Articles
Answers to the question you searched for, with the numbers attached.
Tip1 to 3 min
Note3 to 6 min
Deep dive8 min and up
Problem
All
agent memory
ai agents
ai engineering
at-least-once
batching
buffer pool
bullmq
bytes per row
career
cdn
claude code
claude.md
clickhouse
clickhouse codecs
code review
column ttl
compression ratio
configuration drift
connection pool
context files
cost engineering
data reconciliation
data validation
deduplication
digital signage
digitalocean
disk budget
documentation
doubledelta
durability
edge buffering
eventual consistency
fleet management
guardrails
hiring
idempotency
innodb
interviews
kafka
kafka consumer
leadership
legacy systems
librdkafka
load data
migration
mqtt
mysql
n+1 queries
node-postgres
observability
operations
part_log
performance tuning
php
php-rdkafka
postgres
precomputed snapshot
proof of play
refactoring
reliability
replacingmergetree
replication
reporting
rollout
sharding
sort key
t64
telemetry
timeouts
verification
webhooks
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Note
Catching the agent: mistakes from a real refactor
Nine days, about 110 commits, an AI agent doing most of the typing. These are the mistakes it made that reached a commit or a screen, how each one was caught, and the guardrails that came out of them.
measured ▸ a 15,000-row cap refused a 17,394-row order · validator headline 97.76%, honest number 95.82% · 263 fields left as no proof
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Note
Applying to a job through my agent
Shovels hires engineers with an application only an agent can run. It interviews you, stands down while you sketch, spends a budget on their live API and writes your reference letter. How it went from the candidate side, and what other companies could take from it.
measured ▸ 30 of 250 trial API calls, 0 errors · 3 of our own claims killed in review · answer 40 days later