https://learnbackend.com You already ship backend systems. Learn to ship LLM systems to production: RAG, agents, evals, cost and latency. A free, text-first track for engineers. en https://learnbackend.com/ai-engineering/working-with-llm-apis/model-versioning-and-deprecations/ https://learnbackend.com/ai-engineering/working-with-llm-apis/model-versioning-and-deprecations/ Model IDs are versions, aliases move under you, and deprecations have deadlines. How to pin, monitor, and upgrade your LLM dependency like any other. Mon, 13 Jul 2026 00:00:00 GMT https://learnbackend.com/ai-engineering/working-with-llm-apis/conversation-state-and-history/ https://learnbackend.com/ai-engineering/working-with-llm-apis/conversation-state-and-history/ The LLM API keeps no session state, so your chat feature needs a transcript store, a token budget, and a truncation strategy. Build all three. Mon, 13 Jul 2026 00:00:00 GMT https://learnbackend.com/ai-engineering/working-with-llm-apis/anatomy-of-an-llm-stream/ https://learnbackend.com/ai-engineering/working-with-llm-apis/anatomy-of-an-llm-stream/ What an LLM stream actually sends: OpenAI chunks vs Anthropic events, delta aggregation, mid-stream errors, and canceling generations nobody is reading. Mon, 13 Jul 2026 00:00:00 GMT https://learnbackend.com/ai-engineering/working-with-llm-apis/failure-modes-and-degradation/ https://learnbackend.com/ai-engineering/working-with-llm-apis/failure-modes-and-degradation/ LLM calls fail three ways: real errors, hangs, and 200s that lie. Map each failure to what your API serves instead, from a cached copy to a hidden feature. Mon, 13 Jul 2026 00:00:00 GMT https://learnbackend.com/ai-engineering/working-with-llm-apis/rate-limits-and-capacity/ https://learnbackend.com/ai-engineering/working-with-llm-apis/rate-limits-and-capacity/ RPM and TPM are capacity contracts, not suggestions. Read the rate-limit headers, throttle client-side, and plan token headroom before the 429s arrive. Mon, 13 Jul 2026 00:00:00 GMT https://learnbackend.com/ai-engineering/working-with-llm-apis/provider-abstraction/ https://learnbackend.com/ai-engineering/working-with-llm-apis/provider-abstraction/ Design the one seam every LLM call goes through: a normalized client interface over OpenAI and Anthropic dialects, and when to buy a gateway instead. Mon, 13 Jul 2026 00:00:00 GMT https://learnbackend.com/guides/llm-api-retries-timeouts-fallbacks/ https://learnbackend.com/guides/llm-api-retries-timeouts-fallbacks/ An error-by-error playbook for LLM calls: which failures to retry (and which never), stage-aware timeouts, model fallback chains, and why naive retries are a money bug. Sat, 11 Jul 2026 00:00:00 GMT https://learnbackend.com/guides/pgvector-vs-pinecone-vs-qdrant/ https://learnbackend.com/guides/pgvector-vs-pinecone-vs-qdrant/ A backend engineer's decision framework for vector storage: when pgvector in your existing Postgres wins, when a dedicated engine earns its keep, and the sync-pipeline tax nobody prices in. Sat, 11 Jul 2026 00:00:00 GMT https://learnbackend.com/guides/streaming-llm-responses-sse-vs-websockets/ https://learnbackend.com/guides/streaming-llm-responses-sse-vs-websockets/ Which transport to stream LLM tokens through your backend (SSE, raw fetch streaming, or WebSockets), with a relay implementation, proxy gotchas, and a decision table. Sat, 11 Jul 2026 00:00:00 GMT https://learnbackend.com/guides/add-llm-to-existing-backend/ https://learnbackend.com/guides/add-llm-to-existing-backend/ Six production patterns for adding LLM features to an existing backend, with code: inline endpoint, queue worker, internal gateway, pgvector retrieval, event enrichment, and flagged rollout. Fri, 10 Jul 2026 00:00:00 GMT https://learnbackend.com/ai-engineering/llm-foundations/what-llms-actually-do/ https://learnbackend.com/ai-engineering/llm-foundations/what-llms-actually-do/ A backend engineer's mental model for LLMs: next-token prediction, weights vs context, stateless chat APIs, and why hallucination is a property to engineer around. Thu, 09 Jul 2026 00:00:00 GMT https://learnbackend.com/ai-engineering/llm-foundations/tokens-context-windows-and-limits/ https://learnbackend.com/ai-engineering/llm-foundations/tokens-context-windows-and-limits/ Tokens are the byte of LLM systems: the unit of billing, latency, and memory. Learn to budget a context window and calculate real monthly costs before you ship. Thu, 09 Jul 2026 00:00:00 GMT https://learnbackend.com/ai-engineering/llm-foundations/your-first-llm-api-call/ https://learnbackend.com/ai-engineering/llm-foundations/your-first-llm-api-call/ Demystify LLM APIs with raw curl calls, message roles, the parameters that matter, streaming, and key hygiene, for backend engineers. Thu, 09 Jul 2026 00:00:00 GMT https://learnbackend.com/ai-engineering/llm-foundations/choosing-a-model-like-a-database/ https://learnbackend.com/ai-engineering/llm-foundations/choosing-a-model-like-a-database/ A backend engineer's map of the mid-2026 LLM landscape: model tiers, real costs per million tokens, and a decision framework that actually works. Thu, 09 Jul 2026 00:00:00 GMT https://learnbackend.com/ai-engineering/llm-foundations/non-determinism-latency-and-cost/ https://learnbackend.com/ai-engineering/llm-foundations/non-determinism-latency-and-cost/ Three properties of LLM calls that violate backend intuition (non-deterministic output, alien latency profiles, and token-based cost) and what to do about each. Thu, 09 Jul 2026 00:00:00 GMT https://learnbackend.com/ai-engineering/llm-foundations/the-production-ai-stack/ https://learnbackend.com/ai-engineering/llm-foundations/the-production-ai-stack/ A component-by-component tour of a production LLM system, each piece mapped to backend infrastructure you already run, and the roadmap for this track. Thu, 09 Jul 2026 00:00:00 GMT https://learnbackend.com/blog/relaunching-learnbackend/ https://learnbackend.com/blog/relaunching-learnbackend/ Why this site now teaches backend engineers to ship LLM systems to production, and what the free track covers, module by module. Thu, 09 Jul 2026 00:00:00 GMT