Omar Motala

Omar Motala

Builds AI products, public policy dashboards, legal analytics, and agent infrastructure.

Yale University · Harvard Law School

Six projects

COORD layered hero: the mesh network, the two token-usage panels and the COORD jobs board with the usage strip.

01Agent coordination system

COORD

Coordinates coding agents (Claude, Codex) and tracked jobs through one SQLite-WAL database.

SQLite-WAL database
1
views, board to iOS
6
public source
MIT
ApartmentScout layered hero: the heat-map dashboard with ranked listings, the 3D city and the furnished interior.

02Apartment comparison tool

ApartmentScout

Ranks a rental shortlist on weighted fit, effective rent, commute, building records and modeled sun.

weighted fit dimensions
11
finalists compared
4
walkthrough
72 s
Three Telly iPhone screens fanned on gold light: the viewer archetype, the For You home feed and the Severance title screen with ratings.

03Native iOS app

Telly

Builds a taste profile and viewer archetype from watch history, rates titles and recommends what to watch.

rating providers per title
9
product demo
51 s
on TestFlight
Beta
Climate Hostility layered hero: the US net-hostility map dashboard with the state ranking, the Topics and Diffusion landscape and a bill drawer.

04Public policy dashboard

Climate Hostility

Maps and ranks US state climate and ESG legislation by direction, policy universe and status.

annual bill attempts
1,524
policy universes
3
bill statuses tracked
4
Trippy layered hero: the route map across European cities, the route optimizer and the Explore each city chooser.

05Travel planner

Trippy

Ranks whole-route city orders, compares cash versus points and hotel stays; shared board for group planning.

stops per route, at most
9
booking states
6
export formats
4
SCOTUS OT2025 per-justice scorecard header: 148 of 171 justice votes and 17 of 19 case outcomes right, above the first rows of the case grid.

06Legal prediction model

SCOTUS Prediction

Predicts each justice’s affirm/reverse vote, then the case outcome.

justice votes (148 / 171)
87%
case outcomes
17 / 19
OT2025 decided cases
19
COORD layered hero: the mesh network, the two token-usage panels and the COORD jobs board with the usage strip.View full size

01Agent coordination system

COORD

Coding agents and jobs, coordinated through one database.

Local coordination system for coding agents (Claude, Codex) and tracked jobs. One SQLite-WAL database is the lifecycle authority; CLI, Python and MCP clients share it.

SQLite-WAL database
1
views, board to iOS
6
public source
MIT
COORD jobs board listing running and paused work, with the usage strip above it showing Claude session, weekly and Fable bars, Codex weekly, and CPU, GPU, RAM and disk gauges.
1Board and usage stripRunning and paused jobs under Claude, Codex, CPU, GPU, RAM and disk bars. Dollar figures are recorded token-cost estimates.Tracked CPU, GPU, API and MLX jobs with process-derived liveness, resource locks and dead-run recovery.
2Provider usageCapture loopThe usage capture, scrolled. Dollars are recorded token-cost estimates, not money paid. Full captureOriginal PNGClaude Personal, Claude Team and Codex quotas; session and weekly resets; runout estimates; daily token-cost history.
Uncropped COORD macOS menu-bar dropdown: CPU, GPU, RAM and disk readouts, Claude and Codex usage bars, active work by agent and the Next Up queue.
3macOS menu barUncropped capture; scroll inside the frame. Original PNGCPU, GPU and RAM; active work by agent; the queue. Native views are read-only by default.
Flattened 2D COORD mesh: a ring of agent and work nodes with fan-out spokes and labelled module clusters.
4MeshLive projection, flattened to 2D: agents, work, dependencies and evidence.Live read-only projection of agents, work, dependencies and evidence, grouped into labelled modules.

Captures: mesh, usage and menu views come from the author’s installed environment. The public repo ships the generic system with synthetic demo data.

ApartmentScout layered hero: the heat-map dashboard with ranked listings, the 3D city and the furnished interior.View full size

02Apartment comparison tool

ApartmentScout

Rent, commute and sunlight, weighed together.

