Agent Design Patterns: Run Four Control Flows and Their Failures
Run a fixed workflow, router, bounded tool loop and parallel join. Inspect which steps run, which stop and what evidence reaches the reviewer.
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Run a fixed workflow, router, bounded tool loop and parallel join. Inspect which steps run, which stop and what evidence reaches the reviewer.
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Compare a Python agent backend, a LangGraph chat UI and a full-stack chatbot, then reproduce a pinned starter inspection without paid inference.
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Reproduce a local Pydantic Evals run, then compare Promptfoo, LangSmith, Braintrust and plain Python against the same dataset and scoring rules.
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Make a Claude Messages API request in Python, validate its JSON response, and test authentication, rate limits and bad output with local fixtures.
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Run ten ticket cases through two deterministic baselines, inspect wrong labels and timeouts, and retain failures in a reproducible evaluation report.
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Run a SQLite approval lifecycle that rejects changed, stale, expired and revoked proposals, then returns a completed local receipt on retry.
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Run a four-step ticket workflow with validated dependencies, a dispatch budget, cancellation and traces of failed prerequisites.
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Run a SQLite preference store with owner scoping, versioned updates, provenance, expiry and deletion, then verify it from fresh Python processes.
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Run a six-document retrieval and answer pipeline, inspect citations, exclude private and outdated evidence, and measure an intentional synonym failure.
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Run a versioned Python MCP server and client, discover a ticket-label tool, and test valid calls, schema failures and protocol errors.
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Run a Python tool-calling loop with schemas, argument checks, matched results, turn limits and ten deterministic success and failure fixtures.
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Build one local ticket-review flow in Cursor, then verify proposal, approval, stale rejection and retry behavior through the UI and real HTTP checks.
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