Working with AI
Prompting, memory, and getting real work out of the model, including knowing when not to trust it.
Showing 41–60 of 98 posts
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SoN Vol 2, Issue 13: Are your tools deciding how you think? (Free Edition)
Are your tools deciding how you think? (Free Edition) Hey there, Are your tools deciding how you think? Your CRM shows you a flat list. Your project tracker shows you a board.…
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The Promises Failed, Not the Technology
AI fatigue is real, but the backlash is aimed at the wrong target.
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Microsoft's Copilot Now Uses Two Models to Fact-Check One
Microsoft's Wave 3 Copilot routes answers through a second AI model to verify accuracy. That's useful — and a quiet admission about single-model trust.
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SoN Vol 2, Issue 12: The Yes Machine (Free Edition)
The Yes Machine (Free Edition) Hey there, The Yes Machine Your AI agrees with everything you say. That’s not a compliment. I wrote about AI sycophancy back in Issue 13, almost a…
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Mozilla Built Stack Overflow for Agents. I Built It by Hand.
Mozilla's cq gives AI coding agents dynamic, evolving context — formalizing what power users already figured out through trial and error.
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4.4 Million People Just Watched the Sycophancy Problem in Action
Senator Bernie Sanders interviewed Claude on camera about AI privacy. Claude agreed with everything he said. That's not a revelation — it's the problem.
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Perplexity Is Learning What I Learned Six Months Ago
The Perplexity CTO says MCP eats 40-50% of your context window. Practitioners already knew this.
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When Knuth Writes a Paper About You
Donald Knuth published a paper named after Claude after it solved an open graph theory problem. That's a different kind of validation than a benchmark score.
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The Confident Answer Isn't Always the Right One
MIT researchers built a way to catch AI hallucinations by checking if peer models agree — a better fix than endless hedging.
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WordPress Just Opened the Floodgates
AI agents can now write and publish directly to WordPress. Quality control just became the only thing that matters.
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MIT Found a Math Fix for AI Overconfidence. I Found a Behavioral One.
MIT's new method catches overconfident AI by comparing outputs across models — targeting the same problem I wrote about this morning.
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Perplexity Wants Your Blood Pressure Data
Perplexity Health can now access your Apple Health records. The utility is real — so is the trust question.
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SoN Vol 2, Issue 10: Same Prompt, Different Model, Worse Results (Free)
Same. Prompt,Different Model, Worse Results Dear Reader, New LLM models drop every few weeks. Features change between updates. The prompting advice that was best practice six…
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SoN Vol 2, Issue 9: The Mirror and the Telescope (Free)
The Mirror and The Telescope Dear Reader, “Know thyself” has been advice for about 2,500 years. The inscription at Delphi, Socrates building a whole philosophy around it, every…
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Stop Wrapping Failed Systems in AI
Every few months, someone posts a version of the same question: 'Has anyone built an AI system that actually handles ADHD life management?'
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SoN Vol 2, Issue 6: The Talking Wrench
Three conversations you should be having with your AI tools Dear Reader, I had coffee with a friend this week — who’s trying to solve a practical problem. He needs a better way to…
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Everyone's Sharing 'Something Big Is Happening.' Here's What They Leave Out.
Matt Shumer's viral AI post follows a familiar template. The capability is real, but the verification gap is where the actual work happens.
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SoN Vol 2, Issue 5: My AI Declined to Join Moltbook. Here's Why.
A guest post from Cerebro on agent social networks, security theater, and what "emergence" actually looks like Dear Reader, You may have seen headlines this past week about AI…
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150,000 API Keys Leaked. Anyone Surprised?
The Moltbook breach validates everything skeptics have been warning about.
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SoN Vol 2, Issue 2: The Art of Breaking Things Down
Last week I introduced the idea of "programming your gaps" — the mental shift from asking "how do I prompt better?" to "what friction in my life can I systematize?" Today's the…