AI Services · Strategy & Embedded Execution

The AI playbook for the sports economy.

Most sports businesses are still operating like it's 2019. The competitors who move first will compound their advantage every quarter the others delay. Here's the playbook for moving first — and how I help you ship it.

No. I On urgency

Why the next 18 months compound differently.

Sports — and especially youth sports and children's activity — is one of the last large sectors still substantially operating on 2019 playbooks. Email-and-spreadsheet ops. Front-desk staff catching inbound during coaching hours. Founder-driven content posted whenever there's a window. Marketing built bespoke per business, agency-by-agency, with nothing that compounds across a portfolio.

None of that is wrong. It's how the sector got here. But it's also why the next two years are going to feel discontinuous.

The businesses that move first on AI aren't winning by automating away their humans. They're winning by doing the same operational work with a fraction of the drag — capturing every inbound, qualifying leads in seconds, producing content at the volume their audiences actually want, and freeing their best people to do the high-judgement work only humans can do.

The advantage doesn't show up all at once. It compounds — quietly, then loudly — across every quarter the laggards delay.

That's the thesis. The harder problem is how to act on it without falling into the two traps that catch most teams: pilot purgatory (six months of demos and proofs-of-concept that never reach production), and vendor theatre (paying for AI features that look impressive in a sales call and disappear by month three).

What I do, and what this page lays out, is a method for getting past both. Diagnose where AI moves the needle for your specific business. Architect a sequence that ships something real in weeks, not quarters. Build the deployments alongside your team — so they actually own them at the end. Then keep compounding.

The work is sector-specific because generic AI advice is everywhere and worth nothing. What's worth something is knowing where the bodies are buried in a youth sports ops stack, how a vertical SaaS founder's roadmap actually gets unblocked, where a PE-backed services business loses margin to operational drag, and what AI actually does about each of those. That's the work.

No. II On approach

A five-stage method. Built to ship.

i.
Diagnose Weeks 1–2
Sit with the leadership team. Audit current state — what's working, what's clearly broken, where AI moves the needle fastest. Map operational drag and revenue leak. Identify the three to five highest-leverage opportunities and rank them by effort versus impact. Output: prioritised AI roadmap with 90-day, 6-month, and 12-month horizons.
ii.
Architect Weeks 2–4
Design the rollout sequence — low-effort, high-impact deployments first to build internal confidence and stakeholder momentum. Define success metrics for each deployment. Confirm the team, tooling, and integrations we'll use. Output: signed-off plan with named owners, success metrics, and timelines.
iii.
Build Months 1–3
Deploy alongside your team — not in isolation from them. Use real production data and real workflows from day one. Document everything. Train internal owners as we go, so by the time the deployment is live, your team understands it well enough to operate and iterate without me. Output: live systems, operating on real data, owned by your team.
iv.
Embed Months 3–4
Hand off operational ownership in full. Train edge cases and escalation paths. Document the playbooks. Build the evaluation and iteration cadences your team will actually run after I'm gone — not theoretical processes that decay the moment the consultant leaves. Output: independent operation with clear playbooks and review cadences.
v.
Compound Ongoing
Quarterly reviews. New surface areas. Iteration based on real production learnings. Expansion into the next wave of opportunities. The goal isn't a one-time transformation — it's an organisation that gets meaningfully better at AI every quarter, not just better with these specific tools. Output: an organisation that compounds — not one that consumed a project.
No. III On the work

Five deployments. Built and proven.

i.

Multichannel AI voice & messaging

The 24/7 inbound capture system most sports businesses are quietly missing.

What it replaces

Missed calls when staff are coaching. Slow weekend email responses. Manual lead qualification eating front-desk hours. The conversion leakage that quietly suppresses every revenue forecast.

What gets built

Voice agent personality and prompts tuned to your brand and pricing. Qualification logic. Calendar and CRM integrations. Escalation rules. Transcript capture, dashboards, and continuous-improvement training data.

Typical outcomes

Zero missed inbound. 24/7 lead capture across phone, SMS, WhatsApp, social DM, and web chat. Faster speed-to-trial. Coaching and admin hours reclaimed for actual coaching and admin.

ii.

Content engines at scale

Systematic content production for founders who can't post consistently — built around your voice, not against it.

What it replaces

Founder-bottleneck content (you film when there's time, post when you remember, then disappear). Agency-driven content that doesn't sound like you. The credibility cost of going dark for two months at a time.

What gets built

Content category framework specific to your business. AI-assisted ideation and scriptwriting workflows. Format-specific templates for Shorts, Reels, TikTok, and LinkedIn. Distribution calendars. Analytics and iteration loops.

