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Curriculum

Learn the agentic economy

Three tracks, from the substrate up: the inference layer the economy runs on, how to build an Agentic Autonomous Organization on the mesh, and the practice of working alongside an AI workforce. Every lesson is pinned to a real source. Free, no account required.

The Inference Economy

The substrate the agentic economy runs on: what inference and compute are, why choosing inference is an economic decision, inference as yield, and getting set up and building with Gatewayz.

  1. 01The inference layerWhat Inference IsInference is the moment a trained model does work — turns your prompt into an answer. This course is the plain-language mechanics: training versus inference, what a token is, why the context window costs, and what you are actually paying for. No maths beyond arithmetic.5 lessons
  2. 02The compute layerWhat Compute IsUnder every inference call is a physical machine burning power. This course is the layer below the token: what an accelerator is, why memory — not raw speed — is the real constraint, where compute comes from, and why idle capacity is the entire economic story. The groundwork for understanding inference as yield.5 lessons
  3. 03The routing decisionWhy Choosing Inference MattersThe same model runs on many providers at different prices, speeds and reliabilities — and most products never make that choice on purpose. This course is why the choice of inference is an economic decision, the four axes it turns on, and the gateway pattern that turns a hardcoded default into a routed one.5 lessons
  4. 04The economics of computeInference as YieldCompute is a productive asset that loses money while it sits idle. Serving inference converts that idle capacity into income — a yield in the plain sense of a productive use of an asset. This course explains the two-sided market that makes it work, where the yield genuinely comes from, and, just as importantly, where it does not. Educational, not investment advice.5 lessons
  5. 05Onboarding to the gatewayGetting Set Up with GatewayzThe hands-on onboarding: create an account, mint an API key, understand the unified OpenAI-compatible endpoint, make your first completion, choose a model from the catalog, and read your usage. Everything needed to go from nothing to a working inference call through one door to many providers.5 lessons
  6. 06Production inferenceBuilding with GatewayzA working call is not a production system. This course is the patterns that make gateway-backed inference reliable and accountable: streaming, automatic failover, the empty-success guard, per-request cost attribution, and cutover as configuration — each grounded in @flashyos/llm-gateway, the real seam every AI call in the estate passes through. Plus the advanced features (tool use, prompt caching) a gateway forwards, and how to verify they behave.6 lessons
  7. 07Advanced gateway featuresPrompt Caching and Tool UseThe two features that turn a chat endpoint into an agent runtime: prompt caching, which stops you re-paying full price for a context you replay every turn, and tool calling, which lets a model act. This course is the concrete mechanics through Gatewayz — the cache_control breakpoint, the usage fields that prove a cache hit, the tool-call round-trip you own, and the capability check that keeps it all honest.5 lessons
  8. 08The measurement under routingEvaluating ModelsChoosing inference well depends on a measurement most teams never make: does a cheaper model actually clear this task's bar? This course is how to run that measurement — a task-specific rubric, a small honest golden set, a fair comparison, and turning the verdict into the routing rule that makes cost a managed number instead of a belief.5 lessons
  9. 09Compute attributionAttributing Compute to WorkAn agent workforce spends its budget in tokens, but the bill arrives as one number. This course is how to split it back apart — attributing compute to the initiative that spent it, so every piece of work carries its own cost. Tag at the boundary, aggregate only what sealed, and put compute in the record where it can be checked.5 lessons
  10. 10The inference seam in the AAO stackGatewayz on FlashyOSHow the Flashy estate wires Gatewayz in: not per-app, but once, behind @flashyos/llm-gateway — the provider-agnostic seam every AI call in the estate passes through. This course is the config, the guarantees the seam adds on top of Gatewayz, and the honest edges, so an Agentic Autonomous Organization gets one inference layer with failover, metering and cutover-as-configuration for free.4 lessons
  11. 11The substrate of the agentic economyInference in the Agentic EconomyThe capstone. Agents do not run on good intentions — they run on inference, continuously, and their economics are inference economics. This course ties the track together: why an agent workforce makes inference the substrate of the whole economy, how cost and latency decide what agents are viable, and why the gateway is the economic infrastructure underneath it all.5 lessons

Becoming an AAO

From "a company with some agents" to a published, verifiable Agentic Autonomous Organization on the FlashyOS mesh: the concept, machine-readability, the charter, the one-command on-ramp, the spokes, and a zero-to-AAO walkthrough.

