Available for opportunities

Hi, I'm Bishal Regmi

Backend developer based in Kathmandu, Nepal. I build APIs that handle real traffic, databases that stay fast under load, and systems that don't page you at 3 am.

Technologies I work with

GoTypeScriptNode.jsNestJSPostgreSQLMongoDBRedisGraphQLTypesenseAWSDockerKubernetes
~/backend-projects — zsh
go run main.go
Starting server on :8080...
✓ Database connected successfully
✓ Redis cache initialised
✓ Server ready to handle requests
INFO [2026-07-04] Performance optimised ⚡
3+ Years exp
16 Blog posts
10+ Projects
Coffee cups

What I do

01

API & backend architecture

REST and GraphQL APIs, service boundaries, and data models designed to stay maintainable as traffic and team size grow.

🗄️ 02

Databases at scale

Schema design, indexing, and search infrastructure — PostgreSQL, Typesense, Redis — tuned to stay fast under real production load.

☁️ 03

Cloud & infrastructure

Deploying and operating services on AWS with Docker, thinking through failure modes and rollback paths before they matter.

💳 04

Payments & real-time systems

Idempotent payment integrations, object storage lifecycles, and real-time features built to survive retries and race conditions.

Recent writing

  • Chaos Engineering: Building Resilience, Not Just Features

    Learn why breaking things on purpose with Chaos Engineering makes your production systems stronger, faster, and more reliable.

    chaos-engineeringreliabilitysrekubernetesmicroservices
  • LLM Observability: Trace Agents, Track Tokens, Detect Lies

    Master LLM observability to debug complex AI agents, optimize token costs, and spot hallucinations with OpenTelemetry and NLI models. A 10x guide.

    llm-observabilityopentelemetryai-agentstracingcost-attributionhallucination-detectionnli
  • The Agent Loop: Tool Use, ReAct, and Memory from Scratch

    Learn how to build a production-ready AI agent from first principles: master function calling, ReAct loops, and memory design in Python, avoiding common…

    ai-agentsllm-opspythonbackendsystem-design
  • Why Your 16-Core Database Isn't Multithreading Queries

    Your beefy database server has 16 cores, but queries feel slow. Discover why PostgreSQL might not be using parallel execution, and how to fix it.

    postgresqlparallel-querydatabaseperformancebackend
  • Idempotency: The Unsung Hero of Resilient Systems

    Discover why idempotency is non-negotiable for distributed systems. Learn to prevent duplicate operations, build resilient APIs, and safeguard critical…

    system-designapi-designdistributed-systemsresilienceidempotency
  • Embeddings: The Silent Scalability Trap

    Discover how embedding models, while powerful, can become a critical bottleneck in AI systems. Learn about dimensionality, Matryoshka, and fine-tuning.

    ai-engineeringembeddingsllm-opsscalabilitymlops
  • PostgreSQL's Query Planner: Decoding Optimal Execution

    Demystify the PostgreSQL query planner's core decisions. Understand how the cost-based optimizer picks query plans and master EXPLAIN ANALYZE for peak…

    postgresqlquery-optimizerexplain-analyzedatabase-performanceinternals
  • Circuit Breaker: Stop Microservice Cascade Failures Cold

    Learn why the Circuit Breaker pattern is vital for microservices, preventing cascade failures with clear states and thresholds. Essential reading.

    microservicesresiliencecircuit-breakerbackend-patternsdistributed-systems
  • RAG Accuracy: The Chunking Problem You're Missing

    Boost RAG accuracy by mastering document chunking. Learn token, sentence, semantic, and parent-child strategies to fix common pipeline failures.

    ragllmchunkingnlpbackend
  • Prompt Engineering Isn't Dead, It's Grown Up

    Why structured outputs, JSON mode, and programmatic prompt optimization are making prompt engineering reliable, testable, and production-ready.

    llmai-engineeringbackendprompt-engineeringdevops
  • Designing a Notification System: Fan-Out and Delivery Guarantees

    Patterns and guarantees for building notification systems that scale: fan-out strategies, retries, idempotency, and delivery guarantees.

    notificationssystem-design
  • PostgreSQL Query Planner Internals: How the Cost-Based Optimizer Chooses a Plan

    An overview of PostgreSQL's planner: cost model, statistics, join ordering, and why the wrong plan gets chosen sometimes.

    postgresqlbackendperformance
  • Redis Cluster: The 16384 Slots and the Gossip Beneath

    A deep dive into Redis Cluster's internals: hash slots, gossip protocol, resharding, MOVED/ASK redirects, and failover mechanics.

    redisclusterdistributed-systemshigh-availabilitycaching

Get in touch

Best way to reach me is email. I read everything and reply within a day or two.