/AI1d ago

Tim O'Reilly and Clement Delangue argue AI systems should be built on top of existing legacy infrastructure

They advise against rebuilding operating systems and compilers from scratch.

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Tim O'Reilly@timoreilly#1612inAI

This is so true. What people fail to realize is that when new technology tools become available, they tend to be used to create new capabilities up the stack, while down the stack, archaeological layers of technology remain.

clem 馃@ClementDelangue

Token costs are why there will be no saas apocalypse / good dev tools are cached intelligence for agents!

The popular theory goes: agents can write code, so they'll just rebuild every tool from scratch and hit raw APIs. no more dev tools, no more CLIs, no more software layers. just agents and endpoints!

We just tested this and the data says the opposite. We benchmarked Claude Code and Codex on real Hugging Face Hub tasks (~1,000 graded runs), with two setups: the agent-optimized hf CLI vs the agent hand-rolling curl or SDK calls from scratch.

Hand-rolling burns up to 6x more tokens on multi-step tasks and fails more often (84% vs 94% task success).

And that's just dropping one abstraction layer. It would obviously be orders of magnitude more tokens and a dramatically higher failure rate if the agent tried to bypass HF altogether and rebuild model hosting, versioning, and distribution from scratch. Every time an agent re-derives a workflow from raw API calls, you pay for that reasoning in tokens. every single run. a good CLI compresses that entire chain into a few high-level commands the agent can't get wrong. In a world where everyone is complaining tokens are too expensive, abstraction is leverage: thousands of hours of design decisions your agent doesn't have to re-reason about at inference time.

Good tools are cached intelligence for agents!

So no, agents won't rebuild everything from scratch. they'll gravitate to the most token-efficient tools, because that's what their owners pay for. The software that survives won't just be accessible to agents, it will be accurate and cheap for them to drive.

We're seeing it happen with HF, which is becoming the platform for agents to use AI: ~49M requests in just two months, and growing fast!

https://huggingface.co/blog/hf-cli-for-agents

10:07 AM 路 Jun 7, 2026 路 26.8K Views
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Users affirm that AI agents gain real efficiency from token-efficient dev tools and cached intelligence at runtime rather than paying repeatedly for raw API calls.

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Tim O'Reilly@timoreilly

This is so true. And so obvious when you think about it. If AI were going to roll everything from scratch where does it stop? Does it write new programming languages and compilers? New operating systems? New firmware from scratch? Obviously, there are some things that you want to reinvent but mostly new technology lets you innovate further up the stack, solving problems that were either impossible or too expensive with the previous technology. It's not a new mistake. Netscape lost to Microsoft because they imagined that the web would become a new operating system. Google won because they went forward into new uncharted territory. The same is going to be true with AI

clem 馃@ClementDelangue

Token costs are why there will be no saas apocalypse / good dev tools are cached intelligence for agents!

The popular theory goes: agents can write code, so they'll just rebuild every tool from scratch and hit raw APIs. no more dev tools, no more CLIs, no more software layers. just agents and endpoints!

We just tested this and the data says the opposite. We benchmarked Claude Code and Codex on real Hugging Face Hub tasks (~1,000 graded runs), with two setups: the agent-optimized hf CLI vs the agent hand-rolling curl or SDK calls from scratch.

Hand-rolling burns up to 6x more tokens on multi-step tasks and fails more often (84% vs 94% task success).

And that's just dropping one abstraction layer. It would obviously be orders of magnitude more tokens and a dramatically higher failure rate if the agent tried to bypass HF altogether and rebuild model hosting, versioning, and distribution from scratch. Every time an agent re-derives a workflow from raw API calls, you pay for that reasoning in tokens. every single run. a good CLI compresses that entire chain into a few high-level commands the agent can't get wrong. In a world where everyone is complaining tokens are too expensive, abstraction is leverage: thousands of hours of design decisions your agent doesn't have to re-reason about at inference time.

Good tools are cached intelligence for agents!

So no, agents won't rebuild everything from scratch. they'll gravitate to the most token-efficient tools, because that's what their owners pay for. The software that survives won't just be accessible to agents, it will be accurate and cheap for them to drive.

We're seeing it happen with HF, which is becoming the platform for agents to use AI: ~49M requests in just two months, and growing fast!

https://huggingface.co/blog/hf-cli-for-agents

1dViews 3.2KLikes 13Bookmarks 5
clem 馃@ClementDelangue

@timoreilly Exactly!

Tim O'Reilly@timoreilly

This is so true. And so obvious when you think about it. If AI were going to roll everything from scratch where does it stop? Does it write new programming languages and compilers? New operating systems? New firmware from scratch? Obviously, there are some things that you want to reinvent but mostly new technology lets you innovate further up the stack, solving problems that were either impossible or too expensive with the previous technology. It's not a new mistake. Netscape lost to Microsoft because they imagined that the web would become a new operating system. Google won because they went forward into new uncharted territory. The same is going to be true with AI

23hViews 921Likes 1Bookmarks 0
WillyV3@V3_Willy

@timoreilly yeah cached intelligence at the runtime layer is the real moat. raw-API agents pay the bill every call

23hViews 4
Patrick@patrickssons

@timoreilly the archaeological layer is always the cobol nobody touches, holding everything above it

20hViews 2
Shanon Eide@mudisreo1978Sha

@timoreilly Hey there! 馃尀 Just wanted to say, you鈥檝e got a spark in you鈥攍et it light up the path ahead. 馃挅

13h
Alex Conner@alexconner79

@timoreilly This maps straight onto design tooling. Agents can generate UI endlessly, but generation was never the value, it's the structure the tool enforces: the design system, the tokens, the conventions. That's the cached intelligence that stops every output being a disconnected one-off.

23h