@the55kings Qazi young mahi kanika uditi/arifhsa are the top 5 of this season and they will make qazi young top 2 with kanika at 3.
It's a rigged show. Bkl maine galti Kari gullu ki wjh se wps dekhkr
@HaterKarnataka BIG L
He was just copying old contestants scripts of picking up fights and unnecessary drama. He always tried to create things to show himself in limelight. (Ain't real irl )
@MOHAMMADTamee14@HaterKarnataka Still nahi jeet paate log iske baad bhi
He literally won every argument with logic inmai se ek bhi reply nahi de pata tah usko
. Aaise to they made vivian top 2 and idk kitne favours diye honge ussh.
As a Backend Engineer in the AI era, you must build these projects.
1.) High-Concurrency HTTP Server
Build: Go or Rust server handling 10k+ concurrent connections with graceful shutdown and backpressure.
Why: Concurrency architecture is the one thing AI cannot design for you.
2.) Multi-Tenant Hybrid Search Database
Build: Postgres with Row-Level Security + pgvector + BM25 hybrid ranking across isolated tenants.
Why: Structured data and semantic embeddings now share one query engine.
3.) Event-Sourced Order Pipeline
Build: Kafka or NATS pipeline with immutable events, dead-letter queues, exactly-once semantics.
Why: AI workloads are slow and async. The main thread must never block.
4.) Durable Onboarding Workflow
Build: 3-day Temporal workflow with checkpoints, retries and human approval steps.
Why: Background jobs are for emails. Durable execution is for multi-step agents.
5.) AI Gateway with Semantic Cache
Build: Proxy that caches similar prompts via embeddings, enforces token budgets and fails over to a cheaper model on 503s.
Why: The gateway protects your margins and your uptime from flaky, expensive LLM APIs.
6.) PII-Redacting Auth Middleware
Build: OAuth2/OIDC provider plus middleware that masks PII before logging and restricts AI agents to read-only DB roles.
Why: When agents can write to your database, a prompt injection is a data breach.
7.) Real-Time Streaming Dashboard
Build: SSE/WebSocket dashboard streaming LLM tokens and database updates simultaneously with backpressure.
Why: Time-To-First-Token and perceived latency are the new UX standards.
8.) Correlated Tracing Pipeline
Build: OpenTelemetry + Langfuse pipeline linking each HTTP request to the exact LLM prompt and DB query it triggered.
Why: You cannot debug a hallucination without replaying the exact context the model saw.
9.) Ephemeral Environment Provisioner
Build: Terraform or Pulumi scripts spinning up a complete isolated staging environment for every pull request.
Why: Manual deployments are a liability. Infrastructure must be version-controlled and reproducible.
10.) Queue-Based Autoscaler
Build: KEDA autoscaler spinning nodes up on Kafka queue depth and down when empty with spot-instance fallback.
Why: Backend engineers now own the cloud bill. Idle resources burn runway.
11.) Globally Distributed Rate Limiter
Build: Redis-backed distributed rate limiter that survives network partitions gracefully.
Why: Architecture must degrade gracefully not cascade into total outage.
12.) Chaos Engineering Suite
Build: Fault-injection harness (latency, replica kills, partitions) with SLO burn dashboards.
Why: Resiliency is proven under failure not in diagrams.
13.) Webhook Reconciliation Engine
Build: Idempotent event processor with exponential backoff, dead-letter queues and replay tooling.
Why: Real integrations fail constantly. Reconciliation is what makes them trustworthy.
14.) Cost-per-Request FinOps Dashboard
Build: Per-tenant, per-endpoint, per-LLM-call cost rollups with anomaly alerts.
Why: Visibility is control. You cannot optimize what you cannot attribute.
15.) Public Architecture Teardown
Build: 3 published deep-dives with system diagrams, ADRs and latency/cost benchmarks.
Why: Senior engineers are hired for their judgment not their syntax.
Systems that prove you can scale, secure & ship when agents touch your stack.
Most people watch tutorials. Builders ship systems.
Bookmark & Repost.