A DAILY AGENTIC DEV LOOP YOU CAN PILOT THIS WEEK
A practitioner video outlines a repeatable daily workflow for building and iterating on LLM agents: start with a narrow task, instrument runs (traces, prompts, ...
A practitioner video outlines a repeatable daily workflow for building and iterating on LLM agents: start with a narrow task, instrument runs (traces, prompts, outputs), run quick evals on a small dataset, then refine prompts/tools and redeploy. The emphasis is on short feedback cycles, cost/latency tracking, and keeping prompts, test cases, and traces under version control.
Gives teams a concrete structure to experiment with agents without derailing delivery.
Improves reliability via traceability, small-scope evals, and measurable gates.
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Stand up a minimal agent pipeline with tracing and cost/latency logging; compare against a scripted baseline on one recurring backend task.
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Create 10–20 golden test cases and add an eval step to CI that must pass before prompt/tool changes deploy.
Legacy codebase integration strategies...
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Wrap agent calls behind a feature flag and route logs to existing observability to avoid invasive changes.
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Start with non-critical workflows (e.g., data enrichment or ticket triage) and enforce PII redaction at boundaries.
Fresh architecture paradigms...
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Design agents as stateless services with idempotent tool calls, retries, and timeouts, then containerize with resource caps.
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Define prompt/test artifact repos from day one and wire an offline eval harness into CI/CD.