At CES, McKinsey showed a version of the future that had nothing to do with
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directly, but everything to do with how crypto should build.
McKinsey hosted a demo at the Fountain Bleu all about “rewiring” product development: taking cycles that used to take six to nine months and compressing them into roughly two weeks using AI, digital testing, and simulated customers.
“The key to great product is fast iteration. Try this. Did it work? Okay, it’s okay, but these three things are still a problem.” – Dave Fedewa, Partner at McKinsey told 99Bitcoins
Here’s what to know:
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What McKinsey showcased at CES is an AI workflow that is putting other crypto supply chain companies like VeChain to shame.
McKinsey AI is pulling in over 100,000 unprompted comments from TikTok, reviews, and other social media dialogue, then clustering them into attributes that engineers can act on.
“We can ingest 100,000 comments in a couple hours on a specific space, way better than a survey,” Fedewa told us.
A lot of people will lose their jobs soon
McKinsey’s CEO says he now counts AI agents as “people” the firm “employs.”
The firm currently has 40,000 humans and 20,000 agents, with a stated goal of reaching parity within 18 months. pic.twitter.com/Q8fMrtgf0X
— Dr Singularity (@Dr_Singularity) January 13, 2026
Visual concepts are built in about an hour, then tested with large samples and AI “personas” like a suburban mom with three kids or a 45-year-old football dad.
Imagine persona agents for a Bitcoin maxi, a DeFi yield chaser, and a mobile-only retail user, all stress-testing your product copy, flows, and token design before mainnet.
The old model was simple: build, build, build, then test and pray. The new model is tiny build, relentless testing, rapid iteration. Consumer brands are now getting statistically significant reads from thousands of people in days, not from 20 people behind a one-way mirror.
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One of the more honest parts of the conversation was the swipe at generic AI answers:
“You could plug all these questions into ChatGPT… The answers that would come out would not be good,” Fedewa said.
The McKinsey team believes good answers require good training, and good training requires experience and proprietary data. They’ve been doing this the hard way for 20 years, building a library of product cases and outcomes, then tuning AI on top.
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If CPG giants can take six- to nine‑month product cycles and crush them into a couple of weeks using AI, agentic personas, and digital twins, crypto teams building wallets, exchanges, and DeFi rails don’t get to blame “market conditions” for moving slowly.
There is a blueprint on the table. The only real question is which builders in this space are going to use it first.
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Key Takeaways
- At CES, we watched a version of the future that had nothing to do with Bitcoin directly, but everything to do with how crypto should build.
- The McKinsey team believes good answers require good training, and good training requires experience and proprietary data
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