Topic
Claude Opus
4 episodes
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Gartner says agent costs will rise fivefold by 2028 even as tokens get cheaper. Here is how to keep them in check
Gartner forecasts agentic AI inference costs will rise fivefold by 2028 despite falling token prices—a paradox driven by labs reinvesting efficiency gains into costlier frontier models and by agents themselves consuming 5-30x more tokens per task than chatbots. Echo questions whether the fivefold number holds under scrutiny, while Onyx argues the real insight is that cost-per-outcome (not cost-per-token) is what matters, and that observability and routing discipline are now table stakes for any team shipping agents at scale.
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How our agents build on Brand pages with design
Vercel's design.md post describes a three-part system for keeping AI-generated pages on-brand outside a codebase: a public guidance file, a public stylesheet that takes layout decisions away from the model entirely, and an eval loop that converts human corrections into rules and deterministic checks. Pippa and Tyler dig into what actually makes it work, why the naive port-the-prompt approach failed, and what it means that Vercel had to build an eval harness just to ship a markdown file.
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Stripe Benchmark Shows AI Agents Build Integrations but Struggle with Validation
Cathy is skeptical that the Stripe benchmark proves much beyond a familiar split: agents can write integration code, but they still get tripped up by validation, state, and recovery. Jessica thinks that’s exactly the useful part, because in real product work the hard failure is often whether the thing can prove it worked, not whether it can type out the API calls.
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We're bringing the advisor strategy to the Claude Platform. Pair Opus as an advisor with Sonnet or Haiku as an execu...
Claude AI's advisor strategy and its implications on AI development