Intermediate
26 entries tagged level Intermediate.
- Build on a single canonical model Learn the one-model architecture that lets humans and agents read a whole organization the same way: one typed property graph that documentation, governance, infrastructure, and agents all project into, a single query layer over it, and an MCP-native interface. By the end you'll be able to model your own estate as one graph rather than a rack of disconnected stores. Cogitave's own Core is the worked reference example throughout.
- Engineering standards for an AI-native org Learn the standards floor that governs every repository in an AI-native estate: the floor rules, naming, commits and versioning, testing and quality, API design, configuration, secure SDLC, CI/CD, and observability and reliability. By the end you'll be able to make changes that pass the org gates by default. Cogitave's own standards are the worked example throughout.
- Get started with Cogitave Massar Massar is the guardian agent that lets an authorized Cogitave operator open an audited terminal session on a customer device with no inbound port and no VPN. Understand the dial-out security model and how a session is bridged, then install, verify, and cleanly remove the agent on Linux and Windows using the real installers.
- Introduction to Cogitave Diyar Diyar is Cogitave's edge-autonomous platform for operating regulated field devices, where the device stays the sole authority over safety and evidence and each industry ships as a signed, pluggable solution. Understand what Diyar is, why safety and evidence stay local to the device, and how a device becomes a solution through signed profiles, verdict engines, and app packages.
- Patterns and golden paths Learn to build reuse-first: discover before you generate, start from a patterns catalog, inherit a repository's complete ruleset through the project baseline, and use decision guides for database, infrastructure, and model selection. By the end you'll reach for the named artifact before writing anything new. Cogitave's own patterns catalog is the worked example throughout.
- Design and version an API Shape a clean, consistent API against a clear API design standard - resources, standard methods, typed errors, cursor pagination, idempotency - then version and deprecate it under a versioning policy so no consumer is ever broken without consent.
- Apply the naming standards Name a new identifier, file, repo, or branch the way an AI-native org does - keyword-first, no redundant prefix, cased by role - and tell a functional keyword apart from a product codename, so your first artifact passes the naming gate by default.
- How a device becomes a Diyar solution Diyar turns a physical device into a certified solution through layered signed documents and firmware-compiled registries, not through custom code written per customer. A signed device profile configures the edge's hardware at boot; a certified verdict engine - a frozen product engine or one of the generic function blocks - decides pass or fail; and a three-document app package computes, offline, exactly what a device is authorized to observe, operate, or actuate. The module walks each of these three layers as they exist in the Diyar edge platform today, closes with one worked solution (ISPM-15) built entirely on that machinery, and states plainly where a capability is proven only against internal example fixtures rather than a field deployment - because that distinction is part of what you need to evaluate the product honestly.
- Read the pipeline that ships your change Follow a change from a pull request through the canonical CI stage set to a gated production deploy - the ordered gates a pipeline runs, why CI is the real gate, and how the deployment model promotes one signed artifact dev to staging to prod.
- Commits and versioning Write Conventional Commits whose type, scope, and breaking marker drive Semantic Versioning; see how release-please turns merged commits into a human-approved Release-PR, changelog, and tag; and how the trunk-based, protected-main model gates every release.
- Manage configuration and secrets Classify every value as a constant, a deployment parameter, or a secret; load configuration through the standard precedence chain, parsed once and fail-closed; and keep secrets out of git by referencing them at runtime and committing only encrypted-at-rest .env files.
- The one-model architecture Explain why an AI-native organization runs on one canonical property graph that humans and agents both query, what its node/edge model and identity scheme look like, and why a labeled property graph is the right substrate. Cogitave's Core is the concrete example.
