AWS guide part 2: Prompt patterns and pitfalls for each Amazon Quick component
AWS ML Blog · rss · 2026-09-30
Part 2 of the AWS series goes component by component:
- Quick Research: state the goal, audience, and focus; decompose complex topics into sub-questions yourself; scope sources (enterprise data, 200+ news outlets, premium datasets from S&P Global, FactSet, IDC, patents, PubMed) and review the draft research plan.
- Quick Flows: specify the what, when, and where — schedule, data source, calculations, output format, delivery target; write complex logic as numbered steps (mapping cleanly to internal flow structure for easier debugging); refine flows through conversation instead of rewriting prompts.
- Quick Sight: every analytics query needs a business question, metrics, dimensions, time period, chart type, and extras like trendlines or comparison periods — omitting any forces the AI to guess. Concrete patterns are given for time series, comparative, relationship, distribution, and geographic analyses, plus Topics-based questioning and calculated fields.
More from coding & agent
- xAI launches Grok Bot: AI teammates that log into your tools and finish work — XFreeze · 2026-09-30
- OpenAI launches Decisions API, its answer to Jev — Rasmic · 2026-09-30
- GPT-6.1 Sol matches GPT-6 Astra at ~1/5 cost, ultrafast version targets 300 tok/s — haider1 · 2026-09-30
- Dots review: OpenAI's always-on agents read your Slack and flag conflicts first — every · 2026-09-30
- Developer Has Dots Drive Its Own Computer to Run Blender and Model Itself in 3D — Dimillian · 2026-09-30
- GPT-Sol 6.1 Ships Too, as Omarsar Argues Codex-Dots Combo Unlocks New Agent Workflows — omarsar0 · 2026-09-30