01
Start with a specific audience and problem.
A narrow wedge gives every message, channel, and experiment a chance to become legible.
Failure: Broad reach with no clear reason to care.
AGI OS / DISTRIBUTION SYSTEM
Distribution is how good work reaches the right people.
A strategy workspace for AI builders and researchers to understand the distribution loop, find its bottleneck, and choose the next learning experiment.
Core definition
Distribution is the system that moves a product from existence to the right person’s attention, first value, repeat use, and onward spread.
Scenario qualified reach
21,865
6 cycle horizon
First-value activations
945
People who reached a useful outcome
Referral share
0.2%
Share of qualified reach from referrals
Current bottleneck
Referral rate
40/100 leverage score
System map
The distribution loop
Attention is only the first handoff. The system becomes durable when value creates return visits, referrals, and better proof.
click a stage for operating detail
Selected stage · 01
Audience
Choose the smallest group with a real, urgent reason to care.
Primary metric Qualified audience fit
Required inputs
Specific person, painful problem, reachable context
Failure mode
Trying to reach everyone before learning who cares.
Next experiment
Interview ten AI builders about the first job they would hire Skyloop to do.
Scenario simulator
Find the constraint
Change the assumptions and see how the loop responds. These are scenario outputs, not measured evidence.
A credible early distribution system with room to learn.
Scenario output
Compounded reach
Seed reach12,000
Qualified reach3,643
First-value activations157
Retained users76
Qualified referrals6
Operating rules
Rules that protect the loop
02
Pair every message with credible proof.
Trust travels with the claim: show the mechanism, result, artifact, or person who can vouch for it.
Failure: A promise that asks the audience to do all the believing.
03
Adapt the format to the channel.
Distribution is not copy-paste publishing; each surface has its own native behavior and social contract.
Failure: One asset repeated everywhere with declining signal.
04
Optimize for first value, not impressions.
The real handoff is attention to a useful outcome, not attention to another view count.
Failure: High reach with no first-understanding moment.
05
Build feedback into every channel.
Every distribution surface should teach you something about the audience, message, or product.
Failure: Activity without a learning loop.
06
Measure stage-to-stage conversion and retention.
Track where people fall out of the system and whether the product earns a return visit.
Failure: Optimizing a top-line number while the middle is leaking.
07
Earn repeatability before adding paid reach.
Paid reach can amplify a working system, but it cannot repair weak trust or activation.
Failure: Buying more attention before understanding the funnel.
08
Scale only when the loop stays healthy.
Trust, activation, retention, and referral quality must remain intact as volume grows.
Failure: Growth that creates support load and churn faster than value.
Channel ecosystem
Where the system can travel
Direct founder + researcher outreach
readyTechnical founders, lab leads, and AI researchers
Native format: Personal demo, sharp question, and interviewTrust asset: Specific insight from the recipient’s workflowLearning speed: fastNext: Run 10 conversations around the first valuable research outcome.
Technical communities
learningBuilders already discussing hard AI problems
Native format: Native teardown, experiment, or open questionTrust asset: Transparent method and useful artifactLearning speed: fastNext: Compare an evidence-first post with a product-first post.
Build-in-public visual demonstrations
learningAI-curious builders and product thinkers
Native format: Short visual before/after or live walkthroughTrust asset: Visible transformation in under one minuteLearning speed: mediumNext: Test mechanism-first versus outcome-first demonstrations.
Research + creator partnerships
queuedTrusted voices with overlapping technical audiences
Native format: Co-authored explainer, lab session, or guest walkthroughTrust asset: Borrowed credibility with clear attributionLearning speed: mediumNext: Identify three collaborators who already explain the target problem.
Search + evergreen explanations
queuedPeople actively looking for difficult concepts
Native format: Searchable explanation with interactive visualTrust asset: Depth, citations, and a useful answer before the pitchLearning speed: slowNext: Measure search-to-first-value instead of visits alone.
Experiment queue
Learn before scaling
First-value conversation sprint
nextDirect conversations reveal the language and proof needed to make activation obvious.
Success 8 of 10 interviews identify the same first job
Guardrail No unsupported promise is added to the message
Native demonstration test
queuedA channel-native visual demonstration creates more qualified visits than a generic announcement.
Success Qualified visit rate by format
Guardrail Activation rate does not fall below the current baseline
Shareable research artifact
laterA useful output gives satisfied users a natural reason to introduce another builder.
Success Qualified referrals per activated user
Guardrail Referral quality matches the target audience wedge
Keep the loop honest
Reach is not distribution.
A distribution system earns the right to scale when attention becomes value, value becomes return use, and return use creates qualified spread.
Open Market Fit Scenario-only · no live campaigns