00
Course Trailer
Student understands the course promise and the networking operating loop.
0 browser capture targets · 2 worksheet/resource files
static preview rendered
Standalone course product
AI Networking Sprint
A practical networking operating system for college seniors and recent grads: pick a lane, find relevant people, send low-pressure asks, pair outreach with applications, and review the week with AI.
Course outcome
Teach the operating loop, then let the portal personalize it.
The course is the standalone product. The voice agent and coaching workspace use the same lesson IDs to route students toward the next useful move after intake.
Turn broad career interests into one weekly networking lane.
Find relevant people around roles, organizations, schools, projects, and application targets.
Write low-pressure messages that ask for learning, not favors.
Pair applications with people maps and follow-up dates.
Use AI for research, drafts, prep, and review without sounding generic.
Reset the sprint every Friday using visible signals instead of vague motivation.
Student workflow
The method is a loop students can repeat every week.
Pick the lane
Reduce a scattered search to one useful role family, organization type, problem space, or application cluster.
Find people
Use LinkedIn-style browsing and structured research to build a first list of reachable, relevant people.
Make the ask
Draft short messages that create a conversation around learning, context, and next steps.
Pair every application
Treat applications as one part of the system, not a replacement for people, context, and follow-up.
Review the week
Use replies, silence, conversations, and next actions to choose the next bottleneck.
Preview lesson
Start with the trailer before paid course access opens.
Lesson 00 is rendered as a static Remotion preview. It shows the course promise and the weekly operating loop while browser walkthroughs, narration, and account access move toward the paid launch.
Course Trailer
Student understands the course promise and the networking operating loop.
Status: static preview rendered
Manifest-backed lesson map
The public course outline uses the same IDs as Remotion and voice intake.
Render status stays visible so the course can move from spec to browser captures, narration, captions, and final lesson exports without losing traceability.
01
Build The Weekly Networking OS
Student creates one weekly sprint lane and understands the loop.
2 browser capture targets · 2 worksheet/resource files
pending
02
Pick A Search Lane
Student turns broad interests into 2-4 practical role-family hypotheses.
1 browser capture target · 1 worksheet/resource file
pending
03
Find People With Experience
Student builds a first 10-15 person list around a target lane.
2 browser capture targets · 2 worksheet/resource files
pending browser capture
04
Prioritize The First Five
Student chooses first contacts by relevance, reachability, and question quality.
1 browser capture target · 2 worksheet/resource files
pending
05
Send The Low-Pressure Ask
Student drafts and sends/queues three learning-oriented messages.
1 browser capture target · 2 worksheet/resource files
pending audio and capture
06
Prepare A Useful Conversation
Student prepares questions and a next-step ask for a target conversation.
1 browser capture target · 1 worksheet/resource file
pending
07
Network With Every Application
Student pairs meaningful applications with a contact strategy.
1 browser capture target · 2 worksheet/resource files
pending browser capture
08
Turn Conversations Into Better Applications
Student converts conversation learning into ethical next actions.
1 browser capture target · 2 worksheet/resource files
pending
09
Follow Up Without Being Awkward
Student creates a follow-up queue and next-step messages.
1 browser capture target · 2 worksheet/resource files
pending audio and capture
10
Review, Reset, And Repeat
Student reviews the sprint and chooses the next bottleneck to address.
1 browser capture target · 2 worksheet/resource files
pending
Synthetic sprint preview
Before: saved postings and vague networking. After: a weekly operating loop.
This example is public-safe and synthetic. It previews the student behavior the course is designed to produce: one lane, mapped people, low-pressure asks, application-contact pairing, prep, follow-up, and review.
Day 1
Choose one target lane and three real targets.
Day 2
Build a people map with near-peers, alumni, team-adjacent operators, and hiring-team signals.
Day 3
Write three low-pressure asks that request context instead of favors.
Day 4
Pair one application with a contact strategy.
Day 5
Prepare five questions for one target conversation.
Day 6
Create a follow-up queue.
Day 7
Review replies, silence, applications, and artifact gaps.
Browser walkthrough
The first browser lesson is a people-map pass, not a generic LinkedIn tour.
The paid lesson will show how to move from a target lane to a small list of reachable people, then into tracker rows and low-pressure asks. Public previews use staged examples so the course does not depend on private student data or David-owned screen recordings.
Search
Start from one lane phrase, then search for near-peers, alumni, team-adjacent operators, and role-adjacent profiles.
Qualify
Save people only when there is a specific connection angle: school, project, role path, employer, market, or application target.
Extract
Turn each profile into one tracker row with source, why this person matters, what to ask, and the next action date.
Draft
Use AI to create a short learning ask, then remove generic praise, pressure, and premature referral language.
Launch offer
Launch package: standalone course, bundle-first offer.
The course stays self-serve. The strongest first sale pairs it with the Job Search OS Kit so students have the tracker, people map, prompts, and weekly review assets beside the lessons.
Standalone course launch target: $99.
Primary kit + course bundle target: $129.
No live review is included in the self-serve course.
Paid access opens after the first preview lesson and course account access are ready.
Reviewed help routes to the Career Support Workspace.
Voice-agent bridge
Intake routes students to the course without pretending every student needs the same lesson.
The networking intake schema produces a diagnosed stage, missing context, reviewed tasks, and recommended lesson IDs. This keeps the course, async coaching inbox, and client context packet aligned.
Scripts are Hendeaux-owned rewrites, not copied PGP course copy.
Browser captures must use staged or publishable accounts and screenshots.
Narration uses a Hendeaux voice; no David voice clone without explicit rights.
No rendered asset may include raw transcripts, private paths, private students, emails, phone numbers, schools, or employers.
Voice-agent lesson recommendations must use the same lesson IDs exposed by this product page.
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