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A ¥67 OpenCode Go trial exposed the gap between low API prices and affordable coding subscriptions. Our iKanban task comparison, the limits of API-value ratios, and why more tokens do not automatically become our own ability.
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Borrowing the L1–L5 scale from self-driving cars, we ignore implementation details and look only at outcomes and the division of labor between humans and AI. The result is five levels, AL1 to AL5: code completion, conversational Q&A, a collaborator that explores on its own, a leader that proposes solutions beyond expert level, and a fully autonomous system with no human involved.- Published on
Why can the same GPT model stop midway, slow down, or struggle to finish a task in a different environment? Drawing on our experience with OpenCode and Codex, we examine how the harness affects availability and task performance, and how to choose a better fit.- Published on
Long-running AI agents can produce more code and research than we can absorb. That output extends our capacity, but it does not automatically become our knowledge, judgment, or ability.- Published on
A practical fuzzy-finding workflow that turns shell history, editor search, and browser history into layered indexes for quickly recovering commands, project context, and web resources.