Turn Approved Website Briefs into Release-Review Evidence
Implement an approved marketing-site brief in an authorized repository, verify the actual change set, and prepare traceable release and rollback evidence without deploying it.
Reusable AI capabilities
Use focused capabilities powered by published Amo.ng prompts and workflows. Skills package what to provide, how to use the source asset, and what completion looks like—without pretending to run autonomously.
Implement an approved marketing-site brief in an authorized repository, verify the actual change set, and prepare traceable release and rollback evidence without deploying it.
Implement an approved lead-routing contract across CRM sandbox configuration and disabled n8n staging orchestration, with synthetic reconciliation, retry evidence, and recovery controls.
Carry an owner-approved metric contract through an internal dashboard and disabled recurring report, then reconcile both outputs and prepare evidence for controlled release.
Evaluate an educational AI acquisition against learning need, vendor evidence, accessibility, student-data controls, security, equity, total cost, lock-in, and accountable approval requirements.
Trace a learner’s quantitative work to the earliest unsupported step, test competing error explanations, and design a fresh transfer task that measures reasoning rather than answer imitation.
Maintain a proportionate, honest record of material AI inputs, decisions, source checks, revisions and learning reflection without declaring authorship or policy compliance.
Apply a repeatable evidence gate to a research handoff covering provenance, permissions, code, environment, dependencies, seeds, run instructions, expected outputs and reproduction gaps.
Audit international SEO implementations for reciprocal hreflang clusters, locale codes, canonicals, redirects, indexability, sitemap coverage, and rendered output using crawl and page evidence.
Turn disputed or ambiguous business metrics into governed, testable semantic contracts with explicit grain, calculation rules, lineage, ownership, access constraints, and change-control expectations.
Diagnose Next.js hydration mismatches and server/client rendering failures by tracing observable symptoms to route, component, data, environment, and browser-only boundaries, then define the smallest safe repair and verification evidence.
Evaluate proposed marketing and brand claims against audience interpretation, supporting evidence, disclosures, expiry triggers, and approval needs to produce a claim-control matrix for safer campaign use.
Investigate sample ratio mismatch and related experiment assignment anomalies by tracing expected allocation through randomization, exposure logging, identity joins, telemetry, and analysis eligibility before trusting results.