Renter’s tool for comparing an apartment shortlist. Ranks listings on weighted fit, effective rent, commute, building records and modeled sun.

weighted fit dimensions
11
finalists compared
4
walkthrough
72 s
ApartmentScout in one screen: ranked Manhattan listings on the left, the 3D heat map in the middle and the open unit’s drawer with a furnished-room photo, rent breakdown and rank reasons on the right.
1Rank and commuteRanked listings, the 3D heat map and the open unit’s drawer with rent breakdown and rank reasons.11 weighted fit dimensions; rent adjusted for concessions and fees; door-to-door commute by time of day to multiple destinations.
2Unit in 3DLoopThe furnished living room, panning toward the bay window and the city. Modeled interior.Floor-plan tracing, furniture placement and clearance checks, in synchronized 2D and 3D.
Side-by-side modeled window views from the same building: floor 8 in shadow and floor 25 in direct sun.
3Sun by floorSame window, same moment: floor 8 in shadow, floor 25 in direct sun.Modeled sun and shadow by floor, date and time, from building footprints and heights.
Modeled 3D Midtown skyline at dusk with landmark labels and the unit’s tower highlighted in blue.
43D city at duskModeled Midtown at dusk; landmarks labelled, the unit’s tower in blue.Modeled city around the unit: its tower and window marked, landmarks labelled, day and night orbits.
5Walkthrough72 seconds, with controls and sound. Try the interactive demo ↗The 72-second walkthrough; the interactive demo runs in the browser.

Example: a fall-2026 Manhattan shortlist. Interiors, sunlight and commutes are models and estimates; prices are historical examples.

Three Telly iPhone screens fanned on gold light: the viewer archetype, the For You home feed and the Severance title screen with ratings.View full size

03Native iOS app

Telly

Your watch history, turned into a taste profile.

SwiftUI iPhone app. Builds a taste profile and viewer archetype from watch history, rates titles and recommends what to watch.

rating providers per title
9
product demo
51 s
on TestFlight
Beta
Product demo51 seconds, with sound controls.
Provider ratingsFight Club: nine provider scores, adjusted for you.
Fight Club title screen: where-to-watch row and a 3 by 3 grid of provider scores labelled adjusted for you.

At a glance

Taste
Taste profile and viewer archetype from watch history
Ratings
Rates titles; recommends what to watch
Ask
Natural-language search and recommendations: Ask Telly, Concierge
App
SwiftUI, iPhone; TestFlight beta
Backend
AWS Lambda, DynamoDB, Cognito, API Gateway, EventBridge
On iPhoneTitle screens with scores from several rating providers, adjusted for you, and three silent loops from the demo.
For You home feed with a rated poster rail and a list of recommendations.
Home feed
Captain America: Civil War title screen with poster, provider scores, a Telly score and an Add button.
Title screen
Feed to title · loop
Concierge · loop
Archetype · loop
Climate Hostility layered hero: the US net-hostility map dashboard with the state ranking, the Topics and Diffusion landscape and a bill drawer.View full size

04Public policy dashboard

Climate Hostility

State climate and ESG bills, mapped and ranked.

Public dashboard of US state climate and ESG legislation. Maps and ranks bills by direction, policy universe and status.

annual bill attempts
1,524
policy universes
3
bill statuses tracked
4
Live dashboardLoopMap toggles anti / pro / net; rankings and annual trends follow.

Filters

Direction
Anti-ESG or pro-ESG
Universe
Corporate/Fiduciary ESG, Climate, Broad
Status
Binding, symbolic, pending, dead

Views

Map
National net-hostility map
Rankings
Top 10 / 15 / 25 states
Counts
Combined, enacted, attempts
Trends
Annual, by status and mechanism; topic flows
Topics & DiffusionESG keyword frequency over time, topic evolution and topic × stance.
Topics and Diffusion view: 19 distinct topics, 7,910 clause assignments, ESG keyword frequency lines, a topic evolution area chart and topic-by-stance bars.

Topics

distinct topics
19
clause assignments
7,910
anti-leaning topics
12
pro-leaning topics
6
State profileTexas: composition, focus, mechanisms.
Top of the Texas state profile: bill count tiles, a composition bar, stance breakdown by focus and the mechanism architecture table.
Bill detailTX SB13. Scroll inside the frame.
Bill drawer for Texas SB13: operative summary, status and stance tiles, mechanism and reach flags, severity bars and source passages.

Drill-down · Stack

Drill-down
State profiles, representative bills, exports
Built with
Data modeling, policy taxonomy, static deployment
Paper
Companion paper, Harvard Law
Trippy layered hero: the route map across European cities, the route optimizer and the Explore each city chooser.View full size

05Travel planner

Trippy

Every city order, tried and ranked.

