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February 2026

Building Effective Agents ↗

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Anthropic · December 2024

  • Argues the most effective agent architectures are augmented LLMs with simple tool loops, not multi-agent frameworks
  • Distinguishes “workflows” (predetermined tool orchestration) from “agents” (model-directed tool use) — both reduce to tool loops at different autonomy levels
  • Recommends starting with the simplest implementation and adding complexity only when measurably needed

Taste Is Not a Moat ↗

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sshh.io · 2026

  • Argues that taste is “alpha” (a decaying edge) not a “moat” — as AI baselines improve every few months, individual judgment only matters relative to what the tools do by default
  • Reframes the human role as “taste extractor”: articulating tacit preferences so tool loops can operationalize them, which is exactly the shell pattern of encoding intent into composable commands
  • Proposes concrete extraction techniques (A/B interviews, ghost writing, external reviews) that all reduce to the same structure — a human-in-the-loop refining outputs through iterative feedback cycles