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🤖 How To Identify Transparency Moments In Agentic AI — Smashing Magazine

• Victor Yocco's article is one of the best practical frameworks I've read for designing agentic AI experiences
• The core problem: agentic AI disappears while it works — it acts on your behalf in the background and surfaces information only when it's done — and that creates a trust gap
• Two failure modes to avoid: the black box (user has no idea what happened or why) and the data dump (so many status updates that users develop notification blindness and ignore everything)
• The fix is a decision node audit — map every step in your agent's logic, identify where it branches or makes a judgment call, and ask: does the user need to know about this?
• The impact risk matrix helps prioritise: low stakes and reversible = auto-execute and inform quietly; high stakes and irreversible = ask for explicit permission first
• Status messages matter more than we think — "processing" tells the user nothing; "liability clause varies from standard template, analysing risk level" tells them exactly what they need to know
• My favourite method from the article: have a user watch the agent work and think aloud — timestamp every moment they say "wait, what?" or "what did it just do?" — those are your transparency gaps

🚀 Rocket — A Startup That Tells You What To Build — TechCrunch

• Rocket connects research, competitive intelligence, and product strategy into one workflow — input a prompt, get a McKinsey-style PDF with pricing, go-to-market recommendations, and product requirements
• The pitch: generating code and designs is now a commodity — the real gap is knowing what to build in the first place
• I like the idea, and I think it will genuinely accelerate a lot of early-stage thinking
• But here's my challenge: it synthesises data that already exists on the internet — it cannot tell you what real users think, feel, or struggle with, because that data isn't publicly available
• My bigger concern: we are removing barriers to creation faster than we are strengthening the filters that determine if something is worth creating — the majority of products already fail because of insufficient user research, and commoditising product ideation will make that worse, not better
• My take: the more we accelerate creation, the more we need to invest in user research as a compensatory mechanism — not less

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