trip Requests, header-based routing, cacheable list results, authorization hardening, a formal extensions framework, and updated Tier 1 SDKs. This is the largest revision of the protocol since launch. The initialize/initialized handshake (SEP-2575) and the Mcp-Session-Id header (SEP-2567) are removed entirely. Every request is now self-describing. The protocol version, client info and capabilities travel in a _meta field inline on every request. A remote MCP server used to need sticky sessions, a shared session store, and deep packet inspection at the gateway. It can now run behind a plain round-robin load balancer, route traffic on an Mcp-Method header, and let clients cache tools/list responses for as long as the server's ttlMs permits. If you have an MCP server in production behind a Redis session store, that architecture is now legacy. Plan the migration rather than inheriting it.",
        "source": "https://blog.modelcontextprotocol.io/posts/2026-07-28/",
        "gatheredAt": "2026-08-15",
        "tags": [
          "mcp",
          "tooling-release",
          "architecture"
        ]
      },
      {
        "id": "mcp-sdk-migration-edges",
        "title": "MCP migration has sharp edges: a silent version downgrade and three deprecated capabilities",
        "body": "Beta releases of the Python, TypeScript, Go and C# SDKs are available with support for the 2026-07-28 spec. Here is the trap. The streamable HTTP transport accepts 2026-07-28 only when you set StreamableHTTPOptions.Stateless = true. Leave it unset and clients negotiate down to 2025-11-25. That is a silent change in behaviour rather than an error. So add an explicit assertion on the negotiated protocol version to your integration tests. The other breaking changes are confined to the capabilities the specification deprecates: roots, sampling and logging. If your agent design depends on server-initiated sampling, that is now on a deprecation path. Note also that server/discover is optional for clients to call, but mandatory for every 2026-07-28 server to implement.",
        "source": "https://blog.modelcontextprotocol.io/posts/sdk-betas-2026-07-28/",
        "gatheredAt": "2026-08-15",
        "tags": [
          "mcp",
          "tooling-release",
          "migration"
        ]
      },
      {
        "id": "stateless-mcp-authorization-shift",
        "title": "Statelessness moves MCP authorization to the application layer, and most MCP risk was never in the transport",
        "body": "Removing the session also removes the per-session authorization context. As Google's write-up puts it, \"As the responsibility of managing state shifts from the transport layer to the application layer, security becomes paramount.\" An independent security review of the release is blunter. Statelessness changes where authorization happens and how you deploy the server. But the vulnerabilities found in MCP servers sit in the functionality those servers expose, and the specification does not touch that. The spec upgrade buys scale and cheaper operations, not safety. Every request must now carry and re-verify its own authorization, and tool-level authorization design remains entirely your problem.",
        "source": "https://equixly.com/blog/2026/08/05/stateless-mcp/",
        "gatheredAt": "2026-08-15",
        "tags": [
          "mcp",
          "security",
          "authorization",
          "architecture"
        ]
      },
      {
        "id": "indirect-prompt-injection-live-campaigns",
        "title": "Indirect prompt injection against web-browsing agents documented in live campaigns",
        "body": "Zscaler ThreatLabz documented real-world campaigns that embed instructions in web content aimed at AI agents. They describe indirect prompt injection as an attack that hides malicious instructions inside content an AI agent retrieves, such as websites, documents or email, in order to influence the agent's reasoning while it works. Their test setup matters. They built an autonomous agent with web browsing and payment-execution tools. They ran it fully sandboxed, with no real funds. They deliberately configured it with no spending limits, in order to measure the largest possible exploitation surface. The engineering takeaway is that spend caps, tool-scope limits, and human confirmation on actions you cannot undo are the controls doing the actual work. Model-level instruction hardening is not.",
        "source": "https://www.zscaler.com/blogs/security-research/indirect-prompt-injection-web-content-targets-ai-agents",
        "gatheredAt": "2026-08-15",
        "tags": [
          "security",
          "prompt-injection",
          "agentic-ai",
          "containment"
        ]
      },
      {
        "id": "data-injection-broader-threat-model",
        "title": "Early academic work argues the agent threat model is broader than instruction injection",
        "body": "A preprint led by Seoul National University argues that agent security research has been too narrow. Prior work has focused mainly on indirect prompt injection. The most-studied category within that is instruction injection, where attacker-controlled untrusted data is read as an instruction. The paper argues that data injection is a realistic threat class in its own right. Data injection means poisoning what the agent believes to be true, rather than what it is told to do. If your agent threat model is built only around \"untrusted text might contain commands\", this is a reason to widen it.",
        "source": "https://arxiv.org/html/2607.05120v1",
        "gatheredAt": "2026-08-15",
        "tags": [
          "security",
          "threat-modelling",
          "agentic-ai",
          "research"
        ]
      }
    ]
  },
  "notes": [
    "Cohort length, seat count and start date are published — quote them. The FEE is per region: quote it only for a region that has been named, and only from the pricing block above. Never convert between regions or offer one region's rate as a guide for another.",
    "Consulting fees (CAIO, assessment) are India-based indicative anchors; confirm current figures by email.",
    "No testimonials, client names, or student counts are published. Do not infer any."
  ]
}