SEPTEMBER 24, 2025

• PromptCraft: Sharpen Outputs, Find Your Blind Spots, Get Rid of Perfectionism, and Challenge Your Thinking with These 16 Prompts
• NewsDive: 25 Business Intelligence Uses for Generative AI
• THE HEADLINES: Faster-cooling chips; AI parenting; AI demands for 10 nuclear reactors; Facebook Dating uses AI to combat 'swipe fatigue'; OpenAI mobilizes for AI device
• Tool Spotlight: Strata Is Your GPS to Thousands of Tools and Apps

Sharpen Outputs, Find Your Blind Spots, Get Rid of Perfectionism, and Challenge Your Thinking with These 16 Prompts

• ​Eight prompt styles for sharper outputs: Practical set including Outcome Contract, Data→Decision table, Assumptions+Tests, Two Drafts/Two Purposes, Constraint-Box Creativity, Counterexample/Limitations, Platform Remix Pack, and an Action Board. Each forces clarity, constraints, and measurable follow-through for tighter, more specific responses.
• ​Blindspot Revealer framework uncovers hidden problems: A copy-pasteable prompt system that converses to collect context, then surfaces “blind spots” with evidence and actions. Built around memory-aware questioning, multi-lens analysis, and structured output so you get tailored diagnoses, not generic advice.
• ​Perfectionism Detox Specialist prompt: Role prompt that treats overachievement like an addiction: assess “toxicity,” identify withdrawal patterns, prescribe relapse-prevention, and deliver one shock intervention. Useful when standards stall shipping; pairs mindset reframes with concrete rules of done and next steps.
• ​Five prompts to challenge your thinking: “Assumption Detector,” “Devil’s Advocate,” “Ripple Effect Analyzer,” “Blind Spot Illuminator,” and “Status Quo Challenger.” Each targets a different cognitive failure mode and returns pointed critiques plus corrective plans to de-romanticize pet ideas.
• ​“Final Boss” YouTube learning prompt: A rigorously sequenced, 12-step analysis pipeline for long videos (concept extraction → analogies → counterpoints → applications → spaced recall). Forces step-by-step reasoning so you leave with durable notes, examples, and practice tasks—not shallow summaries.

25 Business Intelligence Uses for Generative AI

Most Are Ways Typical ChatGPTers Ignore

Generative AI helps business intelligence teams turn raw data and documents into decisions. Below are practical use cases across marketing, sales, operations, finance, and governance. For each one, you’ll see what goes in, what methods are common, and the output leaders can act on.

Revenue and Marketing Analytics

Marketing mix modeling and budget reallocation. Feed the model with channel spend, impressions, product price, promotions, and seasonal patterns. Modern mix models account for carryover and saturation, so weekly return curves make sense in the real world. The output includes the marginal return by channel and a budget plan that allocates funds to the channel with the highest return. Teams that follow these plans often target a ten to twenty percent lift in return on ad spend.

Campaign uplift modeling. Use treatment and control logs to find people who change their behavior because of the campaign—not those who would convert anyway. Causal uplift models surface who to target and who to leave alone. The result is a target list, a “do not target” list, and a lower cost per incremental conversion.

Next‑best offer and bundle optimization. Train on carts, product catalog data, and text or vector embeddings of product content. The system suggests the next offer at checkout or through the customer relationship management system and proposes bundles that pair well together. Expect higher attach rates and a lift in average order value when these offers are tested and rotated.

Lead scoring and routing. Combine firmographic data and every touchpoint from the customer relationship management system to score the chance to close by account. Apply service‑level agreements in the rules so hot leads go to the right rep fast. The payoffs are higher win rates and shorter speed‑to‑lead.

Price elasticity and promotion lift by region and product. Hierarchical demand models use your prices, promotions, competitor pricing, and seasonality to estimate how quantity changes with price at each level. The deliverable is an elasticity matrix and a list of “safe” price moves that protect margin. Leaders track margin dollars gained, not just volume moved.

​CHECK OUT THE REST ON SUBSTACK​

HIGHLIGHTS: Faster-cooling chips; AI parenting; AI demands for 10 nuclear reactors; Facebook Dating uses AI to combat 'swipe fatigue'; OpenAI mobilizes for AI device

• ​AI chips are getting hotter. A microfluidics breakthrough goes straight to the silicon to cool up to three times better.​
• ​AI Is Coming for Parents​
• ​The AI Kids Take San Francisco​
• ​OpenAI and Nvidia’s $100B AI plan will require power equal to 10 nuclear reactors​
• ​Will AI end the world? AI ‘prophet of doom’ speaks to Newsnight​
• ​Facebook Dating tries using AI to end ‘swipe fatigue’​
• ​Hitachi agrees to acquire German data and AI services firm synvert to accelerate Agentic AI and Physical AI development, driving global expansion of HMAX business​
• ​Helping protect journalists and local news from AI crawlers with Project Galileo​
• ​What Are the 2 Best Bargain Artificial Intelligence (AI) Stocks to Buy Right Now?​
• ​Will AI Disrupt Tech’s Most Valuable Companies?​
• ​AI buildouts need $2 trillion in annual revenue to sustain growth, but massive cash shortfall looms — even generous forecasts highlight $800 billion black hole, says report​
• ​How Can We Meet AI’s Insatiable Demand for Compute Power?​
• ​How are developers using AI? Inside Google’s 2025 DORA report​
• ​China’s Huawei hypes up chip and computing power plans in fresh challenge to Nvidia​
• ​Deploy your own AI vibe coding platform — in one click!​
• ​A ‘global call for AI red lines’ sounds the alarm about the lack of international AI policy​
• ​Oracle Corporation Announces Promotion of Clay Magouyrk and Mike Sicilia to CEOs; Safra Catz Appointed Executive Vice Chair of the Board of Directors​
• ​OpenAI taps Apple supplier to make AI device, the Information reports​
• ​MediaTek Dimensity 9500 Unleashes Best-in-Class Performance, AI Experiences, and Power Efficiency for the Next Generation of Mobile Devices​
• ​Why we built the Responses API​
• ​Introducing SEAL Showdown: Real People, Real Conversations, Real Rankings​

Strata Is Your GPS to Thousands of Tools and Apps

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Strata is like a GPS for your AI agents: one MCP server that guides them step-by-step through thousands of tools across apps, so they choose the right action without token bloat or “choice paralysis.” Instead of dumping every tool into context, Strata progressively narrows the path—intent → app → category → action—making complex, multi-app workflows far more reliable.

It’s open-source, works via UI or API, supports custom MCP servers, and ships with evals showing \~+15% pass\@1 gains vs baseline GitHub/Notion servers—plus a $200 credit to get started.

Learn more: https://www.klavis.ai​

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