heyarnoux.

Fractional GTM x AI

Let's Build Your GTM x AI Engine.

Implementation, done with you. I'm your fractional architect and head coach. We build your GTM x AI engine inside your team, motion by motion. The signals, the workflows, the agents, the reporting. 20+ builds in, B2B and B2C.

How it works

I'm your architect. We build the engine together.

01

I learn your environment.

Your systems, your data, your team, your funnel. The Diagnostic Sprint maps where revenue leaks and what your stack can already do. By the end we both know what to build first.

02

We pick the first motion.

One play, live on your data, a win in weeks. Your team builds it with me, so the capability stays in the building.

Example first motions

Lead scoring on your CRM Self-learning paid marketing ads ABM on the accounts that matter Outbound that fires on real buying signals Sales enablement, briefs and battlecards per deal Lifecycle flows that react to behavior SEO + GEO content that AI answers cite A reporting agent that drafts the weekly board update Call transcripts mined for objections
03

We stack motions into an engine.

Each new motion reuses most of the plumbing of the last, so every one ships faster and cheaper. Little by little it becomes your GTM x AI engine, running inside your team.

Two ways in

Pick how we work together.

Start with me as your architect. Option 01 is the full engagement. Option 02 adds build capacity once the first motions are live. Pick one, add the other later.

Option 01 Your fractional architect and head coach.

I'm your Architect (and your head coach).

I design the architecture, lead the build and stand up your Center of Excellence, embedded in your team. We ship motion by motion until the engine runs itself.

Embedded Sprints + Marathons Center of Excellence

What you get

  • I'm your architect and head coach. The steering seat: architecture, sequencing, weekly cadence, C-suite translation.
  • Audit lives inside the work. Stakeholder interviews, maturity scorecard, agentic architecture, ranked pilot backlog.
  • Sprints ship quick wins. 2 to 4 week pilots in production. First wins inside 90 days.
  • Marathons harden and embed. Pilots scale to production. Training, playbooks, runbooks, monitoring.
  • Center of Excellence inside your org. A permanent function that owns GTM x AI after I leave.
  • 20+ implementations across B2B and B2C. Same playbook. Same traps avoided.
Book a fit call →
Option 02 Embedded engineers, when you need build capacity.

GTM Engineers, in your team.

Trained on my playbooks, up and running in days, not months. Each builds 2 to 3 proofs of concept in parallel, with my architecture and weekly oversight. Most teams add engineers after the first motions ship.

Dev placement Cancel anytime Money-back month 1

What you get

  • Strong GTM x AI engineers embedded in your Slack, repos and daily rhythm.
  • Full-stack: React, Next.js, Node, Python, AWS / Azure / GCP, Supabase + Vercel for early stage.
  • AI-native: Claude Code, agentic workflows, MCP servers, automation. No vibe coding.
  • I architect and oversee weekly. Each engineer runs 2 to 3 POCs in parallel.
  • Easy cancellation. Swap the engineer if fit isn't right. First-month money-back.

Investment

EUR 5,500 to 7,500 / engineer / month

See how placement works ↓
Companies I've worked with
Google  ·  Backbase  ·  SkyShowtime  ·  Joom  ·  Raiffeisen Bank  ·  Sage  ·  HotelsOne  ·  SOSU  ·  GoodHabitz  ·  Unmuted  ·  Marktlink  ·  Tribes Media  ·  Everconvert  ·  Growth Tribe  ·  and more

Flagship case · GTM x AI in production

A €2.5B fintech rebuilt its GTM function from zero. I architected it.

Backbase runs the platform 120+ banks sit on. Over the past year I led its GTM x AI transformation into a GTM OS the team owns and runs. Their CMO published the numbers.

10xAccount coverage
per marketer
85%+New pipeline
YoY
60%+Deal size
YoY
Read the Backbase case study →

The exact engine this page sells, built and shipped.

Case study · B2C growth OS

Programmatic SEO + paid that optimizes itself.

A fast-scaling B2C brand (anonymized) rebuilt acquisition into one growth OS: an SEO engine built for the AI-answer era, and paid advertising that tunes itself daily. Owned traffic that compounds, spend that chases customers who stay.

12,000+pages 4.2xorganic 41%lower CPA
Read the case study →

The menu

The motions we pick from.

This is the menu behind step 02. A catalog drawn from 20+ implementations across B2B and B2C. Your first motion and your backlog get cut from this list, scored on impact × ease, sequenced at the Sprint workshop. Every play has shipped to production somewhere.

