Browse Comments — Raw (as collected)

Oh dear, looks like I'm in... what's that word again, hold on let me ask Claude... oh yes: trouble.

Thank you for all your advice 🙏

Great way to present that AI is not just two letters

Claude is amazing and by far the hest AI tool i am using. I have completed with Claude the interactive worksheets for my ICP -> SaaS Founders, created skills for my business growth such as marketing, my business ideal customer persona (with whom I'm chatting each day) and exploring Claude design recently. It for sure works best with the real life cases!

The best plan for beginners to master Claude!

Great to see Anthropic taking a lead here and consulting sources of wisdom to guide AI adoption across a broad ideological spectrum. The real question is, is it all fluff or are they going to back it up with serious business strategy and values?

AI only becomes valuable when it starts absorbing the messy context of your actual day instead of living inside isolated experiments.

The scary part about AI isn’t just job replacement. It’s that humans get meaning, identity, routine, and social connection from work too. Society is not psychologically prepared for that conversation yet.

Olu Olojo we have agency. We choose to use AI when and if appropriate. You cant just learn with AI. AI is a tool but not the tool box. And we have used varied assessment methods for decades before AI arrived.

This is insane.

The useful part here is starting with an actual task instead of treating it like software to explore. That usually gets you to a workable setup faster and cuts a lot of random clicking.

Roll on retirement

What exactly is the groundbreaking revelation here? Half the studys participants were primed for the task of solving fractions manually. The other half were not primed and had to context switch to handle it. Are we surprised people prepared for a task perform better than those who are not? People who are surprised by a task don't do as well as those who have been doing the task consistently for an hour?

Luís Rodrigues This is a useful way to frame the AI stack. LLMs, RAG, agents, and MCP - each solve a different problem, but enterprise value only appears when they are designed together around workflows, controls, and business outcomes. Deepesh Khandelwal, MBA, PMP, SA

✔️✔️✔️

The real question is not what humans will do when AI does the work. It is what humans will do when the work they currently do loses its social meaning. Work provides structure, status, and community. If we automate the output without replacing those three things, we get efficiency without dignity. Pascal naming redesign of participation as the unresolved problem is the hardest truth in the entire AI transition.

Very interesting 🔥🔥🔥

authenticity and integrity

Michael Ladomery that’s excellent. AI can do it better. You too have a pleasant day. 😊

This is the part that matters most for enterprise governance. The issue is not whether a particular lab is well-intentioned. Some clearly are. The issue is that good intentions do not neutralize the incentive structure. If frontier AI labs operate under commercial pressure, capital pressure, geopolitical pressure, and speed-to-market pressure, then enterprise buyers should not treat vendor assurances as a complete governance basis. That does not mean AI should not be adopted. It means adoption has to be authorized against present capability, disclosed limitations, model-change risk, output-shaping controls, and the actual conditions under which reliance is justified. Self-governance is not enough when the market is also selling the reliance. I wrote about this from the adoption-integrity side here: https://www.linkedin.com/pulse/real-ai-risk-sell-just-system-paul-mcdonald-bqave The market is selling the projection. The law has to make them show the machinery.