3 min read

GTM Engineering Series #8: AI and Agents Need GTM Runtime Controls

As agents begin changing records, triggering workflows, and influencing priorities, they become GTM infrastructure. Permissions, review gates, logs, evaluations, and ownership make their actions traceable, governable, and safer.
3 min read

GTM Engineering Series #7: Experimentation Belongs in GTM Infrastructure

GTM experiments belong in infrastructure, with explicit hypotheses, populations, metrics, guardrails, owners, and decision rules that preserve organizational memory and distinguish repeatable learning from mere increases in AI-generated activity.
3 min read

GTM Engineering Series #6: Enrichment Pipelines Need Reliability

Enrichment becomes infrastructure when its fields drive routing, segmentation, and prioritization. Timestamps, provenance, confidence, refresh rules, and graceful failure handling prevent uncertain external data from becoming authoritative internal error.
3 min read

GTM Engineering Series #5: The CRM Is a Product Surface

Reps experience CRM as a product, so poor design predictably produces avoidance and bad data. A useful operator surface reduces ambiguity, supports real decisions, and returns value to every user.
3 min read

GTM Engineering Series #4: Routing Is Production Logic

Routing turns GTM strategy into a production decision about who acts next. Versioned rules, defined inputs, documented exceptions, and inspectable evidence keep multiplying motions from creating collisions downstream.
3 min read

GTM Engineering Series #3: Signals Need Contracts

Signals become useful only when contracts define their meaning, freshness, ownership, action, and learning loop. Treating them as production inputs prevents noisy alerts, false urgency, and AI-driven attention debt.
3 min read

GTM Engineering Series #2: The GTM System Has a Data Model

GTM failures often begin with undefined objects and relationships, not flawed reporting. An explicit data model aligns ownership, lifecycle, hierarchy, and system boundaries so automation and AI can act on reliable context.
4 min read

GTM Engineering Series #1: GTM Engineering Is Not RevOps With Code

GTM engineering makes revenue operations executable and inspectable through explicit objects, rules, contracts, queues, tests, and ownership. That discipline lets complex revenue systems sense, decide, act, learn, and fail without fragility.

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