AI agents are only useful
attached to real work.

Most AI marketing projects fail because nobody decided what the AI was for. Story Mode installs workflows around specific operating needs — reporting, research, content operations, account research — designed by an operator who has run the marketing function, not sold software.
100+
Workflows shipped
6
Workflow types installed
20yr
In growth marketing
Trusted by founders at
GroundfloorRaiinmakerBlockonomicsBitrefillDSCVRTradeZeroStep3

What this looks like in practice.

RaiinmakerChief Marketing Officer (Fractional), 2024
Two audiences with almost nothing in common, both needed at once.

A decentralised AI network where consumers contribute video data through a mobile app and node operators run validator infrastructure. Operators evaluate the network on technical and economic terms; contributors respond to reward mechanics and community. One message could not serve both, and the network needed volume on both sides simultaneously to be commercially useful.

  • Split go-to-market into parallel B2B and B2C tracks with separate persona content
  • Ran wallet-level targeting to reach holders of specific tokens on X and Reddit, sidestepping the ad restrictions that block conventional crypto acquisition
  • Built distribution through KOL and alpha group partnerships, plus a campaign with a major professional sports franchise
  • Sustained community engagement through town halls, X Spaces, and recurring activations
Network scaled from ~200,000 to over 450,000 users

What they said.

Deep knowledge in marketing with a deep passion about crypto. Always quick to produce results.

Sergej KotliarCEO, Bitrefill

Helped kickstart our marketing strategy from concept to new product launch.

Nick CasaresHead of Product, Step3

The line between
leverage and noise.

01
Automate the mechanical

Collecting, formatting, summarising, monitoring. High frequency, low judgment, and you can tell good output from bad at a glance.

02
Keep the judgment

Positioning, pricing, what to say and to whom. AI produces plausible marketing fast, and plausible is the failure mode — it reads fine and says nothing.

03
Adoption decides it

A workflow nobody uses is worth nothing. Most of these projects die at team adoption, not at the build, which is why SOPs and handoff are part of the work.

Sound familiar?

1
You have AI tools everywhere and no system tying them together.
2
The output is fast, generic, and someone has to rewrite all of it anyway.
3
Manual research and reporting still eat a day of every week.
4
Somebody built a workflow once and nobody on the team uses it.
5
You cannot tell whether any of this has actually saved time.

Story Mode installs the system and the operating discipline around it — so your team runs strategy, and the mechanical work runs itself.

Six workflows worth building.

These are the ones that consistently earn their keep in a small marketing team. Each is scoped to a specific job, with a checkable output and a named owner.

01
Weekly reporting

Pulls channel performance into one synthesised read with the changes worth noticing, so the Monday report stops consuming an afternoon.

02
Competitor monitoring

Watches positioning, pricing, and launches across a named set of competitors and flags what genuinely changed rather than everything that moved.

03
Content brief generation

Turns a topic and an audience into a structured brief with angle, proof points, and sources — the slow part before anyone writes.

04
Lead and account research

Builds account context ahead of outbound or a sales call, so reps are not opening ten tabs to prepare for one conversation.

05
Campaign QA

Checks links, tracking parameters, copy consistency, and asset variants before launch. Unglamorous, and it catches the errors that quietly cost money.

06
SEO opportunity tracking

Monitors rankings and surfaces the pages and queries where a small change has disproportionate effect.

The first 90 days.

Week 1–2
Find the real drag

Where the team's week actually goes, measured rather than assumed. Rank tasks by frequency, judgment required, and whether the output is checkable.

Time auditTask rankingStack review
Week 3–4
Build one workflow properly

Usually reporting or research. One workflow running reliably beats six half-built, and it proves the model to the team before you ask them to change how they work.

First buildContext and constraintsQA loop
Month 2
Extend and document

Add the next workflows, write the SOPs, and get the team using them in their normal week rather than as a side experiment.

Workflow expansionSOPsTeam adoption
Month 3
Hand it over

Your team runs the system without you. Ownership assigned, failure modes documented, and a way to tell whether it is still working.

Ownership mapFailure modesHandoff

How we work together.

AI-enabled marketing systems

Workflow design and installation, scoped to the operating needs a diagnosis surfaces rather than a fixed package.

Time and workflow audit
Six workflow types available
Built around your existing stack
Voice and context standards
QA loop and failure modes
SOPs written for the team
Ownership handoff
Month-to-month, no lock-in

Installed by the same operator who runs the marketing engagements, which is why the workflows tend to fit how marketing actually gets done.

Questions.

What are AI marketing agents?
Task-specific workflows that carry out repeatable marketing work without a person driving each step — pulling research together, drafting from a brief, monitoring competitors, assembling the weekly report. They are not a product you buy. They are built around your stack and your process, which is why a generic tool rarely survives contact with a real marketing team.
Do AI agents replace a marketing team?
No, and any engagement sold on that premise is worth declining. Agents remove the mechanical middle of the work — collecting, formatting, summarising, monitoring. Judgment about what to say, who to say it to, and what to do next stays human, because that is the part that actually determines whether marketing works.
Which marketing workflows are actually worth automating?
The ones that are high frequency, low judgment, and have a checkable output. Weekly reporting, competitor monitoring, content brief generation, lead and account research, and campaign QA all qualify. Positioning, pricing, and anything requiring taste do not. If you cannot tell good output from bad at a glance, do not automate it yet.
What should stay human?
Positioning, final messaging judgment, brand decisions, customer conversations, and prioritisation. AI produces plausible marketing very quickly, and plausible is precisely the failure mode — it reads fine and says nothing. Someone senior has to decide what is worth saying before any of this is useful.
How do you keep AI output from sounding generic?
By giving the system real context and real constraints rather than a prompt. That means documented positioning, a written voice standard with concrete examples, and specifics about the business the model could not otherwise know. Most generic output is not a model failure — it is a briefing failure.
How long does implementation take?
First workflows are usually running within a few weeks, then get refined as real output exposes the edge cases. The work that takes longer is not the building — it is the adoption. A workflow nobody on the team uses is worth nothing, which is why SOPs and handoff are part of the engagement rather than an afterthought.

Want a system your team
will actually use?

One 30-minute call. A practical conversation about where your team's week is going and which parts are worth automating.

Book a Call
hello@storymode.co· Niagara-on-the-Lake, ON · Remote-first worldwide