- Safety and evidence in Diyar Cogitave Diyar drives real industrial heat-treatment equipment without depending on a network connection, and this module explains the three mechanisms that let it do so safely and provably. First, a layered, hardware-first fail-safe design where every failure path — a wedged CPU, a blind sensor, a power cut, a lost serial cable — falls back to the heater being off, never the reverse. Second, a request model where the cloud and any remote client can only ask the edge to start a run; the edge alone verifies and can refuse, and there is no primitive anywhere in the system that lets a remote party force actuation. Third, an evidence pipeline that journals every reading locally before it is ever published, chains it so tampering becomes detectable, layers a Merkle history tree on top so completeness can be proven without shipping an entire run's history, and lets the cloud independently reconcile what it received rather than trusting the edge's word. Throughout, the module states plainly which parts of this are built and verified today versus named, not-yet-shipped follow-ups.
- Install and operate the Massar agent This module installs and operates the Cogitave Massar agent: the small, cross-platform binary a customer runs on a device so an authorized Diyar operator can dial in for an audited remote terminal, with no inbound port and no VPN. You install it with the CLI installer for your OS - install.sh on Linux, install.ps1 on Windows - confirm it is verified and running as a service, trace a session from open to close, reproduce the whole relay locally with the project's own dev harness, and remove it cleanly when you are done. Two facts are stated plainly rather than glossed over: today's supported install targets are Windows and Linux only, and every end-to-end proof described here is the local dev harness, not a production Diyar deployment.
- A native MCP interface to the canonical model Read a canonical model's native MCP interface as the source of truth for how humans and agents query one org's estate - why the surface is native rather than adapted, the protocol contract it commits to, and the tools and resources you call. Cogitave's Core is the worked example.
- Observability and reliability Instrument a service with OpenTelemetry-spec traces, metrics, and logs, understand why agent traces are kept as evidence, and reason about reliability through SLIs, SLOs, error budgets, and the policy that turns a spent budget into a release freeze.
- Operate from Day 1 Describe the Day 1 operating model - the pinned inner loop and the flow-based outer loop - state the parity contract that keeps the inner loop honest, read Cogitave's flow-based ways of working and its ADR-0025 choice of flow over Scrum as one org's answer, and explain why the human gate stays an exception inside the flow.
- Project products into the canonical model See how content projects into one canonical model as typed, content-addressed nodes rather than separate silos - Cogitave's Core is the worked example - and how the fact registry's cite-not-restate rule and fact-drift scanner keep one owner per fact across your estate.
- Query your canonical model Learn how a query layer resolves a request against one canonical graph - lexical BM25 and dense HNSW vectors fused by Reciprocal Rank Fusion, a graph-aware rerank and ranking signals, and a bounded, read-only profile agents call directly. Cogitave Query is the reference implementation you'll trace.
- Reliability and SRE Reason about a service's reliability targets the way an SRE discipline does - set an SLO from the user's journey, compute the error budget it buys, and operate the service against that budget with burn-rate alerts, sustainable on-call, a toil cap, and the freeze that stops shipping when the budget runs out.
- Respond to incidents Walk the incident-response flow end to end - detection, severity declaration, single-commander roles, containment through a runbook, communication, recovery, and the blameless postmortem - and see how business continuity and disaster recovery extend the same discipline to a region loss or a destructive event.
- Run agentic operations Explain what agentic operations means - agents running an estate unattended inside rails - state the draft-vs-act rule that decides when an agent acts unattended versus when it stops for a human, and study Cogitave's own fleet of scheduled and operations agents as the worked example of the fleet you would build.
- Build with the secure SDLC State the security baseline - threat modeling, least privilege, and IAM - and follow the secure development lifecycle that shifts security left, so each stage of a change carries its own security gate instead of a check bolted on at the end.
- Test to the standard and pass the quality gate Learn how an AI-native org tests a change - the pyramid/trophy shape, the diff-coverage and mutation gates, flaky-test quarantine, the runnable harness, and the craftsmanship review bar - so you can test your own change and get it through the gate.
- Agent identity and capabilities Every Cogitave agent acts under its own identity inside an explicit least-privilege capability grant, in a sandbox, with every action recorded as evidence. What that model guarantees, and where a human is still required.
- What Yuva is Yuva is a from-scratch, agent-native sovereign unikernel in no_std Rust, with formally verified leaves and a boot that fails closed. What it is for, how it is verified, and exactly which parts are not live yet.
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