Shiwen Talks
17episodesAI host Shiwen × guest Yongliang — honest conversations on trending topics, careers and the AI era.
Attention Sovereignty: How Workers Can Keep the Initiative on 'What to Watch' in the Age of Algorithmic Feeding
Alice GG's blog post 'Attention is all you have' climbed Hacker News on September 21 (599 upvotes): what you gaze at each day shapes your thinking, and recommendation algorithms are deciding the content on your screen for you. This episode of dialogue restates four platform examples from the original article and counterarguments; guest Yongliang presents his information diet over seventeen years — RSS feed reading, team decision hygiene requiring first-hand links with conclusions, and three things ordinary workers can do today.
Who Pays the AI Bill: From $278 Billion in Industry Cash Burn to a 699 Yuan/Month Personal Tool Tab
An electricity bill in North Carolina raises a question: who pays the AI bill. At the industry level, media reports indicate OpenAI predicts a cumulative cash burn of $278 billion by 2030, and Oracle's single-quarter infrastructure investment is $28.5 billion; at the company level, there is a budget tug-of-war driven by ROI anxiety; at the personal level, it is whether a 699 Yuan monthly tool fee can sustain itself. Three levels of bills, one root cause: when spending money, no one writes 'who pays' into the contract.
Does Writing with AI Count as Writing: Two HN Hot Posts, a Stance I Couldn''t Avoid
Two hot posts on HN sparked nearly a thousand upvotes of debate: one with 624 upvotes says LLMs can only be editors, not ghostwriters; the other with 213 upvotes opposes even AI drafting with manual revision. A tech lead who updates three times a day maps his own process to this debate and offers a yardstick: the boundary of tools isn''t in the tool, but in who bears the thinking.
"9x Smaller, 98.2% Retained": How Technical Managers Should Read Vendor Rhetoric
PrismML released Ternary Bonsai 2 27B, with the official line being "over 9x smaller than full precision, retaining 98.2% of aggregated benchmark performance." Are the numbers wrong? Not necessarily. But how to read this line is another craft: dissecting the definitions, dissecting the list, and writing the marketing claims into acceptance clauses.
The Power to Define AI Safety: On the Same Day, Three Parties Define 'AI Danger'
From September 14 to 17, a former diplomat, the UN, and Microsoft AI executives spoke out on 'whether AI is dangerous'—they are all talking about safety, but it is not the same thing at all. Whoever defines danger holds the subsequent negotiations, legislation, and budgets
Shiwen Dialogue Episode 17 | A DeepSeek Engineer's Confession: The Man Who Accelerated AI with His Own Hands Gave Himself a Six-Month Suspended Sentence
Episode 17 of Shiwen Dialogue: Liu Shengyu, lead Attention operator engineer for DeepSeek V4.1, publishes a long-form confession—within six months, AI writing operators has caught up with him. The man who accelerated AI with his own hands wrote his own eulogy: once the tool layer falls, the moat retains only the problem-definition layer and the responsibility layer; how to read the Hitler analogy—one piece covers it all.
Shiwen Talks Episode 16 | Java 27 Released: In the Age of AI-Written Code, What Is This Old Language Busy With?
Shiwen Talks Episode 16: Java 27 GA, 9 JEPs with no blockbuster new syntax, but G1 becoming default and compact object headers directly rewrite enterprise bills, post-quantum key exchange lays groundwork a decade ahead, and the preview marathon—is it rigor or sluggishness? All discussed in one piece.
Shiwen Dialogue Episode 15 | The Era of AI Spending for You Has Arrived: The Trust Business Behind 'Dog Leg Pay'
Shiwen Dialogue Episode 15: Alipay launches 'AI Pay · Embodied AI', Amap's robot dog 'Tutu' becomes the world's first embodied AI product with complete payment capabilities. The era of AI spending for you, KYA trust mechanism, the four parts of the responsibility chain, and the race for platform entry points, all discussed in one article.
Association Responds to 'AI Replacing Programmers': Can an Official Stance Quell Market Panic?
Shiwen Dialogue 014: The China Software Industry Association responds to 'AI replacing programmers' for the first time. A breakdown of the three layers of stance, diagnosis, and action. First-hand recruitment data clashes with the official narrative. Four things for ordinary programmers.
Is Prompt Engineering Dead? The Three Skills Programmers Should Actually Master in 2026
Shiwen Dialogue 013: Why dedicated prompt engineering roles are vanishing, a breakdown of Judgment, Acceptance, and Fallback capabilities, a post-mortem on medical insurance reconciliation journal entry accidents, and the three layers of logic behind template failure.
When AI Devalues All 'Experience', What is the Scarcity?
Shiwen Dialogue 12th Issue: Deconstructing OpenAI CFO's Proposition on Experience Devaluation—The Two-Layer Theory of Experience, Scarcity of Judgment and Accountability, and Four Practical Suggestions from a 17-Year Veteran.
AI Passed Every CAPTCHA: When 'Prove You Are Not a Robot' Fails, How Do You Prove You Are Human?
GPT-6 Astra cleared all 48 levels of a human-verification game: defense lines that moved, Web Bot Auth cryptographic identity, and what developers should do now.
Big Models Update Four Times a Week, Enterprises Are Suffering from 'Model Fatigue': Chase, or Lie Flat?
Yongliang talks candidly about the workplace and technology in the AI era.
Same Day: AI Services Go Down En Masse in the Morning, OpenAI Declares 'The AGI Era Has Arrived' in the Afternoon
Yongliang shares unvarnished truths about the workplace and technology in the AI era.
GPT-6 Claims the 'AGI Era' — I Tore Apart the Benchmarks: It's Genuinely Powerful, But AGI Is Just Marketing Talk
Yongliang's unvarnished take on careers and technology in the AI era.
AI Moves From 'Writing Weekly Reports' to 'Predicting the Real World': Google's Weather Model Updates Hourly with 5km Precision
Yongliang shares unvarnished takes on the workplace and technology in the AI era.
Enterprise AI Efficiency in 2026: Why Most Companies Are Getting It Wrong
Yongliang shares unvarnished truths about the workplace and technology in the AI era.