Content + SEO + GEO

  • Programmatic SEO pages
  • GEO, get cited in LLM answers
  • Blog brief assembler
  • Product description writer
  • Newsletter generator

Account Intelligence + ABM

  • Signal engine, score accounts by intent
  • Per-account research dossier
  • ABM one-pager generator
  • Competitive radar
  • Buyer-committee mapping

Outbound + Inbound

  • Personalized outbound at scale
  • Inbound qualification bot
  • Reply triage + routing
  • Re-engagement campaigns
  • Event follow-up

Conversion + Performance

  • Ad creative engine
  • Landing page generator + A/B
  • Conversion health monitor
  • Lead scoring + routing
  • Pricing page personalization

Lifecycle + LTV

  • Cart abandonment recovery
  • Win-back + loyalty campaigns
  • Channel-attributed LTV
  • Next-best-SKU recommender
  • Predictive lifecycle model

Pipeline + Forecasting

  • Pipeline + QBR auto-gen
  • Forecast model
  • Win/loss analysis
  • Churn prediction
  • Revenue attribution

Customer Success + Retention

  • Health-score cockpit
  • Renewal forecast
  • Onboarding playbook
  • CS QBR auto-gen
  • Expansion alerts

Sales Enablement

  • Call intelligence + coaching
  • Deal review bot
  • Battle card auto-update
  • Proposal generator
  • Pricing recommender

Brand + Reviews + PR

  • Review monitor + auto-reply
  • Brand mention sentiment
  • Customer story generator
  • Influencer outreach
  • PR / earned media tracker

Voice + Conversational

  • Out-of-hours voice agent
  • Callback queue automation
  • Inbound voice triage
  • Call summarizer
  • Sales coaching agent

Internal Brain

  • Executive RAG brain
  • Decision log
  • New-hire onboarding agent
  • Vendor selection assistant
  • Strategy doc consolidator

Ops + Data

  • CRM gap analysis + repair
  • Data hygiene bot
  • SaaS audit
  • Integration repair
  • Comp / quota model
+ An example 90-day backlog

Example backlog · first 90 days.

Cut from a real engagement. Your version gets reshaped at the Sprint workshop, scored on impact and ease, sequenced for compounding momentum.

Play Impact Ease Time to ship Type
Pipeline + QBR reporting auto-gen High Easy 2 to 3 weeks Quick win
Per-account research bot High Easy 2 to 3 weeks Quick win
Signal engine, score target accounts High Medium 4 to 6 weeks Marathon
Performance marketing creative engine Medium Easy 2 to 3 weeks Quick win
Sales call intelligence + coaching High Medium 3 to 4 weeks Marathon
Customer health-score cockpit High Medium 4 to 6 weeks Marathon
RAG executive brain High Medium 4 to 6 weeks Marathon
Re-engagement campaign automation Medium Easy 2 weeks Quick win
Programmatic SEO + GEO engine High Hard 6 to 8 weeks Marathon
Out-of-hours voice agent High Hard 6 to 8 weeks Marathon
Channel-attributed LTV model High Hard 6 to 8 weeks Marathon

Pick the plays you would start with.

Browse all 60, click the ones you want in your first 90 days. I turn your picks into a Sprint proposal.

How it runs

A typical 120 days.

Week 1 to 2
Stakeholder interviews. I sit with your specialists, sponsors, compliance, product / IT. Each session surfaces facts, pain, the buyback list.
Week 3 to 4
Architecture, scorecard, ranked backlog. Maturity-gap rated. Quick wins ranked. Agentic architecture drafted. Roadmap deck shaped.
End of Sprint
Two workshops + executive readout. CEO or sponsor in the room. Path locked. Sprint retro hands off to the retainer.
Week 5 to 12
Retainer engages. Weekly cadence, steering meetings, KPI dashboards. First pilots ship from the ranked backlog. Engineers plug in if build capacity is the bottleneck.
Week 13 to 17
Compounding mode. Pilots scale to production. Backlog turns over. Bigger bets unlocked. Quarterly recalibration with your sponsor on the horizon.

Running it

Your GTM x AI OS, in motion.

What the dashboard looks like 90 days in. KPIs, plays running, alerts triggered, this week's wins. Real shape, illustrative numbers.

+ What the weekly dashboard looks like (illustrative)

Illustrative numbers, the real one runs on your data.

gtm-os · weekly view
Pipeline coverage
3.4x
↑ 0.6x vs last quarter
Signal → meeting
11.2%
↑ from 4.1% baseline
Win rate
28%
↑ 6 pts
Churn, annual
7.1%
↓ 2.3 pts
Active plays · 8 running, 1 scheduled, 1 paused
  • Signal engine · 4,127 accounts scored daily
  • Pipeline + QBR auto-gen · Mondays 6am
  • Per-account research bot · on-demand
  • Outbound sequence builder · 38 sequences live
  • Health-score cockpit · 612 accounts monitored
  • Call intelligence · 100% calls processed
  • Programmatic SEO · 1,840 pages indexed
  • RAG executive brain · 47 queries this week
  • Re-engagement campaign · launches Tuesday
  • Voice agent · pilot complete, decision pending
Who's hot today · 6 alerts
  • CriticalAccount #142 · CEO + CFO on /pricing 4x this week
  • HighAccount #87 · renewal in 14 days, score dropping
  • HighAccount #213 · 3 buying signals in 48 hrs
  • MedAccount #44 · added 8 new users
  • MedAccount #168 · funded yesterday
  • LowAccount #29 · re-engaged after 41 days
This week · what shipped
  • SHIPPEDABM asset generator · 47 personalized one-pagers sent to target accounts
  • SHIPPEDBattle card auto-update · 12 cards refreshed from competitor moves
  • SHIPPEDCS health alert · 9 accounts flagged before renewal, 6 saves in motion
  • SHIPPEDProgrammatic SEO · 23 new pages indexed, 8 ranking top 10
  • SHIPPEDInbound qualification bot · 142 leads triaged, 18 booked direct

