AI Marketing Engineer

Strategy Worth Automating · a two-week agentic sprint

Your 2027 plan is being written on 2025 metrics.
Fix the strategy, then build the tools.

Marketing is being rewritten, and last year's plan can't be assumed to work. In two weeks, your team finds the real constraint on growth, places one bet on its own data, and builds the first tool that makes it work.

-67 to -75%Time to market
30+ to 70+Tests per campaign
-49 to -77%Acquisition cost

Ranges across three recent client engagements, anonymised. Details below.

What's changing

The marketing landscape is changing.

Every aspect of marketing is being rewritten by AI, and it's all moving at once, and quickly. Each has changed before, but rarely all together and never this quickly, so there is no playbook to follow that has already been through this.

  1. 01

    How customers find you

    AI answers now shortlist the options before anyone clicks.

  2. 02

    Who makes the work

    Agents draft copy, creative and research in minutes. Judgement on what to make is the scarce part.

  3. 03

    How media is bought

    Ad platforms choose more of the audience, placement and creative themselves.

  4. 04

    How people buy

    Assistants compare products, and are starting to complete the purchase for the customer.

  5. 05

    How results are measured

    Rankings, sessions and clicks mean less each quarter.

We don't focus on one channel. We focus on marketing and growth as a whole, and your constraint decides where the two weeks go.

What good teams are already doing

Small teams, one bottleneck, tools they built themselves.

30 seconds
To make one ad, down from 30 minutes. Anthropic's growth marketer ran paid search, social, email and SEO alone, with tools he built himself.Anthropic, January 2026
24 hours
For legal review of marketing content, down from 2-3 days, after a lawyer built a self-review tool. Lawyers still check everything.Anthropic
7 days
For Klarna's image production, down from 6 weeks, while an internal copy assistant wrote 80% of its copy.Klarna, via Reuters, May 2024
50% cheaper
And twice as fast: Unilever's product imagery, rendered from digital twins instead of reshot.Unilever, March 2025

What these teams have in common: one person or a small team, one narrow bottleneck, the people who own the work building the tool, and people keeping the final approval. The other side matters too. An MIT study found most organisations saw no measurable return from generative AI; the ones that did tied it to a specific workflow, a clear outcome and an accountable owner. That is what the sprint sets up.

The planning lag

You can hit every target and still lose ground.

Most organisations lock next year's plan about 12 months ahead to get it through the boardroom. By the time it runs, the data is two years old and the metrics may no longer mean what they did. Dashboards still count campaigns, sessions and leads while the way customers buy, and the way the work gets done, has changed. A team can hit every target on the old dashboard while the business loses ground.

Data the plan is built on
Written and approved
Plan runs
Typical annual planning cycle. Plans are locked about 12 months before they start.

What the dashboard counts, and what to count instead

The old dashboardWhat tells you it is working
Campaigns shippedTests run, and what they changed
Traffic and sessionsEnquiries or sales by source
Cost per leadCost per outcome: a sale, a renewal, a settled loan
RankingsNamed or cited in AI answers
Hours workedTime to market
12-month targetsA 90-day review with a decision

The question every marketing leader is asking

Should we build our own AI tools?

Build only for the work your strategy says matters, and only where it compounds.By Day 10 your team knows which tools those are, has one working, and has a plan to adopt it.

DiagnosisThe real constraint on growth
One betOn your own data, with how you'll know
Carry it outTools that do the bet's work at scale
OutcomeSales, renewals, members
Make it betterTools that help the team see, decide and measure
↑ Feeds the diagnosis and the bet, and every decision after the sprint

Tools that make the strategy better

They help the team see, decide and measure: a monitor of what AI answers say about you, an interview coder, a weekly read of the numbers in your measurement plan. They improve every decision after the sprint.

Tools that carry out the strategy

They do the work the bet needs at a scale people can't: pages for every customer question, campaign variants for testing, sales enablement. Only worth building once you know the bet is right.

How it works

Week one, the right strategy. Week two, the right tools.

BeforePre-work · two weeks out · Problem, data, interviews and a place to build
Week 1
Mon · Day 1Operating model and agent charter
Tue · Day 2Find the constraint, with the AI shelf test
Wed · Day 3Inside the customer's head
Thu · Day 4What works, and what we believe
Fri · Day 5Place the bet, and how we'll know
Week 2
Mon · Day 6Audit the work the bet needs
Tue · Day 7Build, buy or skip
Wed · Day 8Build the prototype
Thu · Day 9Test it and plan the adoption
Fri · Day 10Present to leadership, then run it again
  • DiagnosisWeek 1 · Days 1-3What is actually wrong?
  • StrategyWeek 1 · Days 4-5What works, what do we believe, what do we bet on, and how will we know?
  • ToolsWeek 2 · Days 6-8Which parts of the bet are worth automating: build, buy or skip?
  • AdoptionWeek 2 · Days 9-10Does the tool beat how we work today, and how does the team take it on?

A day in the sprint

WhenWhat happens
Two weeks beforeKickoff call, data pack, five customer interviews booked
8:00-11:00amLive session every day: the idea, agent work in squads, a decision
AfternoonsAbout 3 hours of team work with agents. The rest is for essential BAU
4:30pmEach day's deliverable posted; written feedback before 7:30am

Agents and people

Agents multiply whatever strategy you already have.

So agents do the volume, speed and pattern-finding. People keep the diagnosis, the belief and the decision.

