Can this guarantee rankings, AI citations or pipeline?

No. The work can improve how the team prioritises, creates and reviews evidence, but it does not guarantee a search position, citation or commercial outcome.

Pricing follows the selected scope, access requirements and delivery responsibilities. The first conversation determines whether there is a defined workflow worth building and what it requires.

What happens after the first workflow is in place?

The team can run it independently using the handover materials, or agree an ongoing review cadence for iteration and additional workflows.

Fractional Marketing Engineer for Tech Companies

How the role works

A CMO directs the work. Octocrew orchestrates the agent team.

The human owns strategy, decisions and approvals. Octocrew plans the work, routes dependencies and returns results from specialist agents for review.

The AI-native marketing department

One human directs a coordinated team of agents.

HumanAI-native CMO

Strategy, priorities, decisions and approvals

AI marketing department

Agent orchestratorOctocrew

Plans jobs, manages dependencies and hands results back

Customer Truthcalls, support, churn

SEO / Contentsearch and founder content

Outboundsignals and timely outreach

Creativehooks, angles and tests

AI Searchcitability and visibility

Growth Cockpitresults and next actions

Results and exceptions → CMO. Strategy and accountability stay with the human.

Why this matters

Most teams have the data. They do not have a marketing memory.

Calls, CRM, support tickets and experiment results sit in different places. Random AI chats produce drafts, then forget the customer language, founder voice and corrections that should improve the next run.

More useful output

Every agent starts from approved customer evidence and business context.

Faster experiments

Hooks, offers and channels improve from recorded results instead of repeated guesswork.

Sharper positioning

Customer language flows into content, landing pages and sales material.

A smaller team that learns

Agents get a clear job, input, approval point and definition of a useful result.

The core asset

Random chats forget. The Growth OS remembers.

Random AI chats

Each prompt starts again. Context lives in individual conversations and disappears from the operating process.

isolated promptslost correctionsno result historyscattered context

Growth OS

A shared marketing memory that agents can read before working and update after results are reviewed.

customer truthfounder voiceresult historyagent corrections

Six systems

Turn one market signal into assets, distribution and learning.

Build the system with the clearest commercial priority first. Then use what it learns to improve the next one.

Customer Truth

Sales calls, tickets and churn notes become a weekly brief in the language customers repeat.

Founder Content Engine

Interviews and calls become source-backed drafts that keep the founder’s real voice.

Outbound Signal Engine

Funding, hiring and public pain create timely reasons to start a conversation.

Creative Testing Engine

One approved offer becomes multiple hooks and angles, with results written back.

AI Search Visibility

Customer questions and search demand become an evidence-backed SEO and GEO queue.

Growth Cockpit

A weekly view of what changed, what worked and what deserves attention next.

Get the workflow library →

An O-CMO example / Marketing Engineer

From one thesis to a market test that learns.

01 / Founder POV

“One marketer with an AI-agent team.”

The idea is a hypothesis until buyers respond.

02 / Human decision

Test it as a Fractional Marketing Engineer offer.

Define the buyer, the promise and what counts as a qualified conversation.

O-CMO: strategy + approval

03 / Agentic layer

Octocrew orchestrator

Specialist agents build and distribute one campaign angle.

SEO explainerService landing pageFounder postSignal-based outreach

04 / Learning loop

Analyze results. Reinforce what works. Standardize the process.

Qualified calls, objections and corrections update the offer and agent playbooks for the next experiment.

Illustrative workflow based on the O-CMO offer; no performance claim.

The engagement

Build the first working system in 30 days.

The output is a process your team can run, review and improve after the engagement.

WEEK 1

Pick the system

Choose the repeated marketing problem with the clearest commercial value.

WEEK 2

Build the Growth OS

Organise customer truth, founder voice, performance data and guardrails.

WEEK 3

Run one machine

Give agents live inputs, clear outputs and a human approval point.

WEEK 4

Prove and hand over

Review the result, record corrections and leave the team a repeatable cadence.

Practical stack

The workflow is the skill. Tools support it.

We start with the stack your team can maintain and add software only where it makes the chosen system more reliable.

Signals

CRM, support, sales calls, analytics and product feedback.

Build workbench

Claude and Codex for assets, pages, scripts, dashboards and small tools.

Operations layer

Octocrew for scheduled workflows, memory, approvals and recurring jobs.

Clear ownership

Marketing Engineer and Fractional CMO solve different problems.

A Marketing Engineer builds the system behind execution. A Fractional CMO sets broader marketing direction and priorities.

Marketing Engineer and Fractional CMO responsibilities
Area	Fractional Marketing Engineer	Fractional CMO
Primary responsibility	Turns an agreed priority into a repeatable workflow.	Sets broader marketing direction, positioning and priorities.
Typical output	Working system, agent jobs, review rules and handover.	Operating plan, market choices and leadership decisions.
Decision ownership	Reliability of the agreed workflow.	Marketing direction linked to company goals.

Explore Fractional CMO services →

What happens on the call

30 minutes. We define the first useful system:

Minutes 0–10
You show us where marketing work loses context, stalls or keeps restarting.
Minutes 10–20
We identify the first system worth building and the customer evidence it needs.
Minutes 20–30
We outline a 30-day build, approval points and the result we would use to judge it.

Three things worth knowing

You talk to Yaroslav directly.

Yaroslav reviews the workflow with you and tells you plainly whether a Marketing Engineer engagement is useful.

Yaroslav LehenchukFounder & Fractional CMO

Start with one working system.

The scope begins with one repeated problem, one clear owner and one measurable result.

No commitment before the scope is clear.

You leave knowing what to build first, what inputs it needs and whether O-CMO is the right partner.

See how the role works →

No contractNo sales script30 minutes

Your name *Work email *

Company *Website (optional)

Stage *Industry *

Which system should we build first? * What is happening now? *

Takes about 90 seconds. We reply within 24 hours.

FAQ

Common questions.

What should we start with?+

Start with one repeated workflow where lost context or unclear ownership blocks a meaningful commercial priority.

Do we need a large marketing stack?+

No. We begin with the tools and source material already in use, then add only what the selected workflow needs.

Can this guarantee rankings, citations or pipeline?+

No. The system improves how work is selected, executed and reviewed; market outcomes still depend on the offer, timing and execution.

What does it cost?+

Pricing depends on the first system, required access and delivery responsibility. The first call determines the scope.

One marketer with an AI-agent team.