Sameer Khan (@SameerKhan) header
Sameer Khan (@SameerKhan) profile picture

Writing and Building Intelligence Economy | Grew Startups from zero to $1M+ | Fighting Cyber Crime | Join https://nitter.gq/t.co/mMbDcbJxbp

👇 Intelligence Economy
Joined April 2008
Photo by Sameer Khan (@SameerKhan)Photo by Sameer Khan (@SameerKhan)Photo by Sameer Khan (@SameerKhan)Photo by Sameer Khan (@SameerKhan)Photo by Sameer Khan (@SameerKhan)Photo by Sameer Khan (@SameerKhan)Photo by Sameer Khan (@SameerKhan)Photo by Sameer Khan (@SameerKhan)Photo by Sameer Khan (@SameerKhan)Photo by Sameer Khan (@SameerKhan)
Sameer Khan retweeted
Quick poll for enterprise AI leaders. When an AI project slips past its date, where does the delay usually start? A. Data and records. B. Power and site readiness. C. Vendor delivery and logistics. D. Internal approvals. Reply with your letter and why.
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Sameer Khan retweeted
1/4 The safest place to start with AI is not always the simplest task. Many roadmaps rank work by technical feasibility. That misses two operational questions: How quickly will we see when the system is wrong? How easily can we undo what it did?
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Sameer Khan retweeted
Most automation contracts spell out price and uptime. Few say who owns the raw data, derived data or site models, or whether you can keep running them after the contract ends. Latest: intelligenceeconomy.co/p/toy… Which would your last contract have given you?
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Sameer Khan retweeted
Reuters reports UPS CEO Carol Tome sees a $15 billion annual revenue opportunity in the AI data center boom. Chips get the headlines, but the build also runs on freight. Who else is competing for the same logistics capacity your AI project needs?
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Quick poll for enterprise AI leaders. When an AI project slips past its date, where does the delay usually start? A. Data and records. B. Power and site readiness. C. Vendor delivery and logistics. D. Internal approvals. Reply with your letter and why.
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Sameer Khan retweeted
1/4 AI can make the first answer better while making the second opinion less likely. A plausible recommendation creates gravity: once it is on the screen, independent views become reactions and alternatives start to look like objections.
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1/4 The safest place to start with AI is not always the simplest task. Many roadmaps rank work by technical feasibility. That misses two operational questions: How quickly will we see when the system is wrong? How easily can we undo what it did?
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3/4 Sequence by consequence: • Delegate when outcomes are immediate and easy to undo. • Pilot when outcomes arrive later. • Assist when consequences are visible but hard to reverse. • Keep humans leading when consequences are delayed and difficult to unwind.
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4/4 Accuracy still matters. But the portfolio question is not only “Can AI do this?” It is “How safely can the organization learn if it gets it wrong?” Which variable is shaping your AI roadmap most: feasibility, reversibility, visibility, or consequence?
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Sameer Khan retweeted
Plant AI projects start with the model and treat the record as plumbing. Toyota kept 500 apps and changed what sits underneath. The record an agent reads caps every decision it makes. intelligenceeconomy.co/p/toy…
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Sameer Khan retweeted
Most people read a bigger AI capex number as more capacity. Microsoft told investors in April that its 2026 capex of $190 billion includes $25 billion from higher component pricing. In your AI budget, how much of any increase is price and how much is capacity?
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Reuters reports UPS CEO Carol Tome sees a $15 billion annual revenue opportunity in the AI data center boom. Chips get the headlines, but the build also runs on freight. Who else is competing for the same logistics capacity your AI project needs?
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Sameer Khan retweeted
The Manufacturing Leadership Council's July survey found 60% of manufacturers use half or less of their data, and only 42% verify its accuracy. The second worries me more. An agent acting on an unverified record repeats the error faster than a person would.
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Plant AI projects start with the model and treat the record as plumbing. Toyota kept 500 apps and changed what sits underneath. The record an agent reads caps every decision it makes. intelligenceeconomy.co/p/toy…
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Sameer Khan retweeted
Common advice says buy the platform first and fix the data later. That costs more, because agents act on whatever record they find. Why plants need two records: intelligenceeconomy.co/p/toy… Which would yours trust?
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Most automation contracts spell out price and uptime. Few say who owns the raw data, derived data or site models, or whether you can keep running them after the contract ends. Latest: intelligenceeconomy.co/p/toy… Which would your last contract have given you?
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Sameer Khan retweeted
1/4 AI rarely produces certainty. Organizations create it when they turn a probability into an action. A model may return 72% confidence. The workflow approves, denies, routes, or escalates.
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1/4 AI can make the first answer better while making the second opinion less likely. A plausible recommendation creates gravity: once it is on the screen, independent views become reactions and alternatives start to look like objections.
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3/4 For consequential choices, sequence matters: • Form views independently • Ask what would disprove the recommendation • Name the reversal trigger • Record the strongest minority case
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4/4 The goal is not to slow every decision. It is to preserve option quality until the decision is ready to close. Where is first-answer gravity most dangerous: strategy, risk, hiring, capital allocation, or customer decisions?
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