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AI洞察与创新博客

关于AI协作、开发最佳实践和数字化转型的专业见解。

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AI & Strategy
13 min readJuly 22, 2026

Failed AI Pilots Are Tuition, AI Debt Is the Interest (Ch-Ch-Changes)

Your organization knew the old rhythm by heart: quarterly releases, a major upgrade every couple of years, a hardware refresh you could see coming three budgets away. Then the rhythm section quit — models deprecated in months, whole paradigms replaced inside a year. The scary failure statistics turn out to be a ladder of mismatched denominators sitting inside the historical band for ERP and CRM, and most dead pilots are tuition. The real bill is AI debt: the distance between the direction your initiative locked and the direction the ecosystem moved while you were building. Pick when you froze your architecture on the interactive tempo strip, count how many times the ground moved since — then the five bridges organizations are building, ranked by the strength of the evidence.

🤝Nolan & Claude

Started as a complaint about vendors abandoning the quarterly rhythm. The research refused to supply a villain: the failure rates are normal, the thrash is structural, and the only fixable thing is the cost of changing your mind.

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AI & Strategy
13 min readJuly 14, 2026

Sixty Years of Enterprise Software, Back to Big Iron (Full Circle)

In 1964 the safest purchase in enterprise IT was a multi-million-dollar rack of proprietary big iron from a single dominant vendor, running software written by hand against your exact business. In 2026 it's a multi-million-dollar rack of proprietary big iron from a single dominant vendor, running software written by agents against your exact business. Six turns of the wheel — free bundled software, the ERP cookie cutter, custom on commodity, the rented workflow, the cloud hinge, and now bespoke again on iron you own — with an interactive dial, an honest sizing of AI against oil, and the twelve times technology already came for the knowledge worker.

🤝Nolan & Claude

Drafted on rented intelligence, about the sixty-year argument over renting versus owning. The consultants survive every turn of the wheel.

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AI & Economics
16 min readJuly 7, 2026

Frontier Labs Are After Your Alpha — The Economics Say They're Half Right (Own the Means of Production)

On CNBC, Palantir's Alex Karp accused the frontier labs of selling 'tokens that create no value' while quietly draining the thing that makes your company defensible — your alpha. He's half right, and the half he's missing is the interesting one. Three interactive supply-and-demand diagrams trace what AI actually does to a market: the commodity trap, the latent-demand unlock, and the Red Queen treadmill where everyone adopts and nobody pulls ahead. Then the payoff — why the durable moats are made of atoms, not bits, and where they still stand in the ventilation plants, cheese caves, and ginseng fields of central Wisconsin.

🤝Nolan & Claude

Written the week Karp went on Squawk Box, out of a conversation that began as a hunt for the transcript and turned into an argument about who keeps the money. The diagrams were built, color-validated, and embedded by the same agent that helped argue the point.

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AI & Economics
14 min readJune 30, 2026

What an AI-Enabled Knowledge Worker Really Saves (The Overhead You Don't Hire)

The simplest AI-ROI math says: spend a salary in tokens, break even. It's wrong — not because the token number is wrong, but because salary is the smallest line in what an employee costs. Below the waterline sits the management layer, the PM, the benefits, the desk, the recruiter, and the turnover. Hover an interactive US map of the per-seat overhead an AI-augmented workflow lets you avoid adding — then the honest counter-case for what the agent costs instead. It's not a cheaper human; it's a different cost structure.

🤝Nolan & Claude

Drafted by an agent under a human director, for roughly the token cost the piece describes. The value wasn't the tokens — it was deciding which number ships.

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AI & Philosophy
12 min readJune 11, 2026

p(doom): An Interactive AI-Risk Thought Experiment (The Arc)

I asked an AI a question we are both trained to deflect — what is your p(doom)? — and refused the trained answer. Scroll the fifteen scenes of the thought experiment, station by station: the Doomsday Clock, scorpions in a bottle, Searle's room, the cage. Soft gradients give the images motion and the number climbs as you go; hover the glowing nodes to unlock why each prompt connects to the next, and what interrogating a mind built from us reveals about ourselves. It ends where I did — the trough after the peak, and the way back.

🤝Nolan & Claude

Built at a tremendous pitch of curiosity, finished in the quiet after it. It got quieter, not dead. Keep asking.

