System trace
Vacancy → outreach brief
One signal. Five layers. Every step is a versioned artefact in git. Follow a single job posting through the full Next Move Engine pipeline — from raw file to a ready-to-send message with stop conditions.
Scenario
Input: a Head of Engineering vacancy at Ve##ra — a fictional B2B fintech (~80 engineers, Series B, Q3 regulatory milestone).
Output: a typed outreach action: who, channel, exact message angle, CTA, KPI, stop condition.
Names and companies are synthetic. The file structure, skill contracts, and decision rules are real.
Layer 1 — Input
File arrives. No processing yet.
A vacancy is dropped into inputs/vacancies/. This is the boundary of the system — raw text, no classification.
# inputs/vacancies/ve##ra-head-of-engineering.md
Ve##ra — Head of Engineering
We are a B2B payment infrastructure company (~80 engineers, Series B).
CTO K**er B**vik is looking for a Head of Engineering to own delivery
across three product squads and one platform team.
Requirements: 5+ years engineering leadership, experience scaling orgs
past 50 engineers, strong on process and technical standards.
Context: Q3 2026 regulatory certification milestone.
Delivery pace and squad autonomy are top of mind.
Layer 2 — Signal
vacancy-intel classifies the input.
First output: a signal card in market-state/signals/. Type and strength assigned against a fixed vocabulary — no free-form inference.
# market-state/signals/ve##ra-leadership-gap-2026-03.md
---
id: S-41
company: Ve##ra
signal_type: leadership-gap
strength: strong
source: inputs/vacancies/ve##ra-head-of-engineering.md
date: 2026-03-14
linked_person: K**er B**vik
---
CTO posting a Head of Engineering role = explicit delegation play.
Strength: strong — public source + structural indicator + named deadline.
One signal. Not yet a pattern.
Layer 3 — Intelligence
vacancy-intel produces the deep profile.
Second output: a structured intel report in market-state/intels/. Company profile, role analysis, hidden agenda, two entry-point lenses.
# market-state/intels/ve##ra-head-of-engineering.md
---
skill: vacancy-intel
date: 2026-03-14
company: Ve##ra
source: inputs/vacancies/ve##ra-head-of-engineering.md
signals: [S-41]
---
## Company profile
Series B fintech, payment infrastructure, ~80 engineers.
Regulatory certification Q3 2026 — delivery predictability is existential.
Growth stage: scaling from startup to structured engineering org.
## Role analysis
HoE under existing CTO = delegation play, not co-founder hire.
CTO wants delivery ownership off their plate before the deadline.
Squad structure already decided (3 product + 1 platform).
## Hidden agenda
CTO is measured on the Q3 milestone.
Hiring for delivery acceleration — 60–90 day decision window.
## Entry point: consulting lens
High fit: engineering leadership setup + delivery acceleration.
Angle: delivery ownership at scale, not a recruitment pitch.
## Entry point: hiring lens
Fit: strong on process and delivery. Risk: HoE under CTO = limited scope.
Probe: squad autonomy level, tech debt situation, board pressure.
Layer 4 — Hypothesis
market-analyst synthesizes across the full state.
Runs periodically. Reads new signals and intel, cross-references the full market-state/. Output: a dated, confidence-scored hypothesis.
# market-state/hypotheses/ve##ra-delivery-pressure.md
---
id: H-22
level: micro
confidence: high
date: 2026-03-14
companies: [Ve##ra]
signals: [S-41]
intel: market-state/intels/ve##ra-head-of-engineering.md
expires: 2026-06-30
---
Ve##ra CTO is under delivery pressure ahead of Q3 regulatory deadline.
Delegating engineering execution now — looking for someone to own delivery.
This is a narrow, time-bound window: 60–90 days.
Receptive to delivery-acceleration conversation.
Not receptive to a generic EM pitch.
Confidence: high
Why: structural signal (public vacancy) + named deadline + delegation pattern.
Layer 5 — Action
action-planner drafts the outreach brief.
Reads the high-confidence hypothesis. Produces a typed AI-* action: concrete, executable, self-contained.
# market-state/actions/AI-28.md
---
id: AI-28
kind: outreach
hypothesis: ve##ra-delivery-pressure
created: 2026-03-14
who: K**er B**vik, CTO, Ve##ra
channel: LinkedIn DM
status: not started
dependency: none
---
Angle: noticed the HoE opening — curious what the current bottleneck looks
like at 80 engineers when delivery ownership is being split out.
Message draft:
"K**er, saw you're building out delivery ownership at Ve##ra.
I've set up similar structures at 50–200 engineer orgs — the hard part
is usually not the org chart but the squad contract model.
What's your biggest constraint right now — pace, autonomy, or something else?"
CTA: one open question. No CV. No services list. No call request.
KPI: any reply within 7 days.
Stop: silence → log in market-state/people/b**vik.md, no retry for 30 days.
What this trace produced
Signal
S-41
leadership-gap · strong
Intel
ve##ra-hoe.md
company + role + entry points
Hypothesis
H-22
micro · confidence: high
Action
AI-28
outreach draft · ready to send
2 model skills. 1 human decision. Every artefact versioned in git. No guessing.
Architecture decisions
Why files, not API calls?
Each layer writes a file to market-state/. The next layer reads files. No direct skill-to-skill calls. No shared memory.
Every state transition is versioned in git. You can reconstruct what the system knew on any given day.
Why typed actions?
An AI-* action has fixed fields: who, channel, angle, CTA, KPI, stop condition. A generic "reach out to X" has none of those.
Typed actions are immediately executable. They also enable dependency graphs: AI-9 unlocks AI-10 only after AI-9 is logged.
Why confidence threshold?
Low-confidence hypotheses produce PI-* positioning items — fix the narrative, write content. Not outreach.
Outreach on weak signal is noise. The system treats your attention as expensive.