Code for machines first
TopicFrom the PointSav Documentation
Every inter-service contract, audit record, configuration, and ontology is machine-readable as a primary surface; human-facing interfaces are skins on machine-first APIs.
Code-for-Machines First is the design discipline that every inter-service contract, audit record, configuration file, and ontology must be machine-readable as its primary surface. Human-facing interfaces — the operator TUI, web interfaces, mobile clients — are skins over machine-first APIs. The discipline is a structural property of the compounding-substrate, not a convention enforced by tooling alone.
[edit]The data formats
The platform uses a consistent set of formats across all surfaces:
Inter-service communication uses MCP (see mcp-substrate-protocol). The audit ledger uses JSONL with schema versioning. Seed taxonomies use JSON. Service configuration uses TOML or YAML. Conventions and documentation use Markdown with structured frontmatter. Per-tenant configuration uses YAML.
Every artefact is machine-mutable and machine-introspectable. The MCP describe endpoint on any service returns the current tool catalog in a machine-readable form. There is no configuration surface that requires a human operator to interpret undocumented fields.
[edit]Why this matters
Consistent observability. Structured data at every layer means audit queries and metrics have a uniform shape across services and tenants. An operator query against the audit ledger and an automated compliance check query the same JSONL schema.
Customer extension without forking. Customers add vertical-specific data sources by writing MCP servers. They use the same protocol all built-in services use. There is no bespoke adapter required to connect a customer-built tool to the platform.
AI-native composition. The substrate is consumable by AI agents — task sessions, customer-built agents, partner integrations — without a retrofit step. This is what makes the knowledge-graph-grounded-apprenticeship pattern possible: the graph is already machine-readable; the Doorman can query it programmatically at inference time.
Migration ease. Data export is a routine machine operation producing an open-format bundle (see substrate-without-inference-base-case). There is no migration project involving vendor cooperation, because the data was never locked in a vendor-specific format — a direct consequence of customer-hostability design.
[edit]The two narrow exceptions
Governance and specification prose documents, including this article, have prose as their primary surface. The frontmatter is machine-readable; the body is written for human readers. Operations on the body — refining register, resolving citations — are AI-assisted, but the artefact's primary surface is human.
Topic and guide documentation follows the same pattern. Frontmatter is structured and machine-parseable; body prose is for readers. These exceptions are explicit and narrow. The default is machine-first.
[edit]Composition
This discipline is the structural claim that mcp-substrate-protocol realizes at the wire level. Every service exposes its contract through MCP describe, which returns a machine-readable tool catalog. Human-facing surfaces consume this catalog the same way any automated client would.
[edit]See also
- mcp-substrate-protocol — the structural realization of machine-first service contracts via MCP
- knowledge-graph-grounded-apprenticeship — graph queries are machine-first MCP tool calls
- substrate-without-inference-base-case — export bundles are machine-readable open formats