Open-source multi-city travel planner (TypeScript, Next.js; beta). Compares city order, nights and gateways across air, rail and car legs.

stops per route, at most
9
booking states
6
export formats
4
Trippy decision lab: Optimize route ranks three whole-route city orders with score, confidence, known cost and missing legs, above flight, rail and car options for one leg.
1Route optimizerThree city orders scored with confidence, known cost and missing legs, above the per-leg options for Kraków to Brussels.Ranks whole-route city orders across air, rail and car legs, with elapsed time, transfers and coverage gaps.
Explore each city: seven stops with idea counts and nights, a strip of activity photos and the first stop’s city card above its waypoint map.
2CitiesSeven stops with idea counts and nights, a photo strip, and the city card above its waypoint map.Each stop with its nights, idea count, photos and a waypoint map.
Cash versus points workbench for Kraków to Brussels: direct and connecting cash fares, award points, taxes and positioning, giving best cash, award cash cost and cents per point. Sample inputs.
3Cash vs pointsSample inputsKraków to Brussels: best cash, award cash cost and cents per point.Fares, awards, taxes, transfer ratios and point valuations recorded together; cents per point. Sample inputs.
Kraków activities: category chips, must, should and could filters and photo cards with time allowances and Add to day.
4ActivitiesKraków: category chips, must / should / could filters, photo cards with time allowances.Must, should and could tiers; photo cards added to days.
Export studio previewing a visual itinerary for the 2026 Europe trip with a large aerial photo.
5ExportExport studio: visual dossier or compact brief, with a photo cover.HTML, PDF, JSON and CSV. Six booking states kept distinct: a quote never becomes a confirmation.

How the optimizer works

  1. Ranks city orders. Tries every order of the middle cities, first and last fixed (up to 9 stops); takes the best recorded option per leg; scores each route 1–99 with confidence and known cash.
  2. Weighted trade-off. Cost, time, transfers, reliability and carbon, weights summing to 1; Balanced value, Lowest cost and Shortest practical time presets.
  3. Gaps count against a route. Each missing leg costs 11 points; backtracking is penalised and stated.
  4. Cash vs points. Points spent from transfer ratio, minimum and block size; cents per point = (best cash − award taxes − positioning) ÷ points; award favoured at 1.5¢+.
  5. Multi-leg scenarios. Gateways incl. open jaws; through, separate or mixed tickets; cash per currency and points per programme.
  6. Must / should / could. Activities tiered, dragged onto days, grouped within 1.5 km.

Itinerary, stays, output

Itinerary
Dated editor with photo activity cards
Stays
Price basis and cancellation terms
Shared board
Ideas, votes, reviewed changes
Scenarios
Undo/redo, snapshot restore
Exports
HTML, PDF, JSON, CSV

Note: screens show recorded sample plans, not live inventory or bookings. The hosted demo is older and may lag the source.

SCOTUS OT2025 per-justice scorecard: title, tiles reading 148 of 171 justice votes right and 17 of 19 case outcomes right, a legend and the first case rows under nine justice headshots.View full size

06Legal prediction model

SCOTUS Prediction

Nine justices, predicted vote by vote.

Predicts each justice’s affirm/reverse vote, then the case outcome, for the Supreme Court’s OT2025 term.

justice votes (148 / 171)
87%
case outcomes
17 / 19
OT2025 decided cases
19
Per-justice scorecardAll 19 decided cases; green right, red wrong.
SCOTUS OT2025 per-justice scorecard: a grid of 19 decided cases by nine justices, each predicted vote green when right and red when wrong, with a right-count column.

Model

Stage 1
Each justice’s affirm/reverse vote
Stage 2
The case outcome
Scope
Only the 19 decided OT2025 cases
Missed
Chatrie and Watson (case outcomes)
With model confidenceEach call with its confidence; misses in red.
Scorecard with best-model confidence: every justice cell shows the predicted call and a confidence percentage; misses shaded red.
Ideology axesJustice × six doctrinal axes. A model input.
Heatmap of nine justices across six doctrinal axes with signed positions, blue liberal-leaning and red conservative-leaning; a model input.

Scholarship

Three papers · Harvard Law and Yale

Cover page of the paper State ESG Legislation and Financial Judgment.

