Context Engineering
Your AI tools have no idea who you are.
Every sales call, every deal, every hard-won positioning decision — locked in your team's heads and scattered across 15 tools. Context engineering pulls it together into a system your AI actually uses. Deployed in 3 weeks.
The $200/seat/month tool that knows nothing
Context scattered across 15 tools
HubSpot, Google Docs, a slide deck nobody can find. Your AI sees none of it.
Every prompt returns generic output
You pasted your positioning doc into the chat. It still writes like it's never heard of your buyer or your last three lost deals.
Every conversation starts from zero
ICP, pricing, competitive landscape — re-explained every session. 30 minutes before anything useful happens.
Nothing compounds
Six months in, your AI is no smarter than day one. Every license dollar is a subscription to amnesia.
What context engineering actually is
It's not prompt engineering. Prompt engineering is asking better questions. Context engineering is building the memory that makes every question productive.
You don't need polished docs. We take the fragmented mess and build the coherent whole.
Give us the raw material
- 1
Call recordings — even messy ones
- 2
A CRM export
Whatever state it's in. We'll find the patterns.
- 3
Your competitors' names
That's it. We do the rest.
- 4
Whatever positioning exists
A website, a deck, a one-pager — or just a conversation about what you do.
- 5
How your team actually works
Doesn't need to be documented. We'll map it together.
- 6
Product docs if you have them
If you don't, we work from what's public.
What you get back
- 1
Master context file
ICP, positioning, messaging pillars, proof points, voice standards — one file your AI loads every session.
- 2
Competitor intelligence system
Full breakdowns for each competitor: positioning, strengths, weaknesses, where you win, where you lose, and how to respond.
- 3
Custom skill library
Meeting prep. Prospect research. Content drafts. Deal scoring. Cold outreach. Competitive battlecards. All tuned to your data.
- 4
Connected tools
HubSpot, Slack, email, calendar. Wired in, not pasted in.
- 5
Knowledge graph
Win/loss patterns, customer objections, product capabilities, sales playbooks — linked so AI pulls the right context automatically.
- 6
Measurement baseline
Week 1 vs. Week 4. The proof your CFO needs.
Case Study
Series B controls engineering platform
Series B, 50+ employees, two continents. GTM running on spreadsheets and tribal knowledge. VP of Sales spending half his week on manual pipeline reviews.
Three-week engagement. Knowledge mapping surfaced gaps nobody expected — the system works because it finds what's broken.
VP of Sales got his week back. Marketing producing content from actual win/loss data. 47 custom skills compounding daily.
3 weeks
to full deployment
47
purpose-built skills
12x
content output
$0
additional hires
Who builds this
- 15 years B2B SaaS GTM. Two exits. 2-3x sustained growth.
- CB Insights → BurnAlong → Pixee
- 2.5 years building AI-native GTM systems in production
- The system I sell is the system I run
I run the same system I deploy. Every engagement sharpens it.
Let's talk about your context.
Two engagements per month. Tell me what you're working on — I'll tell you if this fits or doesn't.