Nathaniel Whittemore
speaker
48,511 appearances
192 recordings
3 series
first heard Oct 2025
last heard 5d ago
Nathaniel Whittemore’s voice in public audio — every appearance, attributed to the second.
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recordings per month · last 12 monthsRecordings per month over the last 12 months — 192 in all, peaking in Jun 2026 with 31.
Appearances
It's time you add agents that feel like teammates.
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Feature 10 is perhaps one of the features that many organizations are the farthest along with, which is to build agent-native development systems, letting fleets of coding agents plan, write, test, review, and ship code while humans define intent and acceptance criteria.
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This is a lot less controversial than it would have been a year ago, but obviously there are still many organizations that are using a traditional process, despite there likely being an inevitable shift that will happen in the coming years.
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Feature 11 once again gets at the sub-theme of token efficiency, dividing the business of work into planning phases and execution phases, using higher effort models for heavy planning and then executing with cheaper and faster models.
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The good thing will be that if we've done our job with feature number four, about designing efficient token architectures, this is the type of division of labor that should naturally fall out of those systems.
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Feature number 12 feels at first glance fairly term heavy.
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It's used CLI tools to parse metadata in markdown files and traverse dependency relationships, allowing agents to be precise about input token usage.
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But really, this is a technically specific way of designing a more token efficient system.
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Basically, what Alex is arguing for is organizing a company's knowledge in a way that agents can only load the slice they need rather than the whole thing.
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It feels
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Related to the idea of progressive disclosure, which is an information architecture pattern where complexity is unpacked gradually and in sequence in order to not create too much context overhead when an agent is working.
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Now, in addition to just making agents work better, there are obviously cost dimensions of that as well.
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And why I'm glad Alex included it is that so far we've been operating at a really high level, but this is an example of where you start to get granular and
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actually do things differently, i.e., making sure that the metadata that an agent can reference to understand whether something is useful is right there at the top of knowledge files that it has access to, so that it doesn't waste context window on things it doesn't need.
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With feature number 13, we're starting to get into specific parts of the organization.
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He suggests that finance will run more continuously, moving accounting and record keeping towards continuous processes, resetting forecasts on a much tighter cadence.
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OpenAI CFO Sarah Fryer actually recently wrote about how she had done this inside OpenAI and about what a mindset shift and a technological discipline it took to make this sort of change.
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Alex also suggests that in AI native organizations, other parts of the organization, and specifically the larger agentic operating system through which it runs, will have access to those financial models so that that can be part of the logic as strategy and tactics are designed.
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