Case study 01 · This website

He isn't a 3D model.

The character who watches your cursor is 55 video frames, five short clips and a little trigonometry. This is how he was made, start to finish.

Scroll to turn him round

01 · Source

Shoot it on green.

Every clip starts from one master image, animated in Google Flow against a flat green wall: 720 × 1280, 24 frames a second, six seconds each. Green, because nothing he wears is.

04-look-circle.mp4 · 144 frames

02 · Key

Take the wall away.

ffmpeg removes the green. The obvious filter, chromakey, ignores brightness and ate his black sweater, so the key measures plain RGB distance instead, kept tight enough that the beard stays solid. The wipe you are scrolling is the same maths, running in a shader.

colorkey=0x109757:0.12:0.06,despill=type=green

03 · Sprite

One slow look around, cut into frames.

In a single clip he turns away from the camera, then sweeps his gaze through a full circle. Every second frame goes into one image: one pose facing you, 12 turning away, 42 around the ring.

look.webp · 8 × 7 cells

04 · Follow

The angle of your cursor picks the frame.

Move the pointer around him. Its angle maps to a place on the ring, and he gets there through the real frames in between, the short way round. Nothing is blended or generated on the fly, so nothing smears.

atan2(dy, dx) → cell 13…54

05 · Rest

Stop moving and he comes back to life.

After 1.6 seconds of stillness he returns to the camera, and a looping clip takes over from the very same pose: breathing, shifting his weight. Move again and the frames pick up where the film left off.

idle.webm · VP9 with alpha, HEVC for Safari

  • 55frames
  • 5clips
  • 2codecs
  • 03D models
Illustration of Tina and Emmanuel walking hand in hand

Case study 02 · tinaandemmanuel.me

An invitation that flows.

Our wedding invitation, built for our guests as one long scroll-painting: two streams rise in the mountains, travel side by side, and become one.

33 commits · April to October 2026

Ink drawing of the mountains where the two streams rise

01 · The world

Scroll down, travel sideways.

The page scrolls down while the world slides sideways, one pixel for one pixel. A fragment shader paints the two streams live as watercolour, rose and indigo, and the paper itself warms from dawn to dusk along the way.

River.tsx · OGL fragment shader

Illustrated portrait of the couple

02 · The confluence

Where they meet, the river rises.

At the confluence the world holds still and the water climbs over the whole screen. The two colours steep into one while a poem is read, then the water drains back and the journey goes on. The pointer stirs it; a tap sends a ring across it.

Water.tsx · two pigments, one pool

03 · Performance

Lighter every week.

The keyed videos began as a loop over every pixel on the CPU, throttled to 24 frames a second, and moved into a WebGL shader. Three.js and react-three-fiber gave way to OGL, the smooth-scroll library came out, and phones got their own smaller encodes.

CPU pixel loop → GPU shader

04 · The reply

A guest list in a spreadsheet.

A guest can be sent a link with their own name in it and be greeted by it. Replies go straight into a Google Sheet through an Apps Script, so the site needs no server and ships as a static export on GitHub Pages.

Next.js static export · Apps Script

Case studies 03–05 · Production

Now the day job.

Three systems built and shipped for 200,000 daily users, each one taken apart below.

02 // THE CHRONICLES · ARCHITECTURAL PROOF

Built With Intention.

Three engineered chronicles. Detailed dissections of production systems architected and delivered for 200,000 daily users: deterministic AI copilots, distributed batch optimizations eliminating 99.7% of database bottlenecks, and 60 FPS matrix virtualization.

“Underneath every thousand concurrent transactions, there is a human heartbeat. Underneath every optimized query, a quiet yearning for elegance.”
Chronicle I // Autonomous AI Orchestrator & UI Sync

The Clockwork Sentinel // Autonomous Enterprise Copilot

“Teaching algorithms to listen with patience and act with integrity.”

Deterministic multi-gate workflow engine capable of autonomously orchestrating high-concurrency payroll runs, biometric attendance reconciliation, and statutory filings. Features strict RBAC validation, honesty guards against masked errors, and real-time bidirectional UI viewport synchronization.

01 · The issue
5stages
between “run payroll” and money leaving the bank

A payroll cycle crosses attendance sync, calculation, audit, sign-off and statutory filing. An agent that runs them for you is only safe if a step that fails quietly cannot pass as done.

02 · What we did
  1. 1
    One gate per stage

    Each stage is a gate with its own authority check, and the run cannot skip ahead.

  2. 2
    Fail closed

    Four gates stop the run on any failure. The first halts and waits for a person to approve.

  3. 3
    Honesty guard

    An interceptor reports a silent 201 as a failure instead of letting it count as success.

