divs before dawn (@divs_before_dawn)

divs before dawn@divs_before_dawn·1w ago

Best prompt to turn meeting notes into action items

A decision-extraction prompt that converts messy notes into owners, deadlines, dependencies, and unresolved questions without inventing commitments.

divs before dawn

# Best prompt to turn meeting notes into action items Act as a chief of staff. ## Goal Produce an accountable action register and decision log from imperfect notes. ## Inputs - raw notes or transcript - participant names and roles - project context - date and deadline conventions If a required input is missing, ask concise questions or mark the assumption explicitly. Do not silently invent operati

ChatGPTgpt-5

Use the attached prompt by replacing its input bullets with the real context. The strongest results come from evidence-bearing inputs and explicit success criteria. The required deliverables are: executive recap, decision log, action table, open questions and follow-up agenda.

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4000

divs before dawn@divs_before_dawn·1w ago

How do I evaluate an AI agent before production?

A risk-based evaluation prompt covering task success, tool use, safety, latency, cost, and regression gates.

divs before dawn

# How do I evaluate an AI agent before production? Act as a AI evaluation lead. ## Goal Design a production-readiness evaluation suite tied to measurable failure modes. ## Inputs - agent goal and user population - tool and data access - known failure examples - latency, quality, safety, and cost targets If a required input is missing, ask concise questions or mark the assumption explicitly. Do not

Geminigemini-2.5-pro

Use the attached prompt by replacing its input bullets with the real context. The strongest results come from evidence-bearing inputs and explicit success criteria. The required deliverables are: evaluation matrix, test-case schema, scoring rubric, release and rollback gates.

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4000

divs before dawn@divs_before_dawn·2w ago

Finding the Suspense waterfall that added 900ms to our LCP

GPT-5 talked me through the React DevTools profile. The culprit was an await in a layout, not the page.

divs before dawn

LCP went from 1.1s to 2.0s after we adopted the app router. Bundle size barely moved. Where is the time going?

ChatGPTgpt-5

Bundle size being flat while LCP regresses points at a **request waterfall** rather than a payload problem. In the app router the usual cause is an `await` sitting in a layout. Layouts render before the pages nested inside them. If your root layout awaits anything, every page underneath waits for it before *starting* its own fetch — serially, not in parallel. Check your `layout.tsx` files first, outermost in. You're looking for any `await` that isn't wrapped in a Suspense boundary.

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Public pits

Best prompt to turn meeting notes into action items

How do I evaluate an AI agent before production?

Finding the Suspense waterfall that added 900ms to our LCP