Field-tested guides on shipping production AI — Gemma 4 fine-tuning, Claude Code workflows, RAG architecture, autonomous agents and rapid MVP delivery.
A practical engineer's guide to fine-tuning Gemma 4 with LoRA and PEFT for domain-specific reasoning — covering data curation, evaluation harnesses, and shipping fine-tuned adapters to production without losing general capability.
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How we deploy Claude Code as an autonomous coding agent at enterprise scale — sandboxing, tool-use protocols, observability, cost control, and the guardrails that keep AI agents reliable in real codebases.
Vector search alone won't deliver enterprise-grade RAG. We break down hybrid BM25 + dense retrieval, cross-encoder re-ranking, and structured grounding patterns that make LLM answers accurate and auditable.
The exact 4-week playbook UltraMVP uses to take an AI product from blueprint to production — discovery, model selection, evaluation, hardening and launch — with templates, KPIs, and the trade-offs we accept along the way.
Most autonomous agent demos collapse in production. Here's how we engineer custom AI agents with planner-executor loops, long-term memory and tool orchestration that survive real-world traffic, edge cases, and audits.
From manual triage to zero-touch ops — patterns for building event-driven AI workflow automation with human-in-the-loop checkpoints, idempotent retries, and end-to-end observability across your stack.