[ 01.1 // SYSTEM SPECIFICATION ] / B2B SALES AUTOMATION · HUMAN REVIEW BEFORE OUTBOUND
An engineered workflow that synthesises buying signals, enriches account profiles, and stages structured human-in-the-loop review points before outbound communications or CRM updates.
[01 // PROBLEM DOMAIN & TARGET OPERATORS] Systemic failure modes of unmanaged SDR automation.
Standard sales automation stacks create severe hidden liabilities: low-quality scraping causes CRM database degradation, hallucinated company references damage brand trust, and high-frequency generic emails trigger domain blacklisting.
When prospect triage is done manually, high-value strategic signals slip through unnoticed. Conversely, handing entire outreach loops over to unsupervised generative scripts introduces non-deterministic hallucinations directly into sensitive executive conversations.
CRITICAL OPERATING BOTTLENECKS IDENTIFIED
- CRM record pollution: stale job changes, duplicate contacts, and malformed phone tags injected into production systems without deduplication logic.
- Context collapse: generic prompts failing to identify subtle multi-stakeholder alignments within complex corporate parent/subsidiary structures.
- Reputational blast radius: unvetted outbound payloads transmitting incorrect pricing assumptions or invalid compliance claims to C-level targets.
TARGET AUDIENCE AUDIT
- OPERATOR PROFILE — DESIGNED SPECIFICALLY FOR: B2B sales operations leaders, RevOps directors, & enterprise COOs
- ORGANISATIONAL PROFILE: teams managing complex, high-ACV enterprise pipelines where each prospect touchpoint carries material corporate liability and requires verifiable strategic context.
- IMMEDIATE OBJECTIVE: cut manual signal collection substantially while keeping human sign-off on executive-facing messages.
PRAGMATIC ARCHITECTURE // ZERO SPAM DRIFT
[02 // HEURISTIC BOUNDARIES] When this approach makes sense vs. when not to automate.
Engineering integrity requires strict demarcation. Automation creates asymmetric leverage only under high structural predictability; it introduces catastrophic noise when applied to subjective social negotiations.
| OPERATIONAL DIMENSION | WHEN THIS APPROACH MAKES SENSE | WHEN NOT TO AUTOMATE |
|---|---|---|
| DEAL ARCHITECTURE | High-ACV, multi-stakeholder enterprise accounts with multiple decision makers across procurement, IT, and legal requiring orchestrated signal mapping. | Bespoke executive-level political negotiations. Board-level relationship introductions, closed-door tender bids, or distressed restructuring terms. |
| SIGNAL TRIGGERS | Structured, verifiable public events: public regulatory filings (e.g. SEC 10-K/10-Q), formal RFPs, public cloud migrations, capital expenditure approvals, or VP-level executive hires. | Vague social sentiment or subjective rumour: unverified podcast mentions, anonymous forum comments, or speculative LinkedIn engagement signals. |
| PAYLOAD BOUNDARY | Rule-constrained technical hypotheses. Draft outbound messages citing exact public events, pointing directly to pre-approved reference material. | Dynamic commercial commitment: quoting contractual pricing bands, custom SLA commitments, or unreleased platform feature roadmaps. |
| DATA INTEGRITY | Schema-validated JSON & rule checks. Payload formatting is strictly type-checked. Note: schema adherence validates structure and constraints, not factual correctness. | Freeform generative text scraping. Blind copy-pasting from web portals directly into CRM primary contact fields. |
Merged from the mobile export — further examples. Automatable (bounded) work: regulatory registry extraction and filing parsing; firmographic schema enrichment; hiring-signal correlation from job boards; draft generation restricted to documented company facts and pre-approved reference material. Keep manual: unsupervised dispatch to top-tier accounts; final contract value estimates and pricing concession proposals; master-record deduplication on ambiguous matches (route to a human); attribution overrides based on unconfirmed social sentiment. (Mobile export’s confidence thresholds and latency figures dropped as invented metrics.)
[03 // SYSTEM INTERFACES] Inputs and expected outputs.
INGESTION VECTOR // INPUT SPECIFICATION [ SOURCE_DATA ] — raw, multi-modal signal intake from asynchronous enterprise streams:
- Unstructured procurement notices — tender specifications, public vendor requisitions, state RFP portals, and tech requirements tables.
- Executive & hiring restructuring — engineering and IT leadership hiring updates, title promotions, and team reorganisations.
- Regulatory & financial filings — SEC 10-K/10-Q filing feeds, quarterly earnings transcripts, and CapEx investor disclosures.
