01
Map
Model the APIs, repos, databases, devices, docs, business rules, and deployment constraints before writing code.
Use cases
Systems with real interfaces.
Zerg is strongest when the work spans fragmented systems: connectors, migrations, data flows, security queues, hardware validation, and operational workflows. The common thread is that code must understand the environment it lives in.
Operations
Operations workflows
Zerg turns recurring operational processes into software with state, permissions, integrations, validation, and human review built in.
workflowsinternal toolsapprovalsoperations
Security
CVE remediation
Zerg turns vulnerability findings into code changes, dependency updates, compatibility fixes, tests, and evidence that the issue is actually closed.
CVEdependency upgradescomplianceaudit trails
Data flows
ETL pipelines
Zerg builds extraction, transformation, validation, and monitoring loops around data sources whose schemas and semantics keep shifting.
ETLwarehousesschema evolutionquality checks
Integrations
Data connectors
Zerg builds and maintains software around APIs, SaaS platforms, databases, internal tools, and vendor systems that change on their own clocks.
APIsSaaSwebhooksschema drift
Migrations
Code migration
Zerg handles mechanical transformations, type migrations, dependency upgrades, and architecture refactors with tests and review checkpoints attached.
TypeScriptframeworkslegacy coderefactors
Common pattern
Map, build, prove, operate.
02
Build
Generate the connector, tool, migration, pipeline, or harness with the real system in view.
03
Prove
Validate with tests, probes, runtime signals, and reviewable artifacts instead of relying on a transcript.
04
Operate
Keep watching for drift so change becomes the next repair loop instead of a surprise incident.
Build with Zerg