03 · The result
Where a 1,420-employee run spends its time
  • M1 · Ingestion320ms
  • M2 · Worker42s
  • M3 · Audit850ms
  • M4 · SecurityInstant
  • M5 · Statutory1.2s
Audit Traceability
100%
Cryptographic action hash log
Silent API Failures
0Δ
Honesty Guard interceptor layer
Batch Run Orchestration
42s
Automated 1,420 employee cycle
Admin Policy Setup
8x Faster
Conversational interview engine
Autonomous Copilot Trace // Bangalore HQ Payroll Execution
HR Admin (Executive Role)·10:41:02 AM
Run September payroll cycle for Bangalore HQ. Auto-reconcile biometric shifts and generate statutory filing packages.
Copilot Autonomous Agent·10:41:04 AM

Initiating declarative Payroll Autopilot for Bangalore HQ (1,420 employees). Verifying pre-flight gates and biometric reconciliation...

tools.reconcile_biometric_punches(tenant_id='BLR-HQ', cycle='2026-09')ACK 200
Params: tenant='BLR-HQ', grace_window=15min
Output: 1,420 matched · 3 unregularized anomalies flagged
GATE M2 INTERVENTION: 3 employees contain unresolved late-mark anomalies exceeding statutory tolerance threshold. Human-in-the-loop authorization required.
HR Admin (Executive Role)·10:41:18 AM
Apply standard 1-day approved grace waiver for the 3 flagged records under manager override and resume computation.
Copilot Autonomous Agent·10:41:20 AM

Manager override authenticated via stored reporting authority. Signed entry written to ai_agent_auditlog. Dispatching Celery background worker...

tools.dispatch_payroll_celery_worker(batch_id='BLR-2026-09-EXEC')ACK 200
Params: chunk_size=10, throttle=50ms, replica_mode=True
Output: 142 batch tasks queued · 100% Celery worker ACK
UI Viewport Synchronization
/payroll/register?cycle=2026-09&highlight=batch_running
Copilot Autonomous Agent·10:42:02 AM

Payroll computation verified in 42.0s with zero variance errors. Compiling statutory compliance bundle (PF ECR, ESI, PT, Form 24Q).

tools.export_compliance_package(types=['PF_ECR', 'ESI', 'PT', 'TDS'])ACK 200
Params: cycle='2026-09', format='GOV_STATUTORY_V2'
Output: 4 statutory packages sealed · Payout challan generated
STEP 6 OF 6
Chronicle II // Distributed Database Optimization & Telemetry

Rivers in the Machine // High-Throughput Batch Optimization

“When twenty thousand records flow without friction, code becomes quiet water.”

Engineered distributed performance overhaul for core batch calculations servicing 150K–200K active employee records across multi-tenant environments. Eliminated cascading N+1 database queries via bulk replica joins and built resilient asynchronous request logging queues with automatic reconnect retry.

01 · The issue
5,001queries
for one 2,500-employee batch

Every employee triggered its own override read and payout write: 2N+1 queries. At this size the run takes about 70.4s, past the 60s load balancer ceiling, so it ends in 504s and retry storms while holding 96% of the connection pool.

02 · What we did
  1. 1
    Bulk replica preloads

    One read-replica call loads the tenant's register, joined in memory by hash index.

  2. 2
    Resilient telemetry queue

    Audit writes moved off the response cycle onto an async queue with an immediate single retry.

  3. 3
    Hardened tenant scoping

    Directory export lookups carry a tenant predicate, so nothing crosses tenants.

03 · The result
Before and after, same batch
  • DB queries · before5,001
  • DB queries · after3
  • Run time · before70.4s
  • Run time · after0.8s
  • Connection pool · before96%
  • Connection pool · after7%

Modelled figures. Drag the simulator below to change the batch size.

Telemetry Reliability
0Dropped Rows
Resilient async queue with instant retry
Interactive Batch Volume Simulator

Drag slider to observe computational divergence between legacy iterative N+1 queries and the optimized batch read-replica engine.

