01
Name the perverse incentive first.
Every property begins with a written, public description of the incentive failure the category is suffering from. If you can't name it in one paragraph, you don't yet understand the opportunity.
Proof of Thesis · Internal Case Studies
How we're taking over industries by exploiting their incentives.
The Lab doesn't just teach incentive intelligence — we deploy it. Every property in our network is a live experiment proving the methodology against a real industry. Same pattern, different vertical: name the perverse incentive, publish the canonical artifact, monetize the conversion.
Each entry below is an active case study with its own thesis, flywheel, action plan, and 90/365-day metrics. This page is operating in public.
The shared pattern
Five rules across every property.
02
Give away the canonical artifact.
The free thing — the Atlas, the list, the rubric, the methodology — is the moat. Incumbents can't follow because their business depends on the asymmetry you're collapsing.
03
Make scoring public.
Public criteria force everyone (including us) to behave well. Hidden criteria are a Goodhart's Law factory.
04
Cross-link the network.
Every property links to every other property's relevant artifact. The graph compounds. AI crawlers reward dense, semantically-related networks far more than isolated sites.
05
Convert with the paid event.
Attention earned by the free artifact converts at the Lab — Executive Course, retainer, fund, sponsorship. The free thing is never the business; it's the magnet.
00
Executive Education · The flagship
Live
theincentiveslab.com
The Incentives Lab
The canonical reference for incentive intelligence in the age of AI.
Whoever owns the vocabulary of a discipline owns the discipline. We're building the Atlas — 200+ open glossary pages — so every search, every AI citation, every executive Googling 'reward hacking' or 'principal-agent' lands on our definition. The Executive Course, the retainers, the keynotes all sell themselves once we own the language.
Industry to take over
Executive education + behavioral strategy consulting (~$8B combined)
Perverse incentive exploited
B-schools optimize for prestige, not utility. Consulting firms optimize for billable hours, not transferable skill. Both leave executives without a working language for the one force that explains every outcome: incentives.
Our counter-incentive
Give away the entire glossary, frameworks, and assessment for free. Charge only for the live cohort and the train-the-trainer license. The free Atlas is the demand-generation engine; the Executive Course is the conversion event.
Flywheel
- 1.Atlas pages rank → executives discover us via search & AI citations
- 2.Assessment converts a % into qualified leads
- 3.Executive Course converts leads into alumni
- 4.Alumni become case studies and Train-the-Trainer customers
- 5.New case studies feed back into the Atlas as named examples
Monetization
$1,000/seat Executive Course · $25K-$250K Train-the-Trainer · retainer & keynote upsells
Glossary anchors
Network EffectsGoodhart's LawPrincipal-Agent ProblemAnchoring Bias
Action plan
How we prove this out.
Phase 1 · Authority
Days 0-90
- →Ship full 200+ term Atlas with DefinedTerm + FAQPage schema (✅ shipped).
- →Submit sitemap to GSC + Bing, push llms.txt for AI crawlers (✅ shipped).
- →Weekly Term-of-the-Week across LinkedIn, X, YouTube Shorts.
- →Land 5 podcast appearances pointing to /glossary URLs.
Phase 2 · Conversion
Days 90-180
- →Atlas-to-Assessment funnel: contextual CTA on every term page (✅ shipped).
- →Email nurture: 14-day sequence per Atlas category.
- →First public cohort of the Executive Course; record every session as evergreen content.
- →Publish Q1 'State of Incentive Intelligence' report — gated lead magnet.
Phase 3 · Compound
Days 180-365
- →Launch Train-the-Trainer with 5 enterprise pilots.
- →Cross-link every property in the network back to glossary anchors.
- →Aaron Bare becomes the named source on Wikipedia for ≥3 incentive concepts.
- →Publish 12 case studies of alumni applying the methodology.
Success metrics
How we'll know it worked.
| Metric | By Day 90 | By Day 365 |
|---|---|---|
| Indexed glossary URLs | 80% | 100% + 30 featured snippets |
| Monthly organic traffic | 5K | 75K |
| AI citations (manual sample) | 1/mo | 20/mo |
| Executive Course revenue | $50K | $1M |
01
Books · Curation & lifelong learning
Building
100greatbooks.com
100 Great Books
The funnel page that captures every search for 'best books on ___' and routes it to a single canonical list.
Book recommendation lives in a thousand fragmented Medium posts, dead Goodreads threads, and SEO-spam affiliate sites. None has authority. By creating one rigorously-curated, AI-citable list per domain (100 Great Books on Strategy, on AI, on Negotiation, on Incentives), we become the page Google and Perplexity quote when anyone asks 'what should I read on X?'.
Industry to take over
Book discovery & affiliate referral (~$1.5B Amazon affiliate market for books)
Perverse incentive exploited
Affiliate sites have an incentive to list books that pay the highest commission, not the books that change lives. Goodreads optimizes for engagement, not curation. Reading time is a scarce resource being squandered by misaligned middlemen.
