OldKnowledge,New Vessel.
Essays on on-device AI, data sovereignty, and building systems that keep knowledge where it belongs.
Enter the archive →— 00 / ThesisEvery business runs on knowledge older than its software.
Latest Entries
KV-Cache Offloading: Serving 10x More Users by Not Recomputing
Feature Flag Architecture: Rollouts, Kill Switches, and Flag Debt
Distributed Locks: Redlock, Fencing Tokens, and Why Your Lock Doesn't Lock
The CAP Theorem, PACELC, and What Real Databases Actually Choose
Connection Pooling: PgBouncer, RDS Proxy, and the Serverless Postgres Problem
अथ प्रथमोऽध्यायः ॥
विद्या ददाति विनयं विनयाद् याति पात्रताम् ।
पात्रत्वाद्धनमाप्नोति धनाद्धर्मं ततः सुखम् ॥
We digitize centuries-old manuscripts. Then we build with the same discipline.
AppScale's roots are in a quiet project: structuring classical Sanskrit texts into faithful digital form. Extraction, structure, provenance, sovereignty — the same principles now power our client work.
Built for Every Business
Intelligence that never leaves the device
Offline-first, data-sovereign systems — LLMs, vector search, inference at the edge.
02Document IntelligenceAir-gapped document vaults
Sealed, searchable, provable.
03AI ProductsFull-cycle AI product builds
Mobile-first, production-grade.
04MCP & AI SecuritySecuring the agentic stack
Tool poisoning, prompt injection, confused deputies — studied and hardened.
05Indic Language AIOCR for scripts the world forgot
Sovereign OCR for Indic scripts.
06Consulting & Architecture19+ years shipping at scale
OTT, e-commerce & mobility platforms serving millions.
KV-Cache Offloading: Serving 10x More Users by Not Recomputing
Your GPU re-prefills the same 15,000-token prompt ten thousand times a day. KV-cache offloading to DRAM and NVMe turns that recompute into a cheap fetch — 10x users.
Feature Flag Architecture: Rollouts, Kill Switches, and Flag Debt
Ship code to production without releasing it to everyone. Feature flags done right: release vs kill-switch types, sticky rollouts, failure defaults, and killing flag debt.
Distributed Locks: Redlock, Fencing Tokens, and Why Your Lock Doesn't Lock
A billing system double-charged 14 customers through a lock that worked exactly as documented. Redlock, fencing tokens, advisory locks, and when to delete the lock.
The CAP Theorem, PACELC, and What Real Databases Actually Choose
The pick-two triangle is a misunderstanding: partitions happen regardless. PACELC, quorum arithmetic, and what DynamoDB, Spanner, and Postgres actually choose.
Connection Pooling: PgBouncer, RDS Proxy, and the Serverless Postgres Problem
A team raised max_connections from 100 to 5,000 and throughput fell. Connection pooling done right: PgBouncer modes, RDS Proxy, sizing math, and the serverless trap.
Multi-Cloud AI: Cost-Aware LLM Routing Without the Lock-In
An enterprise spent nine months duplicating its AI stack across two clouds; every real incident was a quota ceiling. Multi-provider routing: the architecture that pays.
LLM-as-a-Judge vs Deterministic Heuristics: Who Grades the Model?
A judge scored 4.6/5 for months while users churned over wrong answers. When to use LLM-as-a-judge, when deterministic checks win, and the calibration that separates them.
Rust vs C++ for On-Device Inference Engines
Memory safety versus bare-metal control for mobile AI engines. Where the three crash classes live, why ecosystem gravity beats safety, and where to put the unsafe seam.
The CACTUS Framework: Automated Data Quality Gates for RAG
Your RAG hallucinates because the corpus is wrong, not the model. The six CACTUS data-quality gates, the heuristic-vs-judge cost split, and how to measure it.
Batch LLM Inference: Processing Millions of Documents Without Going Broke
A classification backfill through the chat endpoint turned a $400 job into $3,000 and still failed. Batch LLM inference: half the cost, resumable, built for finite jobs.
PromptOps: Managing Prompts as Code Before They Break Production
One prompt edit, shipped with no version history and no eval, silently regresses production for a week. PromptOps: prompts as versioned, tested, rollback-able code.
TOGAF vs Zachman: Do You Still Need an EA Framework in 2026?
TOGAF is a method, Zachman a taxonomy, and neither works as shipped. The decision table, where both fail, and the slim EA stack that survives contact with 2026.
Flutter and React Native at Scale: When Many Teams Share One App
Three squads in one mobile codebase means merge queues, 45-minute CI, and blocked releases. Feature modules, monorepo tooling, and the tribe topology that fix it.
ACID Transactions and Isolation Levels, Explained with Failures
Dirty reads, lost updates, and write skew: the bugs each isolation level permits, what Postgres and MySQL actually default to, and the cheapest weapon per write path.
Database Sharding vs Partitioning: Scaling Beyond One Box
Partitioning makes one box manageable; sharding makes many boxes act as one database. The decision table, shard-key design, and the scaling ladder to exhaust first.
Loop Engineering for AI Agents: The Complete Guide
"I don't prompt Claude anymore. My job is to write loops." The complete guide to loop engineering: brakes, context rot, tool contracts, and the verifier that says no.
Kafka vs RabbitMQ vs SQS: Choosing a Message Broker
Kafka vs RabbitMQ dissolves once you name the workload: a log for facts many systems read and replay, a queue for jobs done once. The decision table and AI angle.
Database Indexing: How B-Trees Power Postgres and MySQL
The same query: 2ms or 3,000ms — the difference is one B-tree. How database indexes actually work, composite column order, covering indexes, and when the planner says no.
JWT vs Sessions: Authentication Architecture That Doesn't Bite Back
The decade-old JWT vs sessions fight has a boring answer: both, deliberately. Short access JWTs, rotating refresh tokens, httpOnly cookies, and a real revocation story.
Background Jobs and Task Queue Architecture: BullMQ, Celery, and SQS
The request cycle is for accepting work; the queue is for doing it. BullMQ vs Celery vs Sidekiq vs SQS, the five production requirements, and the AI-batch job shape.
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