Context Engineering for GTM
Your GTM Operating System
Your ICP, positioning, competitive landscape, and first-party data, structured once, circulating across every function, and run by agents instead of re-explained every session.
Book a strategy callNo pitch, just strategy.
Your motion doesn't compound.
Nothing compounds.
Last week's research doesn't make this week's work better. Every campaign starts from a blank page.
Your data is trapped.
The asset that could drive traffic and authority is sitting in a database nobody queries.
Functions are siloed.
Sales intel doesn’t reach content. Content insight doesn’t reach outbound. The same context gets rebuilt three times.
The AI sounds generic.
It’s never met your business, so it writes like it. You re-explain your ICP every single session.
Context layer → operating system → compounding.
A GTM Operating System is built in that order. First comes the context layer, holding your ICP, positioning, competitive landscape, and proof, structured once. Then come the skills and agents that draw from it, so account research, content, outbound, and competitive intel all run on the same source of truth. Then it compounds, because every output enriches the context for the next one. You own the layer, and the model stays swappable.
Advising a portfolio? This is the infrastructure that standardizes an AI-native GTM motion across portcos without rebuilding it from scratch in each one — so a portco can expand into new verticals and geographies before committing to a full marketing buildout. The same handoff model runs across the portfolio, so the work is less dependent on any one operator's hours.
Book a strategy call →The machine, in six parts.
Generic capabilities, built into your repo and wired to your stack. Build the ones you need first; the rest are already designed to chain in.
Context Layer
Your business, structured once, referenced everywhere.
A repo-resident knowledge layer — ICP, positioning, competitive intel, proof points, voice. Calls and research feed it continuously, so every agent draws from one source of truth. The part everyone skips, built first.
Data-to-Asset
Package your proprietary data into traffic-seeking content assets.
Programmatic pages and content products built on first-party data you already own, turning a dataset that just sits in a database into a standalone content asset and a newsletter flywheel. (See the proof section for what one of these has done.)
Content Production Loops
Consistent expert content in your voice, without the stall.
An SEO-and-context-driven content map, then research → draft → polish loops producing long-form, LinkedIn, and a weekly newsletter without losing your strategic voice or going stale. Each piece enriches the context for the next.
Competitive Intelligence
Always know what the competition is shipping.
Agents that scrape competitor posts, whitepapers, and thought leadership, then synthesize landscape maps, battlecards, and displacement angles indexed to your positioning.
Sales Enablement
Every rep discovery-ready before every call.
Account research that turns 45–60 minutes of manual prep into a 3–5-minute brief: company profile, tech stack, buying committee, MEDDPICC map, and pain hypotheses linked to your proof.
Signal-Based Engagement
Use account signals to prioritize better-timed outreach.
Social listening and trigger detection wired to account research, so outreach leans on real intent signals instead of cold cadence.
What this has actually produced.
A year-deep production system.
This offer is extracted from the AI-native GTM system I’ve built and run for over a year. I’m not selling a theory I sketched; I’m selling the machine I operate.
A PE-backed manufacturer, ~$50M revenue, 4 verticals.
A four-week engagement produced 37 custom skills, full account playbooks across active pipeline, net-new targeting, competitive battlecards, and an SEO content strategy — owned by the client, forever.
The same build, seven times.
Deployed across seven companies and about thirty operators — manufacturers, B2B software, services — in two models: full repo handoff, or a tuning sprint where I ingest your context and configure the system with your team. The motion repeats; the context is what changes.
45–60 minutes → 3–5 minutes.
Account-brief prep cut from the better part of an hour of manual work to a few minutes, with broader research than a human covers by hand.
A data site that out-trafficked the core site in a month.
A standalone data-product site, built on first-party data, drew several times the core marketing site’s traffic within thirty days and tripled the newsletter behind it.
Built the playbook before, twice.
I built the newsletter-led growth engine at a category-defining market-intelligence company, then replicated it. The harness is how I do it faster now.
You own the system. No lock-in, no per-seat tax.
Two models, both ending with you in control. Either I hand you the full system — the repo, skills, context layer, integrations, and security setup — and you run it. Or I spend focused time ingesting your context, building collaboratively, and tuning the skills to your business. Most builds reach a working system in about four weeks. Either way you walk away owning that system on your own private repository, yours to modify, extend, or hand to the team you hire once the motion is proven — with no per-seat fees and no vendor lock. Scope comes out of a strategy call, not a price list.
Book a strategy call.
No pitch, just strategy. We'll map your context, your data, and the fastest path to a motion that compounds. If a GTM Operating System isn't the right move, I'll tell you.