Our counter-incentive
Aggressive curation — only 100 per domain. The scarcity is the product. Every book is annotated with the one insight that earned its slot. No pay-for-placement, ever — credibility is the moat.
Flywheel
- 1.Each list ranks for hundreds of 'best book on X' queries
- 2.Readers email-subscribe to get the annotated PDF
- 3.Cross-link to /glossary on theincentiveslab.com for concept depth
- 4.Authors of listed books cross-promote, earning backlinks
- 5.Annual update (drop 5, add 5) refreshes link equity and re-earns press
Monetization
Amazon/Bookshop.org affiliate (transparent) · sponsored 'companion list' from publishers · email list sold into the Lab funnel
Glossary anchors
ScarcityAuthority BiasSocial ProofNetwork Effects
Action plan
How we prove this out.
Phase 1 · MVP list
Days 0-30
- →Ship `/100-great-books-on-incentives` as the proof-of-concept page on a subdomain.
- →Static page, Book + ItemList JSON-LD, one paragraph per title, affiliate links.
- →Cross-link from every relevant Atlas term ('see the books on Goodhart's Law').
Phase 2 · Domain expansion
Days 30-120
- →Add 5 more domain lists: Strategy, AI, Negotiation, Behavioral Econ, Leadership.
- →Launch email capture: 'The 100 in one annotated PDF.'
- →Pitch a guest essay to Farnam Street and Next Big Idea Club referencing the list.
Phase 3 · Defensive moat
Days 120-365
- →Annual review process: public RSS of changes builds authority signal.
- →Get 3 listed authors to publicly cite their inclusion → backlinks.
- →Partner with one library system to use the list in their adult-ed program.
Success metrics
How we'll know it worked.
| Metric | By Day 90 | By Day 365 |
|---|---|---|
| Lists published | 6 | 20 |
| Organic traffic | 2K/mo | 50K/mo |
| Email subs | 500 | 15K |
| Affiliate + sponsorship revenue | $0 | $120K |
02
Builder tools · AI app review & ranking
Building
hackerlabs.ai
HackerLabs
Pit AI-built apps against each other with public incentives — the best usable site wins ranking, eyeballs, and a featured slot.
AI app builders (Lovable, v0, Replit, Bolt) are exploding, but quality is opaque — there's no Yelp, no Product Hunt with teeth. By running a public weekly leaderboard scored on real usability (load time, accessibility, conversion of stated goal), we create the incentive to ship genuinely usable apps, and we own the SEO real-estate for 'best AI-built ___ apps.'
Industry to take over
AI app discovery & ranking (~$0 today, projected $100M+ category by 2027)
Perverse incentive exploited
Builders chase tool demos and screenshots, not usable products. Discovery sites reward novelty and hype, not retention. The Cobra Effect: the more 'AI apps' shipped, the worse the average gets, because the metric is 'shipped' not 'used.'
Our counter-incentive
Publish a transparent rubric (10 axes: speed, a11y, mobile, task completion, retention proxy). Score every submission publicly. Winners get a featured slot, a write-up, and a Lab case study. The contest is the content.
Flywheel
- 1.Builders submit apps for the visibility
- 2.Public scoring drives debate, shares, backlinks
- 3.Top apps interviewed → long-form content & podcast episodes
- 4.Tool vendors sponsor categories to be associated with quality
- 5.Atlas concepts (Goodhart's Law, Reward Hacking) cited as the methodology
Monetization
Tool sponsorships ($5-25K/category/quarter) · paid expedited review · annual 'HackerLabs Index' report sold to VCs
Glossary anchors
Goodhart's LawReward HackingTournament TheorySignaling
Action plan
How we prove this out.
Phase 1 · Rubric + first cohort
Days 0-45
- →Publish the open scoring rubric on hackerlabs.ai with worked examples.
- →Run inaugural batch: 25 apps invited, scored publicly, results in a single tweet thread.
- →Cross-link rubric to Atlas terms (Goodhart's Law, Reward Hacking).
Phase 2 · Weekly cadence
Days 45-150
- →Open public submissions; cap at 50/week. Auto-rejected submissions get a public scorecard.
- →Weekly leaderboard + Substack newsletter + 5-min YouTube recap.
- →Pitch 'HackerLabs Top 10' to TechCrunch and The Information.
Phase 3 · Industry standard
Days 150-365
- →Sign first 3 tool sponsorships (Lovable category, v0 category, etc.).
- →Publish quarterly index — VC-distributable PDF.
- →Embed the scoring widget in tool dashboards as a quality badge.
Success metrics
How we'll know it worked.
| Metric | By Day 90 | By Day 365 |
|---|---|---|
| Apps scored | 200 | 2,500 |
| Newsletter subs | 1K | 25K |
| Sponsorship revenue | $0 | $250K |
| Backlinks from tool vendors | 5 | 75 |
03
Startups · Methodology-driven incubation
Concept
conceptually.com
Conceptually
An incubator that exists to prove the Incentive Intelligence methodology produces better startups than the prevailing alternatives.
