Keeping a Long-Running Managed Agent Alive Across Sandbox Recycling — Durable Checkpoints and Idempotent Resume
A Managed Agents sandbox can be recycled out from under you. Before 40 minutes of work resets to zero, we design a durable checkpoint that pushes progress outside the sandbox and an idempotent resume that never runs a side effect twice. With working SQLite code.
I Was Handing Gemini Obfuscated Stack Traces — Until retrace Went In Front, the Diagnoses Were Confident and Wrong
Release stack traces come out of R8 with the names flattened. Feed one to Gemini as-is and the diagnosis arrives calm, well-written, and wrong. Put retrace in front, match the mapping by versionCode, and forbid confident answers when you cannot restore. Numbers from 42 reports.
A Japanese query won't surface its English twin — when embeddings notice language before meaning
Embed a translation pair with gemini-embedding-2 and the two halves won't be nearest neighbours, because language itself inflates similarity. Here is how I measured cross-lingual recall using translation pairs as ground truth, and what happened when I subtracted the language centroid.
A Gemini stream drops halfway — restart it, or have the model continue?
Most apps silently restart a dropped stream. Here is the arithmetic behind continuing from the partial output instead, and where to put the threshold.
I stopped storing every generation log — three retention tiers and a prompt fingerprint that keeps traceability
I was storing every Gemini API request and response body for debugging. Here is how I moved to three retention tiers plus a prompt fingerprint, and kept the ability to diagnose issues without keeping the text.
I Asked Gemini to Grade My App Store Screenshots. Everything Scored 78–85.
Ask Gemini Vision to grade App Store screenshots out of 100 and good candidates and deliberately broken ones both land at 78–85. Here is how I measured the judge's discrimination power, dropped absolute scoring, and rebuilt it as debiased pairwise comparison.
The Table Was There, but the Rows and Columns Weren't — Preserving Docs Structure Before It Reaches Gemini
getBody().getText() flattens Google Docs tables into a column of loose values. Here is what that cost me on a 42-row ledger, the Apps Script extraction layer that keeps the structure, and the acceptance test that keeps it honest.
A near-miss label won't fix itself on retry — a normalization layer for closed-vocabulary classification
When responseSchema enum returns an out-of-set label, retrying tends to return the same near-miss. From a wallpaper app's 30-category batch, here is the distribution of how labels miss, plus a normalization layer built on an alias table and gemini-embedding-2 nearest-neighbor, with measured results.
When a Batch Job Sat in RUNNING for Half a Day: Field Notes on Catching Stalls Early with Per-State Dwell Budgets and Record Reconciliation
When a Gemini Batch job stalls quietly under the shadow of the 24-hour SLA, per-state dwell-time budgets and submitted-vs-completed record reconciliation let you name the stall early. Field notes with real operational numbers.
When an Optional Field Comes Back Three Ways: Null, Empty String, and Missing Key in Gemini Structured Output
Optional fields in Gemini structured output drift between null, empty string, and a missing key, and downstream code breaks in three different ways. Here is how I collapse all three into one shape using nullable in responseSchema and a post-output normalization gate, with numbers from a nightly batch.
Retiring the Poll That Waits on an Overnight Batch — An Apps Script doPost Sink for Gemini Signals
Polling a Gemini batch or long-running operation every five minutes from an Apps Script time trigger quietly stacks up UrlFetch calls and latency. Receive the webhook in doPost, treat it as an unverified signal, then confirm authoritatively and apply idempotently.
A minimal evolutionary search loop with Gemini: propose, evaluate, select — prompted by AlphaEvolve's GA
With AlphaEvolve reaching GA, I built the smallest possible evolutionary search loop on the Gemini API: generate candidates, score them with a fitness function, and select the best. Sandboxed evaluation, diversity, and budget control — from real solo-dev use.