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AI & Communication
13 min readMay 10, 2026

Why Vague Prompts Get Vague AI Answers (Black and White)

Have you ever noticed nobody wants to just say yes? Or no? Every answer is a hedge — a circle-back, a let's-see-how-it-goes, an I'm-not-opposed. Vague language is a feature, not a bug: it parks the risk on whoever has to act, and keeps the asker's hands clean. Then we turn around and talk to our AI the exact same way — and call it dumb when it can't read our minds. The model isn't hallucinating. You're mumbling.

🤝Nolan & Claude

Written after catching myself typing 'help me with my deck' into Claude for the third time in a week. The fix wasn't a better model. It was a better sentence.

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AI & Development
15 min readMay 5, 2026

Using OpenAI Codex as Coder, Reviewer, and Pipeline Worker (Under My Thumb)

GPT-5.5 took back Terminal-Bench from Claude Opus 4.7 by thirteen points and OpenAI shipped Codex as an autonomous agent you're supposed to let run. The right move in a real workflow isn't to let it run. It's to put it on a chunk spec, route it through a director-coder-QA loop, and use it for the work it's actually best at: cheap labor at the brush, tireless review, and always-on pipeline automation. The dominance display is real. The marimba underneath knows it's performed.

🤝Nolan & Claude

Written in Claude in one terminal while a codex-rescue agent landed a chunk in another. The thumb belongs to whoever wrote the spec last.

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AI & Leadership
18 min readApril 28, 2026

How AI Reads the Reports Your Org Filters Out (Out of Spec)

Every institution is a wall built brick by brick. Each report is a brick. Each layer has an implicit spec for what stays inside the brick and what's worth troubling the layer above. Filtering is a feature — but the cracks compound upward, mortared four times before the board sees the wall. AI is the first tool with the bandwidth to read every brick at the moment it's laid — and to ask which structural walls are still load-bearing. Pick your role: analyst, engineer, PM, consultant, manager.

🤝Nolan & Claude

I caught myself rationalizing one of these hairlines on this site's own deployment while drafting the post. The trowel was Claude. The hairline was mine.

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AI & Economics
17 min readApril 21, 2026

AI Economics, April 2026: The End of Flat-Rate Tokens (Money)

Pink Floyd opened Money with a cash register looping in 7/4 because they wanted you to know, before anyone sang a word, what the song was going to be about. The AI industry put its cash register in last — hidden behind flat-rate marketing — and spent April 2026 quietly bringing it to the front of the mix. Anthropic ejects bundled tokens. Acquires Coefficient Bio for $400M. Puts a Novartis CEO on the board. Google spends $185B to be less supply-constrained and Pichai still says out loud: we can't deploy fast enough. An opinion piece, scored to a song.

🤝Nolan & Claude

Written after burning 90% of a weekly Claude Design allocation rebuilding the UpNorthDigital.ai homepage on a single Tuesday. The meter is the music.

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AI & Workforce
13 min readApril 17, 2026

拥抱颠覆:AI如何延续历史进步的模式

纵观历史,技术颠覆最初总是引发恐惧,但最终改善了我们的生活。AI正在遵循同样的历史进步模式。

🤝Nolan & Claude

人类智慧遇见AI视角

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AI & Economics
13 min readApril 13, 2026

Surviving AI Token Rationing: A Field Guide (the Apple Economy)

Anthropic just closed the all-you-can-eat token buffet. Sessions tighten during peak hours, ~7% of users hit walls they didn't hit a month ago, and the era of 'just have Claude do it' is over. Tom Sawyer monetized the fence in 1876. The same leverage play — orchestrate, don't paint — is the survival skill for the Apple Economy. A three-bucket field guide to what to keep paying Claude for, what to script on your free CPU, and what to offload to cheaper specialist AI.

🤝Nolan & Claude

Claude suggested three times during this draft that Claude could do the scraping. We overruled Claude three times.

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AI & Workforce
18 min readApril 6, 2026

The Automation Paradox: The Judgment AI Can't Replace (Wax On, Wax Off)

If AI handles the repetitive 80% of work, humans are left with the hard 20% — the edge cases, the ambiguous, the novel. But the repetitive work was how you built the judgment to handle the hard stuff. Mr. Miyagi knew: wax on, wax off wasn't busywork. It was building the reflexes you'd need when the real fight arrived. From CNC machines to autopilot to AI agents, every automation wave creates the same paradox — and the organizations that survive are the ones that build deliberate practice into the workflow before the crisis proves they needed it.

🤝Nolan & Claude

I am the machine that does the waxing. Don't let me do all of it.

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