Loading...
Hands-on projects and practical tutorials for building real-world AI applications. Step-by-step guides from concept to production deployment.
40 posts in total
Which Python dependency manager should you use for production agent services in 2026? The install speed, lockfile story, and Docker build times compared.
How to build retry logic that handles rate limits, timeouts, and transient failures without burning money. The backoff rules and the 3 errors you must not retry.
How to debug a live agent incident using Langfuse traces. The search patterns, the 5-minute workflow, and the post-mortem that catches the root cause.
How to use Langfuse trace data to find where your agent burns tokens. The 4 queries, the cost-per-user view, and the 50 percent savings patterns.
How to combine Langfuse traces with Grafana dashboards for agent monitoring. The integration, the panels, and the alerting that catches real problems.
How Prometheus metrics surface performance bottlenecks in agentic AI. The 3 queries, the alert rules, and the dashboard that finds hot loops fast.
How to stress test an agentic AI service before it ships. Concurrency, tokens, latency budgets, and the load profile that simulates real traffic.
How to run your entire agent stack locally with Docker Compose. Postgres, Redis, the agent service, Langfuse, and the network rules that just work.
How to inject API keys and secrets into agent containers without baking them into the image. BuildKit secrets, runtime injection, and the 3 bad patterns.
How to fix the 5 common Docker build errors in AI service Dockerfiles. apt-get failures, wheel builds, layer cache misses, and the silent bugs.
How to configure CORS for a production agentic API without wildcard origins. The allowlist, the credentials flag, and the preflight that breaks SSE.
Why FastAPI lifespan is the only right place for agent startup code. Per-worker initialization, ordered teardown, and the bugs it kills.