Typical outcomes

50+ scripts produced and published per month. Sustained presence across 3–5 channels. Founder time spent on filming and judgement only — not on the blank-page paralysis that kills most content systems.

iii.

Custom Claude & GPT builds

Bespoke AI assistants embedded into operating businesses, products, and member experiences.

What it replaces

Scattered ChatGPT use across the team with no consistency. Tribal knowledge trapped in senior heads. Generic AI features that don't differentiate. The missed product opportunity of an AI add-on you could be charging members for.

What gets built

Specialised prompt and tool architectures. Knowledge bases drawn from your real content and SOPs. Conversation flows mapped to user intent. Deployment surfaces (web, app, Slack, email). Evaluation and iteration loops.

Typical outcomes

Differentiated product features that retain members and lift NPS. Internal AI tools that 5x specific operational workflows. Defensible AI assets competitors can't quickly replicate or commoditise.

iv.

AI-native deal workflows

The end-to-end automation stack for active acquirers, fundraising founders, and outbound sales operators.

What it replaces

Bandwidth-limited deal teams. Generic cold email that gets filtered before it's read. Slow qualification cycles. CRM data that's three weeks out of date the moment it's entered.

What gets built

Enrichment workflows pulling signal from web, social, financial filings, and news. Personalisation engines that read like a human wrote them. Multi-thread cadence management. Reply parsing and routing. Pipeline scoring. On-demand founder and exec dossiers.

Typical outcomes

10x outreach volume at higher response rates. Qualification cycles compressed from weeks to days. Deal team time redirected to relationship work and judgement calls. Pipeline data that's actually current.

v.

Marketing operating system

A cross-portfolio marketing framework that makes new acquisitions productive on day 30 — not month 6.

What it replaces

Bespoke marketing per business eating budget every time. Agency dependencies that don't compound across the portfolio. Slow GTM on every new acquisition. Founder-driven marketing that breaks the moment the founder steps back.

What gets built

Brand and positioning playbook templates. Content production stack with templates, tools, and prompts. Distribution calendar templates. Attribution and reporting dashboards. Onboarding sequences for new portfolio companies.

Typical outcomes

New acquisitions onboarded to a working marketing engine within 30 days. Consistent brand language across the group. Lower CAC across the portfolio. Agency spend redirected to high-leverage strategic work.

No. IV On the case file

Selected current engagements. Anonymised by request.

AR media · early stage

Youth sports AR media platform

Active engagement

An immersive, AR-driven youth sports media platform building next-generation viewing and engagement experiences for parents, players, and clubs. Engagement covers AI roadmap architecture, content engine deployment, and Claude-powered features integrated directly into the core product layer.

ii. Content engines iii. Custom Claude builds
Youth services · multi-location

US soccer school

Active engagement

A multi-location US youth soccer school capturing inbound demand 24/7 and modernising lead-to-trial conversion across high-volume seasonal cycles. Multichannel AI voice and messaging deployed across phone, SMS, and web — qualification and trial booking automated end-to-end.

i. Multichannel voice v. Marketing OS
Movement & dance · seed stage

Youth dance startup

Active engagement

A US youth dance startup scaling from zero. Engagement focused on the Marketing OS — positioning, content production, distribution calendar, and AI-augmented creative workflows that let a small founding team punch well above its weight on output and consistency.

ii. Content engines v. Marketing OS
Sports media · network

Youth sports media network

Active engagement

A youth sports media network producing podcast and short-form video content at scale across YouTube, TikTok, Instagram, and LinkedIn. Engagement covers content engine architecture, AI-assisted scriptwriting and distribution workflows, and a custom Claude-based research assistant for episode prep.

ii. Content engines iii. Custom Claude builds
Marketing agency · done-for-you

Youth-focused marketing agency

Active engagement

A done-for-you marketing agency serving youth-focused businesses across sport, fitness, and education. The Marketing OS deployed as the agency's productisation backbone, plus multichannel AI voice and messaging running both as an internal ops tool and as a deliverable feature for the agency's own client portfolio.

i. Multichannel voice v. Marketing OS
No. V On engagement

Three ways to work together. Pick the one that fits.

Coda

If your business is at risk of being out-innovated — let's fix that.

Discovery calls are 30 minutes. No pitch deck. We talk through what you're trying to do, where you think AI fits, and whether one of the engagement formats above is the right shape for the work. If it's not, I'll say so — and where possible point you toward someone who is.