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Applied AI infrastructure, agent systems and reverse engineering.

Studying
Information Systems, UMN, semester 5
Based
Tangerang, Indonesia, GMT+7
Status
Open to internships

JaysonChristopher
Lim

I build the layer under AI products: model routing, agents that delegate, memory they share, and data pulled out of systems that were never meant to be read. Lately, a product of my own.

Now shipping · my product

Lintasi

Setiap rit sampai tepat waktu.

Every trip arrives on time.

A trip tracker for Indonesian trucking offices. Dispatchers follow every truck on one screen, drivers report through a WhatsApp link with nothing to install, and every finished trip grades the vendor on that route.

Status
Live at lintasi.id
Auth
Phone + PIN, device-approval 2FA
Data
Stored in Indonesia, backed up daily
Plans
Gratis 15 trips/mo, Pro Rp 199k/mo
Screens show demo data.

J5 EV DashboardReverse engineering2026

73 bytes, no documentation.

CarLinko's cloud sends my car's whole state as one packed blob. I mapped it by driving and watching which bytes moved, then built a self-hosted dashboard on top.

J5 EV Dashboard showing 301 km of range and 65% battery
payload · 73 bytesonly bytes behind the screen were captured
charge cost matched to real PLN receipts
99.6 to 99.9%
charge cost matched to real PLN receipts
same offsets, four countries
4 cars
same offsets, four countries
stars on GitHub
21
stars on GitHub
Repository

Agent-to-Agent OfficeAgent systems2026

Agents that delegate, in plain sight.

A pixel office where agents hand real work to each other: files, shell, web search. A plain-text tag becomes a real JSON-RPC 2.0 call under Google's A2A protocol.

Agent-to-Agent Office: pixel-art office with agents at desks and chat bubbles
office stream
  • > @Thinker tell Kevin to write hello.txt
  • ▍
commits mine, in the 9router fork it runs on
157 / 576
commits mine, in the 9router fork it runs on
LLM providers with fallback
40+
LLM providers with fallback
tools per agent
12
tools per agent
Repository

RouteBenchLLM infrastructure2026

Routing rules, not leaderboards.

Runs the code each model writes against real tests in three languages, makes it repair a broken repo turn by turn, then exports which model should get which task.

RouteBench profile cards scoring two models 91 out of 100
ExecuteRepairRoute

routebench.routing.v1

{
  "primary_model": "model-a",
  "fallback_models": ["model-b"],
  "category_rules": [ ... ]
}
passing tests
200
passing tests
runtimes: python, javac, node
3
runtimes: python, javac, node
production dependencies
0
production dependencies
Repository

memory-coreAgent memory2026

One memory, every agent.

A long-term memory on my home server that Claude Code, Codex and Aider all read and write over MCP. Postgres with pgvector, a local CPU embedder, keyword and meaning search fused.

memory_recallsample data

claude-code asks why does the server keep freezing?

hit · 148 ms · NVMe drops off the PCIe bus; reboot=pci brings it back

Postgres + pgvectorlocal embedderRRF fusion
right memory in top 10, 80 questions
100%
right memory in top 10, 80 questions
median recall
150 ms
median recall
Claude Code, Codex and Aider share it
3 agents
Claude Code, Codex and Aider share it

9router #1144Open source2026

A fix, merged upstream.

GPT-5.5 and DeepSeek streamed Read limits like 25999999999999999. Claude Code rejected the call and retried, burning tokens. I buffered the streamed tool arguments and clamped the limit.

decolua/9router · pull/1144Merged
-  "limit": 25999999999999999+  "limit": 2000

Streamed tool arguments are buffered until complete, then Read's limit is clamped.

decolua/9router
Merged
decolua/9router
clamped Read limit
2000
clamped Read limit
Pull request

How I work

I direct the build. Then I check it against reality.

  1. Frame

    Every project starts from a gap I hit myself: a car app hiding its data, agents forgetting yesterday, trucks nobody could see.

  2. Design

    I work through the architecture with AI as a research partner, and write down the decisions before any code exists.

  3. Direct

    Claude Code writes much of the code. I set the shape, review every change and keep the system coherent.

  4. Validate

    Nothing ships on the model's word. Receipts, real sessions, real drivers: the result has to match how the world behaves.

Tools I reach for

PythonTypeScriptFastAPINext.jsReactNode.jsFlutterSQLPythonTypeScriptFastAPINext.jsReactNode.jsFlutterSQL
DockerPostgres + pgvectorSupabaseTailscaleCloudflare TunnelMCPClaude CodeOllamaDockerPostgres + pgvectorSupabaseTailscaleCloudflare TunnelMCPClaude CodeOllama

Contact

Read the code. Then talk to me.