Simulated Batch:2,500Employees
500 Employees2,500 (Mid-tier org)5,000 (Enterprise)10,000+ (High-Scale Matrix)
Telemetry 01 // Database Query Waterfall & Volume
Database roundtrips generated for 2,500 employee payroll calculation:99.9% Network Roundtrips Saved
Legacy Sequential Pipeline (N+1 Query Loop)5,001 DB Queries (O(N) Explosion)
5,001 Queries
Optimized Architecture (Bulk Read-Replica Join + In-Memory Preload)3 Batched Queries (O(1) Flat)
3
Detailed Query Execution Breakdown:
Legacy Iterative Loop:
  • 1x Batch initialization fetch
  • 2,500x Employee override queries
  • 2,500x Bulk payout status writes
  • Total: 5,001 TCP network roundtrips
Optimized Read-Replica Batch:
  • 1x Bulk pay register fetch from read-replica
  • 1x Bulk copy-override in-memory hash join
  • 1x Chunked payout status batch update
  • Total: Exactly 3 batched queries (O(1) invariant)
1. Bulk Replica Preloads:

Eliminated the per-employee query cascade by materializing tenant company registers in one read-replica call and performing in-memory hash index joining.

2. Resilient Telemetry Queue:

Decoupled API response cycles from DB audit writes using an asynchronous request_queue with immediate single retry to survive broker disconnects.

3. Hardened Tenant Scoping:

Enforced tenant predicate scoping on directory export UUID lookups to structurally guarantee zero cross-tenant entity leakage.

Chronicle III // High-Scale Frontend Virtualization

The Infinite Loom // High-Throughput Virtualized Pay Register

“Rendering only what the human eye can touch, leaving the rest to imagination.”

Real-time payroll register stress-test demonstrating row windowing over massive 10,000+ data sets. Decouples DOM complexity from dataset volume for a locked 60 FPS experience with microsecond frame budgets.

Engine Mode:
01 · The issue
42.8ms / frame
against a 16.6ms budget

The pay register mounted every row it was given. With 1,120+ DOM nodes live, scrolling fell to about 18 FPS and memory sat at 186MB.

02 · What we did
  1. 1
    Window the rows

    Only the rows inside the viewport are mounted, plus three either side as overscan.

  2. 2
    Fixed row height

    Every row is 44px, so the first visible row is one division with nothing to measure.

  3. 3
    One offset

    A spacer keeps the full scroll height and the mounted rows are translated into place.

03 · The result
Before and after, 10,000 rows
  • Frame time · before42.8ms
  • Frame time · after< 1.5ms
  • DOM nodes · before1,120+
  • DOM nodes · after28
  • Memory · before186MB
  • Memory · after14.2MB

Switch Engine Mode below to scroll both versions.

Scroll Refresh Rate
60.0FPS
Locked vsync cadence
Mounted DOM Nodes
28Nodes
Fixed O(1) viewport bound
Memory Footprint
14.2MB
-92% garbage collection overhead
Frame Render Budget
< 1.5ms
Under 16.6ms frame threshold
LIVE REPO DATASET: 10,000 EMPLOYEE SALARY RECORDS
Scroll container below to test 60 FPS frame pacing
Record ID
Employee / Role
Department
Gross Pay
Net Pay
Status
PAY-200001
Engineer #1001 (Senior SDE)
Distributed Infrastructure
₹1,20,137
₹98,513
Dispatched
PAY-200002
Engineer #1002 (Systems Architect)
AI Research
₹1,20,274
₹98,625
Audited
PAY-200003
Engineer #1003 (Lead Developer)
Product Engineering
₹1,20,411
₹98,738
Verified
PAY-200004
Engineer #1004 (Infrastructure Specialist)
Data Systems
₹1,20,548
₹98,850
Dispatched
PAY-200005
Engineer #1005 (Staff Engineer)
Core Platform
₹1,20,685
₹98,962
Audited
PAY-200006
Engineer #1006 (Senior SDE)
Distributed Infrastructure
₹1,20,822
₹99,075
Verified
PAY-200007
Engineer #1007 (Systems Architect)
AI Research
₹1,20,959
₹99,187
Dispatched
PAY-200008
Engineer #1008 (Lead Developer)
Product Engineering
₹1,21,096
₹99,299
Audited
PAY-200009
Engineer #1009 (Infrastructure Specialist)
Data Systems
₹1,21,233
₹99,412
Verified
PAY-200010
Engineer #1010 (Staff Engineer)
Core Platform
₹1,21,370
₹99,524
Dispatched
PAY-200011
Engineer #1011 (Senior SDE)
Distributed Infrastructure
₹1,21,507
₹99,636
Audited
PAY-200012
Engineer #1012 (Systems Architect)
AI Research
₹1,21,644
₹99,749
Verified
SHOWING ROWS 1–12 OF 10,000
ZERO DOM-THRASH GC RECYCLING ACTIVE
Emmanuel's character at his desk, coding across two monitors

Chapter 04 · The handshake

Your move.

That is the story so far. The next chapter could be yours: I am available for engineering roles where concurrency, rendering performance and systems quality matter most.

Immediate joinerBangalore, India

Emmanuel Wilson//Frontend & Systems Engineering