- Internal CRM telemetry — existing stale accounts, historical deal losses, churn records, and product license expirations.
INGEST PROTOCOL (example targets): REST webhooks // SFTP batch // read replicas
EGRESS_PAYLOAD // OUTPUT DELIVERABLES [ STRUCTURED_DELIVERY ] — normalised, typed, and human-reviewed tactical artefacts:
- Canonical JSON schemas — reconciled records formatted for sync to CRM entities.
- Scored account dossiers — briefing summaries highlighting identified levers, recent disclosures, and public tech stack details.
- Draft outbound messaging — contextual email drafts staged for operator review and manual approval.
- Traceability & diff logs — inspection logs showing source text origins and rule-based filter outputs for each draft.
EGRESS PROTOCOL (example targets): JSON:API // CRM bulk API v2 // chat digest
[04 // SYSTEM TOPOLOGY] Process architecture.
Every message and CRM update flows through a 5-stage sequential assembly line. Automatic execution is partitioned from outbound transmission by a configured human approval checkpoint.
ILLUSTRATIVE_WORKFLOW // STAGE_SEQUENCING HUMAN_REVIEW_POINTS
Illustrative example — fictional. Execution diff (hypothetical, not a real experiment or client): the model matched a hypothetical newly filed Q3 Form 8-K from a fictional “Meridian Logistics Corp” citing a fictional $14M warehouse automation upgrade. An outbound draft was tailored to a fictional VP of Infrastructure referencing their fictional legacy WMS migration.
DRAFT_PAYLOAD (fictional) // Subject: Question regarding the legacy WMS cutover schedule
“Reviewing your recent CapEx disclosure on supply modernisation, noticed the integration milestone…”
TACTILE CONFIRMATION SWITCH — VERIFY FACTUALITY & AUTHORISE EGRESS
Detailed operational sequence walkthrough
- Ingestion & de-duplication: incoming events are stripped of tracking noise, mapped to primary entity IDs, and compared against live CRM account records. If an account has an active pipeline deal or a recorded touchpoint within the prior 45 days, the signal is tagged as informational and archived without triggering outreach generation.
- Rule-based normalisation: raw text bodies are structured using rule-based parsing and schema validation. Note that while schema validation enforces data shape and typing, it does not certify factual truth. Rule-based checks flag unverified entity claims for explicit operator inspection.
- Staged egress (illustrative pattern, sometimes described as “air-gapped egress”): the design intent is that no network call to mail servers or production database mutation happens without passing through Node 04. An operator receives a consolidated diff queue, reviews contextual provenance, and signs off. Configured rule checks reduce blast radius — they do not certify model output, and a review point keeps its force only where it is actually enforced.
[05 // ENGAGEMENT MODEL] What a pilot should evaluate.
We do not sell perpetual software subscriptions or black-box platforms. Every evaluation is scoped to examine actual workflow friction, isolate failure modes, define canonical schemas, and test human review ergonomics.
For ongoing AI oversight rather than a single assessment, see the fractional CAIO engagement at haker.ai.
PHASE 01 // AUDIT — Baseline audit & data hygiene. Review of outbound conversion rates, CRM bounce rates, duplicate records, and identification of signal leaks. DELIVERABLE: HYGIENE_AUDIT_REPORT
PHASE 02 // RULES — Schema & boundary modelling. Formalising schema definitions, explicit rule constraints, customer suppressions, and domain exclusion lists. DELIVERABLE: CANONICAL_SCHEMA_DRAFT
PHASE 03 // SIMULATION — Shadow run & dry run. Testing ingestion and synthesis in dry-run mode. Drafts are generated in a staging area with zero external egress. DELIVERABLE: EVALUATION_REPORT
PHASE 04 // PROTOCOL — Review ergonomics & operator training. Configuring human review points directly inside your team’s workflow tools for rapid, frictionless inspection. DELIVERABLE: OPERATOR_REVIEW_GUIDE
RELATED ARCHITECTURAL BRIEF — Why valid JSON does not prove an AI extraction is correct: why schema conformance does not establish factual accuracy, and where human review checkpoints belong in high-consequence enterprise extraction.
[ WORKFLOW EVALUATION // TECHNICAL CONSULTATION ] Evaluate your sales workflow with Marcin.
We review your existing CRM schema, discuss current data friction points, and determine if an engineered validation gate makes operational and economic sense for your pipeline.
STRICTLY TECHNICAL ADVISORY // NO SDR OUTSOURCING PITCH