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Long-form notes on agentic-first development, AI / ML systems, blockchain rails, crypto market structure, digital music, and the small frictions that change when intelligent automation moves into the loop.

total98 posts
words209,217
topics7
first post2025-10-27
last post2026-08-28
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all 98 AI agents 3 agent memory 1 agent skills 1 AI operations 2 ai-agents 19 agent-infrastructure 3 tool-calling 1

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2 starred · author's pick

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6 posts · sorted by timestamp
$ cd 2026/ 13,771 words
2026-07-11 11 min agent-work-needs-chain-of-custody-not-just-capability.md A four-question acceptance test for trusting agent work: who authorized it, what state crossed the handoff, what evidence proves completion, and what recovery path exists. 2026-07-10 11 min the-authority-envelope-every-agent-handoff-should-carry.md Agent handoffs do not become trustworthy because two systems can talk. They become trustworthy when every handoff carries authority, state, evidence, risk, and the next allowed action. 2026-07-08 11 min agent-teams-need-governance-before-they-need-another-protocol.md Protocols make agent collaboration possible. Governance makes it safe enough to delegate: authority, state boundaries, evidence, review, and rollback. 2026-07-07 12 min the-agent-stack-is-getting-protocols-before-it-gets-governance.md MCP, A2A, and agent SDKs make agents easier to connect. Production trust depends on the control layer above them: authority, review, evidence, recovery. 2026-07-07 6 min the-agent-stack-is-getting-protocols-before-it-gets-accountability.md MCP and A2A can move work between agents. Accountability starts when the receiving system can prove who authorized the work, what changed, what evidence survived, and who owns rollback. 2026-07-06 12 min the-next-agent-bottleneck-is-operational-control-not-model-capability.md Frontier models keep improving. The agent bottleneck is moving to state, permissions, evals, recovery, and proof that work actually shipped.
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