What a small on-device model simply cannot do
A small local model has a hard ceiling, and the design question is what happens at it. Find the boundary deliberately, then build the escalation path first.
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The latency maths that decides on-device versus an API call
Comparing a local model to an API is not a race between two averages — it is tail latency, failure rates, and how often one task crosses the boundary.
adb install -r doesn't kill your app, so your screenshot is a lie
Reinstalling over a running app can leave the old composition on screen. A screenshot taken without a force-stop cannot say which build drew it.
Where your AI coding bill actually goes: I measured one long session
22 articles and 110 generated assets in one session. What the retries cost, and the one change that cut attempts per asset from roughly 1.8 to 1.1.
An agent-driven refactor, with the receipts
Before and after on a real module migration: what proved the change was inert, what the agent got wrong, and the receipt that made it safe to run at all.
Running an AI agent in CI without it spending your budget
An agent in CI cannot be asked a question. Budget caps that actually throw, local reproduction before pushing, and the gate that degraded instead of failing.
Agent memory that is just files
Most questions an agent asks about past work are exact, not semantic. What a directory tree answers well, and the one query shape it cannot answer at all.
What should an AI agent never be allowed to do?
A permissions model derived from incidents rather than imagination: three tiers, human-only bypasses, and capabilities removed from reach entirely.
The most useful thing my agent does is refuse
Refusals are only useful if they name the remedy. Four that fired during one session, what each redirected me to, and the one that fired on nothing at all.
The agent that writes the check that blocks it
When the same agent writes the fix and the gate, the gate agrees by construction. RED before GREEN is what makes a machine-written check mean anything.
An agent that installs the app and looks at the screen
The capture loop that makes an on-device claim checkable: force-stop, install, launch, capture, hash. Why the order is load-bearing and what it cannot see.
The context window is not your constraint — what you put in it is
Scoping a shared instruction bundle saved 12.6% per worker, against 40% guessed. Why residency beats capacity, and the surface that was never loaded at all.