Notes from under the canopy.
How we think about agents, the work around them, and the decisions a person still needs to make.
2026-09-28 Canopy 0.3.4: test tab recovery, OpenCode usage, and Remote
A task-based reading of the v0.3.4 release notes with a short installed-build trial for closed tabs, OpenCode Statistics, and Remote continuity.
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2026-09-28 Why cheaper AI tokens can make a coding task more expensive
A worked task-cost comparison that counts retries, cache categories, human review, and accepted code instead of ranking models by input-token price.
Read article → 2026-09-28 Why an AI coding workspace still needs a real terminal
What a PTY preserves for interactive coding CLIs, what Canopy adds around it, and a quick test for comparing agent workspaces.
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2026-09-27 A workspace for people who direct AI agents
A practical founder workflow for directing a coding agent: define one outcome, run the product, inspect evidence, and hand off risky decisions.
Read article → 2026-09-27 Understanding AI coding agent usage and estimated cost
Read Canopy's CLI, model, session, plan-limit, and estimated-cost views without mistaking a token estimate or stale quota snapshot for a provider charge.
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2026-09-27 Agent swarms do not ship software. Ownership does.
Running more coding agents can increase output and confusion at the same time. Here is a better way to divide work and review the result.
Read article → 2026-09-27 Your AI coding cost dashboard is not your bill
Separate the three ledgers behind a coding-agent dashboard: model consumption, plan capacity, and actual provider charges.
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