Agents doPeople decide
Pull 24 months of data and flag where the funnel breaksDecide which break is the real constraint
Ask your customers' questions in Google, Gemini, ChatGPT and Perplexity, three times eachInterview five real customers
Code interviews, cluster a year of campaigns, red-team the betWrite the point of view and place the bet
Merge workflow maps and time notes into one audit of the workDecide what to delete, what to automate, and build, buy or skip
Do the job the prototype is for, and explain their own errorsJudge the tool blind against real examples, and own its adoption

What your team leaves with

A strategy, the tools to run it, and the skills to keep going.

Diagnose → bet → build → adopt → run it again.

  • One bet. On one real problem, built on your own data, with the outcome, leading indicators, kill criteria and a 90-day review.
  • A build, buy or skip list. Every tool the bet needs, costed, with a call and the reasons for each.
  • A working prototype. One agent or tool built on your own data, and tested fairly against how the team does the job today.
  • An adoption plan. Who owns the tool, who uses it, what it may and may not do, training, and a 90-day rollout.
  • The skills to keep going. Everyone has built and tested with agents, not just watched a demo.
  • A method to run again. An agent charter and a quarterly cadence, so strategy and tools stop being an annual lock-in.

Does it pay back?

Faster to market, more tests, lower acquisition cost.

Recent client engagements, measured before and after.

Time to market

Weeks from brief to launch
B2B software company-71%
7 weeks
2 weeks
DTC e-commerce brand-67%
3 weeks
1 week
Superannuation fund-75%
8 weeks
2 weeks

Tests per campaign

Variants tested before, during and after launch
B2B software company
Under 5
45+
DTC e-commerce brand
None
70+
Superannuation fund
Under 10
30+

Acquisition cost

CAC, indexed to before = 100
B2B software company-77%
~$2,500
~$570
DTC e-commerce brand-72%
~$145
~$40
Superannuation fund-49%
~$249
~$126
Show the numbers as a table
ClientTime to marketTests per campaignCAC$50k pays back at
B2B software company18 in marketing and growth, under the CRO7 weeks → 2 weeks (-71%)Under 5 → 45+~$2,500 → ~$570 (-77%)CAC ~$1,100 after 3 months and ~$570 after 6. Tests: 20+ before launch, 5 during, 20+ after.About 26 new customers
DTC e-commerce brand4 in marketing3 weeks → 1 week (-67%)None → 70+~$145 → ~$40 (-72%)CAC ~$40 after 3 months, forecast ~$27 by 6. Tests: 50+ before launch, 20 during.About 480 orders
Superannuation fund17 in marketing8 weeks → 2 weeks (-75%)Under 10 → 30+~$249 → ~$126 (-49%)CAC measured over 12 months.About 410 new members
$50k pays back atAbout 26 new customersB2B software company · 18 in marketing and growth, under the CRO
$50k pays back atAbout 480 ordersDTC e-commerce brand · 4 in marketing
$50k pays back atAbout 410 new membersSuperannuation fund · 17 in marketing

Results from Benny Robinson's recent client engagements. Clients are anonymised; figures in AUD. "Pays back at" is $50k divided by the CAC saving per new customer, using the latest measured CAC.

Formats and price

One team, all of it, together.

Remote

From $50k

$5,000 per person

The whole team, every session live on video. The leadership presentation can be remote too.

Book a call

Hybrid

On request

Quoted for your team

Remote, with Benny Robinson in the room for Day 1 and the Day 10 presentation.

Book a call

On-site

On request

Quoted for your team

Benny Robinson in the room for all ten days.

Book a call

The whole team, every day

Everyone in marketing and growth takes part, not a few delegates or just the leads. A strategy sticks when the people who run it built it together.

Not a leadership workshop

Leaders sponsor it and hear the result on Day 10. The work is your team learning to work together, and with agents, on its own problem.

The business keeps running

Remote by design. The sprint takes about three-quarters of each day, leaving a quarter for essential BAU if you need it. We recommend clearing it.

Before you book

Is this about one channel?

No. It covers marketing and growth as a whole: content, creative, media, CRM, search, sales enablement, pricing and retention. Your constraint decides where the two weeks focus, and strategy comes first because tools only multiply the strategy you have.

Which AI tools do we need?

The ones your company already allows. Pre-work checks access, what data may go into them, and where the prototype may be built. The AI shelf test runs on our tooling if yours can't.

Do we need developers to build the tools?

No. The prototype is built with the AI tools your company already approves. Your most technical team member acts as build lead, but everyone builds, and the person who has built least is at the keyboard.

What data do we bring?

About 24 months of analytics, enquiries or sales by source, Search Console and last year's campaign results. It stays under your data rules.

How much of the team's time does it take?

About three-quarters of each working day for ten consecutive days: three hours live each morning and about three hours of work in the afternoon. The quarter left can cover essential BAU, but the sprint works best when it is cleared.

Can part of the team attend, or just the leads?

No. It is a whole-team sprint, not a leadership workshop. The point is for your team to learn to work together on one problem, so everyone in marketing and growth takes part every day.

How is it priced?

$5,000 per person, from $50k. Hybrid and on-site formats are quoted on request.

A two-week agentic marketing sprint for teams who'd rather be the right kind of busy.

Book a 30-minute call to test whether your problem fits the program.

Team examples as reported by the companies: Anthropic (growth marketing, January 2026; legal review), Klarna via Reuters (May 2024), Unilever (March 2025). Return on generative AI: MIT NANDA, 2025 (preliminary). Client results: Benny Robinson's recent engagements, anonymised.