Practical notes for building fast, safe, cost-controlled AI products.
Writing about multi-model APIs, RAG, agent tools, sandboxing, billing, and operating AI platforms for startups and product teams.
VeloxAI: the multi-model control plane for product teams
Why product teams need one API for models, agents, RAG, billing, analytics, and readiness instead of another thin provider proxy.
- Models· 12 min read
How to choose the right AI model for every product workflow
A battle-tested model selection framework covering cost, latency, context window, tool calling, vision, and reasoning — with real numbers and a decision matrix.
VeloxAI Engineering - Knowledge Base· 13 min read
Building a production RAG system that doesn't lie to users
A production-grade RAG pipeline needs ingestion state, chunk metadata, vector isolation, citations, queue-based indexing, and honest failure modes.
Nguyen Son Everestt - Agent Security· 11 min read
Agent tools are powerful. That's exactly why they need sandboxes.
Useful agents call tools. Safe agents validate tool schemas, isolate execution, cap runtime, block network egress, and log every call.
VeloxAI Engineering - Operations· 10 min read
The AI billing pipeline: from token to invoice
Production AI billing needs usage events, idempotent payments, credit accounting, per-model cost breakdowns, and proactive balance alerts.
VeloxAI Engineering - Engineering· 11 min read
Building a production streaming chat UI: SSE, cancellation, and error recovery
A complete guide to Server-Sent Events for AI chat — buffer management, AbortController, reconnection, and the [DONE] contract.
Nguyen Son Everestt - Reliability· 8 min read
Honest readiness: why 'coming soon' builds more trust than 'fake active'
AI platforms depend on many services. Showing configured/unconfigured/degraded honestly prevents incidents, builds trust, and helps operators sleep.
VeloxAI Engineering - Security· 12 min read
API key security: design the lifecycle, not just the format
Secure API key management with SHA-256 hashing, one-time reveal, safe rotation, audit trails, and the principle of least privilege.
Nguyen Son Everestt - Cost· 14 min read
The AI cost optimization playbook: 7 tactics that actually work
Practical cost reduction: tiered routing, prompt caching, output constraints, batch processing, usage alerts, and cache-aware architecture.
VeloxAI Engineering - Quality· 13 min read
How to test AI products: evaluations, golden datasets, and release gates
Production AI testing needs workflow-specific evals, regression detection, human review loops, automated judges, and gated rollouts.
Nguyen Son Everestt
