Practical guides on building autonomous AI systems, scaling engineering teams, and technical leadership.
Step-through debugging breaks when inputs are stochastic. The replacement is trace-first and replay-based, with four affordances — timeline scrubbing, branch comparison, replay-with-perturbation, and per-step intent recovery — that look nothing like the IDE's debug toolbar.
Production agents accumulate retries, fallbacks, and repair passes that quietly mask quality regressions until eval-on-traffic drifts and the team can't trace why.
Streaming AI interfaces routinely fail screen reader and keyboard users. Here is what the accessibility audit looks like, why it matters in 2026, and the fixes that take a half-day to ship.
Most AI feature sunsets stop at the endpoint and leave the prompt, judge, regression set, and incident memory behind. Here's the asset-by-asset playbook for retiring an AI feature without the orphaned configs, ghost eval runs, and lost institutional knowledge that show up two quarters later.
Most teams pick build or buy for the AI gateway on instinct in week one, then regret it in month nine. A framework for the decision that actually matters at 18 months.
The thin abstraction in front of your LLM providers became the load-bearing control plane for every AI feature you ship. A look at why its blast radius now exceeds any provider outage, and the SRE discipline that should follow.
Enterprise AI products sit in a three-link liability chain where each layer assumes someone else read the fine print. Here is how the indemnification gap forms, why the copyright shield doesn't cover hallucinations, and what discipline closes it before the first claim.
Agent-authored PRs land with a 1.7x higher defect rate while reviewers fold to confident model prose. The structural fixes that keep senior engineers in the merge path before the incident graph bends.
BYOK looks like an auth toggle but moves your trust, cost, and operational boundaries at once. Here's the architecture work most teams underprice.
Every tool you add bends your planner's accuracy curve downward. The fix is a retirement metric — frequency × success × downstream lift — and a single owner of the catalog.
Status page green, error rate zero, customers still unhappy. A field guide to writing AI quality-regression postmortems when nothing crashed — root-cause vocabulary, severity scales, and a follow-up cadence that closes the loop.
Sales demo accounts are a business-critical, unowned eval set — and they're how model migrations quietly break six-figure prospect walkthroughs. Here's the pattern to make them a first-class release gate.