Turn profile-extraction requests into governed engineering work

A team-oriented guide to requirements, source authorization, profile schemas, matching, observability, privacy, and release evidence without scraping instructions.

Educational research only. LinkedIn account access remains decision-gated. No DewEngine LinkedIn connector is approved or implemented.

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Discovery

Write the user outcome before an extraction ticket

A product manager may need a verified identity link, a recruiter may need job-related context, and a CRM user may need a proposed company update. These are distinct requirements. DewEngine's LinkedIn profile target has no approved connector or implementation. The team should specify purpose, fields, actor, destination, freshness, retention, and fallback before discussing any provider mechanism.

Convert broad extraction language into field-level jobs
Reject requirements that depend on bypassing access controls

Architecture decision

Make the authorization gate visible in the design

The architecture record should name the proposed account product, access path, customer role, legal questions, provider authorization, and what remains disabled. It must explicitly prohibit scraping, reverse engineering, private-request replay, session theft, and anti-detection tactics. If the gate does not clear, manual linking or another licensed source should complete the core workflow without a hidden degraded mode.

Keep provider selection outside the canonical profile model
Use capability flags to prevent accidental exposure

Data contract

Agree on identity and absence semantics

Define opaque internal IDs, account-scoped provider references, observed timestamps, optional fields, provider extensions, and source lineage. Decide how not requested, unsupported, redacted, inaccessible, and absent values differ. Customer-entered fields and derived classifications stay separate. This contract lets frontend, backend, analytics, privacy, and support teams reason about the same record without calling it complete.

Contract-test partial profiles before full fixtures
Never store names or URLs as immutable identity keys

Pipeline

Stage, match, review, and commit

An authorized observation first enters tenant-scoped staging with provenance. Matching proposes a customer record using provider identity and customer-known evidence. A user or bounded rule accepts the link, then an idempotent commit writes selected fields according to source precedence. Failed pages and duplicates remain visible. No import event should automatically authorize an invitation, message, candidate stage, or sales sequence.

Make ambiguous matches reversible
Separate enrichment completion from downstream action

Operations

Instrument state without logging personal content

Metrics should cover run age, page progress, duplicates, field presence, match review, stale observations, account health, throttling, and deletion, using safe identifiers. Logs and traces must not contain authorization, profile bodies, message content, or unnecessary URLs. Support can inspect source version, failure class, and correlation path through audited tools rather than opening a broad data view.

Redact raw provider details from customer errors
Alert when a connector continues after account stop

Definition of done

Require legal, product, and technical proof

Done means counsel and provider approval, eligible-account conformance, tenant isolation, field fixtures, duplicate and ambiguity tests, partial recovery, restriction, reconnect, retention, correction, export, deletion, security review, audit, and kill-switch evidence all pass. Documentation must be generated from the released manifest. A successful parser or internal prototype would prove only that code ran, not that LinkedIn profile access may ship.

Assign owners to every open gate
Keep evidence dated and invalidate it after contract changes

Questions

Before you build.

Which team should own LinkedIn profile identity matching?+

The host product owns customer identity decisions, while the connector owns source-scoped observations and provenance. Security and privacy review the boundary; no global matching service should silently merge identities across tenants.

What can engineers build while LinkedIn access is gated?+

They can define the canonical schema, staging and review workflow, tenant checks, capability discovery, privacy lifecycle, fake-provider fault tests, and alternative authorized inputs without collecting LinkedIn data or implying availability.

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Does this match the workflow your users need?

DewEngine is in development. Real use cases decide what ships first.

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Turn profile-extraction requests into governed engineering work

Write the user outcome before an extraction ticket

Make the authorization gate visible in the design

Agree on identity and absence semantics

Stage, match, review, and commit

Instrument state without logging personal content

Require legal, product, and technical proof

Before you build.

Related guides

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Replace the company-scraper idea with a lawful CRM intake design

Design a governed lead-intake workflow without automated extraction

Does this match the workflow your users need?