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PROJUKTI BRIEF

1  Black Forest Labs opens FLUX 3 Image, which lets you sketch the layout before it draws

With FLUX 3 Image, you place bounding boxes where each element should go, describe what belongs inside each one, and the model builds the picture to match. It is a wider release of the multimodal FLUX 3 model Black Forest Labs first launched in July. Try the editor.

2  Micron's revenue climbs to $54B as AI soaks up the world's memory chips

Micron's quarterly revenue reached $54B, up roughly 380% from $11B a year earlier, almost entirely on AI demand for memory. The company even stopped selling RAM to consumers this year to keep up with AI customers. CEO Sanjay Mehrotra expects demand to outrun supply through 2028.

3  ChatGPT's personal finance feature reaches Free and Go users in the US

First announced in May, Finances in ChatGPT lets you link bank and investment accounts so ChatGPT can answer money questions, track spending, and help build a plan. OpenAI has since added credit monitoring, stock watchlists, and weekly summaries. See what it includes.

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PROJUKTI FORWARD

The gap. As of April 2026, only 2.2% of US households paid for any AI service, according to a16z. That is double the 2025 figure, but still a tiny share for a technology that dominates the headlines and the stock market.

The disconnect. Big Tech keeps reporting record AI demand and building data centers on the scale of national infrastructure. Almost none of that demand comes from ordinary households. It comes from businesses and a small group of heavy users. a16z's chart of the gap pulled in 4M views and started a debate.

Two sides of the argument. Nicolas Bustamante argues it is still early, and most people have no idea what today's tools can already do. Others push back, saying they simply do not need AI to write an email, book a table, or check in for a flight.

Where the money is. The buyers who do pay cannot get enough. According to a16z, the top 1% of users spend about 8 times more than the top 10%. When prices drop, these customers tend to use more rather than spend less. That means AI can grow fast on a narrow base of heavy users. The open question is how long that base can carry an industry spending this much.

PROJUKTI SNAPSHOT

👀 Karpathy Returns. After two quiet months, Andrej Karpathy shared his favorite ways to get more out of AI, like asking for diagrams, HTML pages, or video explainers instead of plain text (6.7M views).

✏ The Next AI Tells. Opus 5.5 dropped the em dash habit, but a marketing firm found other giveaways, including one phrase Opus uses 116 times more often than people.

📊 Read the Axis. AI labs keep getting called out for charts that make small gains look huge. This post shows exactly why you should always check the vertical axis (6.5M views).

🧑‍⚖ Muse Goes to Court. People already use Meta's assistant to audit their inbox and cancel subscriptions. Now one founder used Muse to file a small claims lawsuit.

PROJUKTI PROMPTS

Design a lead scoring system

Act as a senior sales operations strategist. Design a practical lead scoring system for [company/product] that helps the sales team prioritize prospects most likely to convert. Context: - Target customer: [ICP/persona] - Sales motion: [SMB / mid-market / enterprise / PLG] - Average deal size: [amount] - Sales cycle: [length] - Available data: [job title, company size, industry, website activity, email engagement, demo requests, etc.] - CRM: [Salesforce / HubSpot / other] - Current problem: [too many leads / poor quality / slow follow-up / low conversion] Create a scoring model using both fit signals and intent/behavior signals. Assign clear point values, include negative scoring for weak-fit or low-intent leads, and define thresholds for Cold, Warm, Sales-Ready, and High Priority. Keep the model simple enough for reps to understand and use consistently. Finish with: 1. A scoring table 2. Qualification thresholds 3. Routing rules 4. A monthly review process to improve the model using conversion data.

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