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Same open-weight model, two very different servers. One is a datacenter throughput engine; the other runs anywhere. Here's which one your agent backend actually wants — and the GGUF caveat to know first.
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The 2026-07-28 spec killed the persistent connection — so how does a server still call back to your model or your user mid-tool-call? The answer is MRTR, and it's a resume loop you drive from the client.
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OpenAI's open-weight workhorse fits on one H100 because of MXFP4. Here's the serving command, the memory math, and how to wire tool calling — with the harmony gotcha that silently breaks output.
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Skip the framework. An agent is an LLM calling tools in a loop — here's the ~40 lines that run it, the three context moves that keep it from rotting, and how to hang a real MCP tool off it.
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Anthropic ships four levers for keeping a long-running agent inside its window. The comparison pieces tell you which is which — this one wires all four together in one loop, in code.
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A stack trace tells you a normal service died. It tells you almost nothing about why an agent did the wrong thing. Here are the seven fields that turn 'the agent broke' into a fix — with a copy-paste record.
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The classic 'five whys' assumes a deterministic chain. An agent that fails at temperature 0.7 breaks that assumption. Here's a postmortem template built for non-deterministic systems — blameless, reproducible, and shippable.
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Google shipped a code-execution sandbox that lives inside your existing Cloud Run instance — millisecond starts, deny-by-default egress, and no extra bill. Here's the copy-paste path from a model's Python output to a safe result, and where the isolation stops.
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LanceDB and Chroma give you retrieval. mem0 and Zep give you memory. Teams reach for a memory layer when a vector database would have done — and reach for a raw vector database when they're about to rebuild mem0 by hand. Here's the line between them.
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They look like rivals but answer three different questions. Pick by the job — discovery or extraction — not by the logo you saw first.
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Passing a bare string to a LanceDB full-text index tokenizes it and ORs the terms — good enough until a user types a phrase, a typo, or a term that only matters in one column. The query classes fix all three, and they're a few lines each.
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A multi-turn agent that spins up a fresh sandbox every turn loses its filesystem, its installed packages, and its running processes each time. Here's the exact pause/resume code — and the auto-pause config that stops you paying for idle boxes between turns.
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No more Mcp-Session-Id header, no initialize handshake — here's the exact client-side change, with copy-pasteable code.
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E2B's Build System 2.0 kills the e2b.Dockerfile and the `e2b template build` CLI step — you define the sandbox environment in Python or TypeScript, and the build runs itself. Here's the exact code, and the one capability it unlocks that a Dockerfile never could.
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A deep agent's harness is a context-window and latency tax you pay up front to survive long tasks. On short ones it buys nothing. Here's the line.
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If you build on Qwen or DeepSeek APIs, this law almost certainly doesn't touch you — unless your product is a persistent emotional companion.
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Langfuse's v4 SDK rewired everything onto OpenTelemetry, so the way you instrument an agent changed. Here's the current, copy-paste path from an empty file to a scored trace — with the v3→v4 renames that will bite you if you copy an old tutorial.
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CrewAI's built-in memory resets every run and lives in a local SQLite file. This is the copy-paste walkthrough for swapping in Mem0 so a crew remembers a user across sessions — both the managed Cloud path and the self-hosted OSS one.
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Pure vector search misses exact terms — product SKUs, error codes, function names — that your agent's retrieval has to nail. This is the copy-paste walkthrough for combining semantic and keyword search in LanceDB with an FTS index and a reranker, in about a dozen lines.
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Every agent that validates a file path with realpath() and then opens it has a race window. An attacker — or the model's own concurrent code — swaps a symlink in that window and your allow-list writes to /etc. Here's the bug, the class of 2026 CVEs proving it's live, and the atomic fixes that actually close it.
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A copy-pasteable walkthrough for founders shipping a coding or data-analysis agent — execute model-generated Python in an isolated E2B microVM, capture stdout/stderr, enforce timeouts, and kill runaway processes without touching your own server.
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