The engine in motion

Chaos in. Playbooks out.

What the engine actually does, every day. The buzzword storm becomes a working machine that ships playbooks that move revenue and cut costs.

Want the full methodology? How I take a company AI-native, one BU at a time.

Read the transformation playbook →

The build

Your OS, three shapes.

Same idea every time. One connected store of everything you know, agents and your team building on top. Pick the shape that fits you and see what it looks like. Yours will differ in detail, the shape holds.

The vital trifecta

What makes a GTM x AI engine actually ship.

Three legs. All three needed. Most teams have one, sometimes two. The third is the binding constraint. We close it together.

In place

Leg 01

Leadership mandate

A sponsor at the top who actually wants this. Permission to move fast. Air cover when something breaks. Without it, the work stalls in committee.

Extend

Leg 02

Infrastructure

A stack you can ship against. Data accessible, tools API-able, security non-blocking. Most teams have the foundation, we extend it for AI workloads.

The work

Leg 03

The team

GTM x AI engineers embedded in your daily rhythm. The binding constraint for most orgs. Players from my bench plug in, or I coach yours up.

What I bring

Pattern recognition, not theory.

20+

Implementations

Same playbook, run 20+ times across B2B and B2C. You won't pay for me to learn how this fails.

∞

Architectural guidance

Agent design, MCP stack, vendor selection, compliance guardrails. Decisions that compound or rot for years, locked at the right time.

0

Lock-in risk

Sprint stops at workshop if numbers don't add up. Engineers refund the first month. Retainer cancellable monthly after the minimum.

Option 02 in detail · How placement works

Put an embedded engineer in your team.

Full-time, inside your Slack and your repos, trained on my playbooks, with my architecture and weekly oversight on top. From use case to shipping in week one. Here is the whole path.

YOUR TEAM your embedded engineer
your people the engineer, full-time inside the team, a different colour on the org chart
How the profiles work. When you engage you receive three real anonymized profiles matched to your use case, employers removed, results kept, one flagged as my recommendation. You pick, you meet them on a call before kickoff, then you decide.
Step 1Tell me the use case

Requirement analysis, 1 to 2 days. What you want built decides who you meet.

Step 2Meet 3 profiles

Three anonymized profiles from a 30+ bench, one flagged as my recommendation. Your pick.

Step 3Call before kickoff

You talk to your engineer before anything starts. Wrong fit? You meet the next one.

Step 4Embedded in 72h

Inside your Slack and your tools, shipping in week one. Money-back month 1, 90-day replacement.

Want to see who is on the bench?

Six full example profiles, anonymized the same way real ones are. Superpower, shipped work, experience, stack. Employers removed, results kept.

See the example profiles →
+ Everything that's included

Included the day we sign.

Zero extras, zero surprise line items.

Claude Code on us
The tooling, our tab

The engineer ships on our Claude Code subscription. You never see an AI tool bill from this engagement.

Your channel
In your Slack or Teams

One dedicated channel. Async by default, synced when needed. No tickets, no agency portal between you and the work.

Key security
Your team never sees the keys

A secure setup where everyone uses every agent while the core API keys stay locked away. Built in from the start.

Own playground
Nothing touches prod unsigned

The engineer works on a separate environment. Nothing hits your live systems without your sign-off.

End-of-day note
You always know what shipped

Short end-of-day update when something meaningful ships. No black box, no surprise changes.

Engineer switch
Friction-free if the fit is off

If the person is wrong, we swap them with a full handover through the shared channel. No restart cost.

30+Engineers on the bench
72hTo start
95%First-year retention
90 daysReplacement guarantee
Month 1Money-back if not happy
Book a scoping call →

Tell me what you want built. You get three profiles matched to it, one recommended, then a call with your pick before anything starts.

Next step

30 minutes. Decide together.

A fit call covers your context, the gaps, what the Sprint would scope, and whether it makes sense to start. No pitch deck. No CRM follow-up sequence.

On the call we cover
Book a fit call → Read the playbook Email me direct

Not ready for a call? Tell me where you are. I reply personally.

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