『David's Saturday AI Thoughts』のカバーアート

David's Saturday AI Thoughts

David's Saturday AI Thoughts

著者： David Boyle
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今ならプレミアムプランが3カ月 月額99円

2026年5月12日まで。4か月目以降は月額1,500円で自動更新します。

概要

 Each Saturday, David Boyle reflects on what feels important in the world of AI. Not the breathless hype or the doom. The practical, analytical perspective: what happened this week, what it means for people who use language models in their work, and what to try next. David is Director of Audience Strategies and co-founder of Steadman. He advises organisations from L.E.K. Consulting to the BBC on AI adoption. This podcast is a spoken-word version of his Saturday AI Thoughts newsletter, with different voices for each section.© 2026 Steadman AI
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  • Rise of the auditors

    Rise of the auditors
    2026/04/25
    AI-native teams need three roles: Director, Builder, Auditor. Execution is cheap, verification is expensive. Most organisations have zero Auditors and are shipping nothing because nobody is named to check. What happened this week: * <10% of organisations scale agents beyond pilots (McKinsey) * GitHub paused Copilot signups / Uber blew 2026 AI budget / Goldman inference costs approaching headcount parity * 29% of employees sabotaging AI initiatives (Writer survey) What to try: * Ask is this the simplest version (Cantrill laziness) * Audit cold: different model, fresh context * Save one reusable AI workflow (Chrome Skills) Read the full edition with all links and sources: https://steadman.ai/newsletters/david/#edition-2026-04-25
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    12 分
  • The proxy break

    The proxy break
    2026/04/18
    AI broke the old proxy (good writing = good thinking) but the new proxy ('sounds like AI' = no thinking) is equally unreliable. A friend's challenge prompted a deeper question: evaluate thinking, not wording. Two tests proposed: Quality (does the argument hold under pressure?) and Ownership (CEO principle). Fine-tuned models now preferred over human writing 62% of the time. What happened this week: * AI cover letters killed the signal: Freelancer.com study shows Goodhart's Law in action, better letters no longer predict better hires * Snap cut 1,000 jobs (16% workforce), AI writes 65% of new code, $500M annualised savings: substitution model has arrived * Passive AI delegation erodes confidence, pushing back strengthens it: 2,000-person study. Gartner: of 5.4hr saved, only 0.6hr reduces working time What to try: * Ask what keeps people awake at night, not how AI can help: surfaces real problems with AI solutions * Let the model research you before writing custom instructions: web search + self-portrait generates better instructions than manual writing * Find where your AI value sits: AI Value Map interactive tool, five questions on value allocation then five on capture Read the full edition with all links and sources: https://steadman.ai/newsletters/david/#edition-2026-04-18
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    11 分
  • What a day can do

    What a day can do
    2026/04/11
    Team-level AI infrastructure can precede and contain individual training. The cost of encoding how a team works into shared reusable tools just dropped from hours to minutes with Gen 2 tools (Claude Code + transcripts). A small jewellery company built thirteen shared skills in a day. Step two doesn't just follow step one, it can contain it. What happened this week: * Claude Code now writes 4% of all GitHub commits, doubled in six weeks; Anthropic run rate $30B (up from $9B at end of 2025), Claude Code alone $2.5B; projected 20% of commits by December * Goldman Sachs quantified AI's net labour market drag: -25k jobs substituted + 9k augmented = 16k net monthly loss; entry-level-to-experienced wage gap widened 3.3pp. But CFO surveys put genuine AI ... * Meta's internal tokenmaxxing leaderboard: 85k+ employees, 60T tokens in one month, Zuckerberg not in top 250. Rewards orchestration over outcomes. Incentivise use yes, incentivise maxxing no What to try: * Start with critique, not creation. Brand voice evaluator was diagnosis-only; teams fear proofreaders less than replacements. Nobody fights the spellchecker * Ask what keeps people up at night, not what they want AI to do. First question surveys existing habits; second surfaces unmet needs. Almost nothing appears on both lists * Show your team how others use AI. 515-startup field experiment: case studies alone led to 44% more AI usage, 1.9x revenue, 39% less capital needed ('the mapping problem') Read the full edition with all links and sources: https://steadman.ai/newsletters/david/#edition-2026-04-11
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    11 分
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