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OpenAI is winding down its fine-tuning platform — the clearest signal yet. The 2026 decision framework: when RAG, prompting, SFT, RFT, distillation or DSPy wins, verified costs ($29 for a 70B LoRA), and the EMNLP research on why fine-tuning can't add knowledge.
7/28/2026
Every major AI agent breach of 2025-26 — EchoLeak, the Supabase MCP dump, Cursor RCE — shared three ingredients. The lethal trifecta, OWASP's new Agentic Top 10, MCP tool poisoning, and the defenses that actually hold in production.
7/27/2026
Swarm is dead, AutoGen and Semantic Kernel are frozen, and 57.3% of teams run agents in production. The July 2026 scorecard: LangGraph vs OpenAI Agents SDK vs Microsoft Agent Framework vs Google ADK vs CrewAI — and when to skip frameworks entirely.
7/22/2026
"RAG is dead" is back — so is the math against it. Context rot evidence (Chroma, NoLiMa, RULER), the 1M-token cost reality, and how retrieval moved up the stack into hybrid search, reranking and agentic retrieval.
7/21/2026
Up to ~10M vectors, Postgres + pgvector is still the right default in 2026. The honest scale limits, the Pinecone/Qdrant shakeout, BM25 hybrid search in Postgres, and when a dedicated vector database actually earns it.
7/20/2026
MCP went from Anthropic experiment to Linux Foundation standard in 18 months. What the Model Context Protocol is, MCP vs function calling, and what the stateless July 2026 spec changes.
7/18/2026
Every memory framework implements the same four memory types — working, episodic, semantic, procedural. Here's how to build all four on plain Postgres + pgvector, and when Mem0, Zep or Letta actually earns its keep.
7/11/2026
LLM, SLM, LRM, VLM, LCM, LAM - the AI world runs on acronyms. Here is what each type of AI model actually does in 2026, with real examples and when to use which.
7/9/2026
AI agents demo beautifully, then break in production. A practitioner's guide to the 8 failure modes — and the guardrails that keep agents shipping.
7/8/2026
Context engineering replaced prompt engineering in 2026. A production RAG engineer breaks down the techniques, the dead tricks, and the stack that ships.
7/7/2026
Claude vs GLM for agentic coding in 2026: Sonnet 5 and GLM-5.2 are ~1 point apart on SWE-bench Pro, but GLM is MIT open-weight at ~1/3 the API price. Here is when to use each.
7/6/2026
Everyone uses AI now, but developers use it in a completely different gear. Here is how engineers actually code with AI in 2026, backed by real data on tools, trust and time.
7/4/2026
The 2026 RAG tech stack, re-curated from production: frontier & open LLMs (Qwen3, DeepSeek, Kimi over Llama 4), LangGraph agents, vector DBs (pgvector, Qdrant), Docling parsing, vLLM/SGLang serving, Voyage/BGE-M3 embeddings, and DeepEval/Ragas/Langfuse for eval — with the fading 2024 tools flagged.
7/3/2026
Prompt caching stores your prompt's static prefix (KV cache) so repeat LLM requests skip recomputing it — up to ~85% lower latency and ~90% cheaper cached input. How it works, OpenAI vs Anthropic vs vLLM in 2026, prompt vs semantic caching, and the prompt-structure mistakes that silently kill your cache-hit rate.
7/2/2026
How I built an in-app AI assistant with Retrieval-Augmented Generation — chunking, embeddings, pgvector, and the tuning that keeps answers grounded.
6/29/2026