•twitter2888
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2888
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+24%
903 positive
1780 neutral
205 negative
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Sep 30 – Oct 4, 2026 · Daily
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5
mentions
Showing 201–205 of 205 mentions
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• twitter 2d negativeAs 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 Databas… 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 requeview source ↗
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• twitter 2d negativePewdiepie casually explained why you should learn coding better than Indian influencers whose entire career is teaching coding😭😭 https://t.co/Y0VueT9F2b Pewdiepie casually explained why you should learn coding better than Indian influencers whose entire career is teaching coding😭😭 https://t.co/Y0VueT9F2bview source ↗
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• twitter 2d negativeWorking in tech means fumbling generational wealth every few years 😭 https://t.co/IrbuzVVLDr Working in tech means fumbling generational wealth every few years 😭 https://t.co/IrbuzVVLDrview source ↗
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• twitter 3d negative@IbrahimElkamali Holy shit this is so bad. I’m 3 minutes in and everything he’s saying I’m doing “wrong” is how having a real job worked, even before AI. @IbrahimElkamali Holy shit this is so bad. I’m 3 minutes in and everything he’s saying I’m doing “wrong” is how having a real job worked, even before AI.view source ↗
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• twitter 3d negativewhat’s happening to chief ai officers 😭 https://t.co/VdlzLHY6Tx what’s happening to chief ai officers 😭 https://t.co/VdlzLHY6Txview source ↗