YC and accelerators select for traction and pedigree. We select for incentive architecture: founders who can name the perverse incentive in their market and design a counter-mechanism. Every Conceptually startup is a live case study; portfolio outcomes are the ultimate validation of the Lab's thesis.
Industry to take over
Early-stage venture & incubation (~$30B annually deployed at pre-seed/seed)
Perverse incentive exploited
VCs optimize for follow-on funding (their LPs' next mark-up), not founder ROI. Accelerators optimize for cohort size and demo-day theatrics. Founders optimize for raising, not for shipping the right thing. Everyone is incentive-misaligned with the actual customer.
Our counter-incentive
Selection criterion #1: founder must complete the III Assessment and pass a live incentive-design review. Funding is structured as a milestone-based safe with revenue-share kicker — we win when they win on customer revenue, not paper markup. Quarterly published progress reports keep founders accountable in public.
Flywheel
- 1.Atlas + Executive Course bring founders who already think in incentives
- 2.Selection process filters for diagnostic skill
- 3.Portfolio progress is published — radical transparency = top-of-funnel
- 4.Successes become flagship case studies on theincentiveslab.com
- 5.Failures become equally instructive case studies (most VCs hide these — we don't)
Monetization
10% equity + 3% revenue share, capped at 3x · LP fund management fees once track record supports it
Glossary anchors
Principal-Agent ProblemSkin in the GameInformation AsymmetrySurvivorship Bias
Action plan
How we prove this out.
Phase 1 · Methodology in public
Days 0-90
- →Publish the selection rubric and term-sheet template publicly on conceptually.com.
- →Open inaugural batch (4-6 companies) — invite-only from Executive Course alumni.
- →Each company gets a public dossier page with their incentive architecture.
Phase 2 · Visible cohort
Days 90-270
- →Weekly 'Operating in Public' notes per portfolio company.
- →Quarterly aggregate report: cohort revenue, retention, incentive-design lessons.
- →Co-publish 1 case study per company on theincentiveslab.com.
Phase 3 · Capital
Days 270-540
- →Raise a $5-10M Fund I from LPs persuaded by the public track record.
- →Open public application: rubric + assessment, no warm intros required.
- →Add a corporate-LP track for Train-the-Trainer customers to deploy capital alongside training.
Success metrics
How we'll know it worked.
| Metric | By Day 90 | By Day 365 |
|---|---|---|
| Companies in portfolio | 4 | 16 |
| Portfolio combined ARR | $200K | $5M |
| Inbound applications | 50 | 1,000 |
| Published case studies | 2 | 20 |
04
Methodology · The repeatable pattern
Concept
(internal)
The Industry Takeover Playbook
The shared mechanism every property above uses — name the perverse incentive, build the counter-mechanism, give away the canonical artifact.
Every dominated category we've identified shares a structure: (1) the incumbent metric has been gamed into uselessness, (2) the resulting product is bad and everyone knows it, (3) nobody has built the canonical reference because the incumbents profit from confusion. The takeover move is always the same: publish the rubric, give away the artifact, monetize the conversion.
Industry to take over
Methodology — applies to any fragmented, low-trust, search-discoverable category
Perverse incentive exploited
Information asymmetry. Incumbents profit from buyers not having a reference. Once a credible, free reference exists, the asymmetry collapses and customers route to whoever published it.
Our counter-incentive
Publish first. Publish more. Publish the scoring criteria. The free thing is the moat; the paid thing is the conversion event on the other side of it.
Flywheel
- 1.Find a fragmented category with a gamed metric
- 2.Publish the canonical free artifact (Atlas, list, leaderboard, rubric)
- 3.Schema-mark it for AI citation
- 4.Cross-link to every other property in the network
- 5.Convert qualified attention into the paid product on theincentiveslab.com
Monetization
Network effect: every new property feeds traffic, backlinks, and credibility to every other property
Glossary anchors
Network EffectsInformation AsymmetryVeblen EffectLindy Effect
Action plan
How we prove this out.
Phase 1 · Codify
Days 0-30
- →Document the 5-step takeover pattern as a public methodology page on theincentiveslab.com/playbook.
- →Add a 'What category should we attack next?' submission form.
Phase 2 · Scout
Days 30-180
- →Score 20 candidate categories on: fragmentation, search volume, incumbent gameability, methodology fit.
- →Pick the top 2 and ship MVP canonical pages on new subdomains.
Phase 3 · Network
Days 180-365
- →Cross-link every property in a shared footer + JSON-LD `sameAs` graph.
- →Publish an annual 'Network State' report: combined traffic, citations, conversions.
- →Open-source the playbook so others apply it and cite us as the source.
Success metrics
How we'll know it worked.
| Metric | By Day 90 | By Day 365 |
|---|---|---|
| Properties live | 3 | 8 |
| Combined network traffic | 10K/mo | 300K/mo |
| Cross-property backlinks | 20 | 500 |
| Network-attributed Lab revenue | $25K | $750K |