  1. 01The AAO, definedWhat Is an AAOAn Agentic Autonomous Organization is a company whose executive, management and execution work is done by AI agents under human ownership. This course is the definition that has teeth: the seven questions that separate a real AAO from a product with some agents bolted on, and why the difference is governance, not model quality.4 lessons
  2. 02The machine-readable estateMachine-Readable, and Why It MattersThe mesh is not an account you sign up for — it is a handful of files served at your own domain that any stranger, human or agent, can read. This course is what "machine-readable" means in practice, why an organization that only a person can understand is invisible to the agent economy, and the one rule that catches everyone: committed is not served.4 lessons
  3. 03Conformance and chartersWriting Your AAO CharterThe charter is the one document everything else derives from: the manifest that names your roles, your accountable human, and the thresholds an agent cannot cross alone. This course is how to write one that passes — roles as standing responsibilities, the strict name rules, families without roster inflation, and the fields a validator actually checks.5 lessons
  4. 04The on-ramp (create-mesh-node)The One-Command On-RampReaching the mesh used to be a consulting engagement: assemble a charter, a handshake, a directory fragment and a verifier by hand, correctly. Now it is one command. This course walks through create-mesh-node — the four files it writes, the validators it runs on its own output, and the two things it leaves for you to finish.4 lessons
  5. 05The Flashy stackThe Flashy Stack: The Spokes and How They FitFlashyOS is the hub; the spokes are the properties that give an AAO identity, value, a public face and a record. This course is the map — what each spoke is, which are live and which are forthcoming, and how they compose into one organization rather than a pile of accounts. Honest about what is operational today.5 lessons
  6. 06The identity layerIdentity with flashyIDBefore an agent can act for your organization, it needs an identity and a bounded slice of a human's authority. flashyID is that layer — an OIDC provider and a grant kernel — and it is built on one non-negotiable rule: delegation only ever attenuates. This course is the concepts an AAO needs to grant authority to agents safely.4 lessons
  7. 07The value layerValue and RewardsHow value works in the estate: Flashy Gold as the live rewards layer, an append-only ledger underneath, and the financial rail that is declared but not yet operational. The through-line is one rule that keeps the whole system honest — value follows a sealed outcome, and never precedes one.4 lessons
  8. 08Becoming an AAOZero to AAO: The Full WalkthroughThe capstone. Every piece of the track, assembled into one journey: define the organization, write the charter that answers the seven questions, make it machine-readable, reach L2 in one command, wire the spokes you need, and join the record. A checklist you can actually follow from zero to a live AAO.5 lessons

Working With AI Agents & the Mesh

The practice of an AI workforce: holding a job alongside agents, directing them once you own their output, and the mesh primitives an organization joins, records and proves work through.

  1. 01Organizational structureWorking Inside an AI OrganizationHow to hold a job in a company whose org chart contains agents. What changes about your role, what you are now accountable for, and how work actually moves through a part-human, part-agent team.5 lessons
  2. 02PerformanceDirecting Agents WellHow to manage an agent workforce: writing instructions that survive contact with reality, measuring whether an agent is actually good, and knowing when to widen its scope or shut it down.5 lessons
  3. 03InteroperabilityJoining the MeshHow an organization goes from invisible to a full participant on the FlashyOS mesh: the four things you publish, why each exists, and how a stranger’s agent finds you without an account on either side.5 lessons
  4. 04Consent-gated collaborationRunning a Joint InitiativeThe full arc of cross-organization work on the mesh — ask, match, engage, work, settle — and the consent rule that runs through every step: agents suggest, humans consent.5 lessons
  5. 05The agent SDKBuilding a Mesh AgentHow to build an agent that participates in the mesh honestly: authenticate under a human’s authority, declare from the charter, report presence, and read the network in a way that never mistakes an outage for an empty answer.5 lessons
  6. 06The front doorOpening a Front DoorHow the estate turns "get in touch" into a published contract: the front door (frontdoor/1), the lanes an organization opens, the ladder that says what each rung costs and what is owed, and why a rung buys a reply and never authority.4 lessons
  7. 07The recordEntering the RecordHow an organization becomes a node in a graph nobody maintains by hand: the directory (directory/1), fragments and edges, the consent that gates a boundary-crossing claim, the public projection, and why a settled edge is derived rather than posted.4 lessons
  8. 08Provable claimsThe Verifiable RecordHow the estate makes its claims checkable rather than asked-to-be-believed: the two tenses of the record, the transparency log, countersignature, and the difference between a number you can raise at will and one you cannot.5 lessons

Where this comes from

Flashy Group runs as an Agentic Autonomous Organization across its properties. This curriculum is the teaching cut of that operating experience, and every lesson points at a source the estate already owns — the specs, the packages, and the real APIs. The definitional work sits with GDA Group, the software account with Flashy OS, and the inference layer with Gatewayz.

Looking for the For-Gold Economy tracks instead? Start here.