Harvard Law research paper

State ESG Legislation and Financial Judgment

A doctrinal and empirical account of the anti-ESG wave and state control over analysis, association, and market conduct.

Download DOCX ↓
Cover page of the paper ESG Regulatory Divergence: EU, SEC, and California Climate Disclosure.

Harvard Law research paper

ESG Regulatory Divergence: EU, SEC, and California Climate Disclosure

A comparative analysis of climate disclosure requirements across major regulatory regimes and their implications for corporate governance.

Download DOCX ↓
Cover page of the thesis Redefining Corporate Purpose.

Yale thesis

Redefining Corporate Purpose

An institutional political economy analysis of corporate purpose, market institutions, and the public architecture around firm behavior.

Download DOCX ↓

Spec sheet

All six projects at a glance

Project index
PreviewProjectWhat it doesKey figureStackLink
01COORDCoordinates coding agents (Claude, Codex) and tracked jobs through one SQLite-WAL database.6 views over one databaseSQLite-WAL; CLI, Python, MCP; macOS, iOSSource ↗
02ApartmentScoutRanks a rental shortlist on weighted fit, effective rent, commute, building records and modeled sun.11 weighted fit dimensionsInteractive web demo; synchronized 2D and 3DDemo ↗Source ↗
03TellyBuilds a taste profile and viewer archetype from watch history, rates titles and recommends what to watch.9 rating providers per titleSwiftUI; AWS Lambda, DynamoDB, Cognito, API Gateway, EventBridgetellytech.ai ↗
04Climate HostilityMaps and ranks US state climate and ESG legislation by direction, policy universe and status.1,524 annual bill attempts surfacedData modeling, policy taxonomy, static deploymentLive ↗
05TrippyRanks whole-route city orders, compares cash versus points and hotel stays; shared board for group planning.6 booking states kept distinctTypeScript, Next.js; open source; betaSource ↗Old demo ↗
06SCOTUS PredictionPredicts each justice’s affirm/reverse vote, then the case outcome.148 / 171 votes (87%); 17 / 19 outcomesTwo-stage prediction: votes, then outcomeNo public link

01COORD

AuthorityOne SQLite-WAL database; CLI, Python, MCP
ClaimsLeased claims; version-fenced handoffs
CompletionGated on declared artifacts; independent review
JobsCPU, GPU, API, MLX; liveness; locks; dead-run recovery
ViewsBoard, Mesh, Map, Atlas, macOS menu bar, iOS
UsageQuotas, resets, runout and token-cost estimates

02ApartmentScout

Ranking11 weighted fit dimensions; unknowns visible
RentAdjusted for concessions and fees
CommuteDoor-to-door, by time of day, multiple destinations
BuildingsRecords and complaint patterns (NYC)
InteriorsTracing, furniture, clearances; 2D and 3D
SunBy floor, date and time from footprints and heights
DecideUp to 4 finalists; questions; memo; tour-day plan

03Telly

TasteProfile and archetype from watch history
RatingsRates titles
RecommendWhat to watch next
LanguageAsk Telly and Concierge: natural-language search and recommendations
ClientSwiftUI, iPhone; TestFlight beta
BackendLambda, DynamoDB, Cognito, API Gateway, EventBridge

04Climate Hostility

CoverageUS state climate and ESG bills; 1,524 annual attempts
DirectionAnti-ESG / pro-ESG
UniversesCorporate/Fiduciary ESG; Climate; Broad
StatusBinding, symbolic, pending, dead
ViewsNet-hostility map; top 10/15/25; counts; trends; topic flows
Drill-downState profiles; representative bills; exports

05Trippy

RoutingCity order, nights, gateways; air, rail, car
OptimizerWhole-route ranking; weighted cost, time, transfers, reliability, carbon
PointsFares, awards, taxes, transfer ratios, valuations; cents per point
StaysPrice basis and cancellation terms
GroupShared board; scenarios; undo/redo; snapshots
OutputHTML, PDF, JSON, CSV; 6 booking states

06SCOTUS Prediction

Stage 1Each justice’s affirm/reverse vote
Stage 2Case outcome
Votes148 / 171 correct (87%)
Outcomes17 / 19 correct
ScopeOnly the 19 decided OT2025 cases

Contact

Omar Motala · Yale University · Harvard Law School

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