Most data stacks are excellent at answering: “What happened?” Very few are good at remembering: “Why did we decide this?” That’s a massive blind spot. Every meaningful decision creates context: • assumptions • confidence level • alternatives considered• time pressure And then… it disappears. High-maturity data systems include decision memory. Here’s what that looks like: 1️⃣ Decision Logging Not just outcomes, but: • what signals triggered action • what thresholds were crossed • who (or what) made the call 2️⃣ Assumption Tracking Every decision is tied to assumptions. When assumptions change, the system flags it. 3️⃣ Outcome Attribution Did the decision Help ?Hurt? Have no effect? Most teams track results but not causality. 4️⃣ Feedback into Models Signals that consistently mislead get down-weighted. Reliable ones gain influence. This turns hindsight into learning. 5️⃣ Retrieval at Decision Time When a similar situation appears, the system surfaces: • past decisions • outcomes • lessons This is institutional memory — automated. Data alchemy isn’t about storing facts. It’s about remembering judgment. The future belongs to systems that don’t just analyze the past, but learn from their own decisions.

Hi everyone. I was really hoping to unlock the third level, now that the community is going to be shut down, could you please help me to reach it so that I could still take a pick at the classes? Thank you!

Everyone’s obsessed with making AI predict outcomes — revenue, churn, demand, sentiment. But the true leap forward isn’t in prediction…it’s in perception. AI is learning to see reality as it shifts. It notices when your customers’ tone changes, when your product’s positioning starts slipping, when data stops behaving normally. That’s not forecasting —that’s awareness. The next generation of systems won’t just answer questions —they’ll sense when the right question needs asking. That’s the moment when AI becomes more than analytics becomes adaptive intuition. And the data leaders who design for perception — not just prediction —will build the most resilient companies of the decade.

People talk about “finding insights” in their data as if it’s a treasure hunt. But real insight doesn’t just appear — it’s engineered. Every valuable data insight starts with a great question. - What are we really trying to understand? - What variable actually drives this outcome? - What pattern matters, and what’s noise? AI helps us see faster, but not think better — that’s still on us. The best data teams don’t wait for magic moments. They build systems that generate insight consistently. In the end, insight isn’t luck. It’s design, iteration, and interpretation — the real alchemy of intelligence.

New articles generated by AI briefly outnumbered those written by humans online, but the two are now roughly equal, per a new report from SEO firm Graphite. Why it matters: Researchers have long feared that if AI-made content online overwhelms human-created material, large language models could choke on their own exhaust and collapse. The big picture: A 2022 report from Europol estimated that 90% of online content would be generated by AI by 2026. - According to Graphite's analysis of 65,000 URLs that were posted online between 2020 and 2025, the percentage of AI-generated articles rose sharply after ChatGPT's launch in 2023. - The percentage of AI-generated articles in this data set briefly surpassed human-written articles in November 2024, but the two have stayed roughly equal since. https://www.axios.com/2025/10/14/ai-generated-writing-humans