Lightrains Blog

Engineering notes on enterprise AI, AI engineering and product engineering from the Lightrains team.

Featured

Featured engineering insights

Hand-picked articles on building AI systems for production, including experiments and case studies.

AI Engineering Enterprise AI Context Engineering: A Practical Guide Enterprise AI context engineering connects business knowledge, persistent memory, and authorized data so agents act on current information instead of guesses. Read article
AI Agents Give your agent long-term memory without blowing the context window
RAG Scaling a RAG Pipeline with Qdrant [Production Guide]
RAG From Fragmented Health Records to Unified AI Queries [Case Study]
Topic

Enterprise AI

AI strategy, adoption and governance for teams putting AI to work in the business.

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Latest Cross-Provider AI Brand Visibility Audit [Step-by-Step] Learn how to conduct a cross-provider AI brand visibility audit across ChatGPT, Claude, Gemini, and Perplexity using a persona-stratified methodology. Read article
AI Agents How to Build AI Agents for Customer Support, Sales, and Operations in 2026
Healthcare Why the C-Suite Should Own AI Assistants for Genetic Test Results
Healthcare How to Evaluate an AI Assistant for Genetic Test Results: A Practical Checklist for Genomics Teams
Explore AI Development
Topic

AI Engineering

How production AI systems are built: agents, RAG, MCP, LLM integration, evaluation and guardrails.

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Latest Harness Engineering for SMEs: Make AI Coding Agents Reliable Harness engineering turns AI coding agents from risky code generators into reliable engineering teammates for SMEs with limited teams and high stakes. Read article
AI Agents How to Build an AI Agent in 2026: Architecture, Stack, and Platform Choices
Prompt Engineering Prompt Engineering Is Not Enough. Here Is How to Build Loop Engineering Instead.
AI Agents AI Agent Budgets: How to Stop Runaway Costs Before Go-Live
Explore AI Agent Development
Topic

Product Engineering

Building and shipping web products: React, Next.js, Node.js, APIs, performance and deployment.

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Latest SaaS Launch Checklist in the AI Era A practical SaaS launch checklist for teams building products in the AI era, from scope and readiness to go-to-market basics. Read article
MVP How Startups Can Use AI and ML in an MVP
Next.js Next.js 13 vs 14 vs 16: Release Dates and Key Changes
Next.js React and Next.js Performance: A Practical Guide
Explore Product Development
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Latest

Latest articles

Enterprise AI Context Engineering: A Practical Guide Context Engineering Enterprise AI Context Engineering: A Practical Guide Enterprise AI context engineering connects business knowledge, persistent memory, and authorized data so agents act on current information instead of guesses. Read
Harness Engineering for SMEs: Make AI Coding Agents Reliable Context Engineering Harness Engineering for SMEs: Make AI Coding Agents Reliable Harness engineering turns AI coding agents from risky code generators into reliable engineering teammates for SMEs with limited teams and high stakes. Read
Why nlohmann/json Became the Default C++ JSON Library Developer Tools Why nlohmann/json Became the Default C++ JSON Library See why nlohmann/json is the C++ JSON library of choice, with before-and-after examples, real use cases, and honest trade-offs. Read
How to Build an AI Agent in 2026: Architecture, Stack, and Platform Choices AI Agents How to Build an AI Agent in 2026: Architecture, Stack, and Platform Choices A practical framework for how to build an AI agent covering architecture layers, platform choices, and production deployment considerations. Read
Give your agent long-term memory without blowing the context window AI Agents Give your agent long-term memory without blowing the context window A distilled, budget-capped store for coding agents cut an audit session from 8,150 tokens to 564 without changing the answer. Read
Prompt Engineering Is Not Enough. Here Is How to Build Loop Engineering Instead. Prompt Engineering Prompt Engineering Is Not Enough. Here Is How to Build Loop Engineering Instead. Prompt engineering gives you a single response. Loop engineering builds a self-correcting system that improves over time. Read
AI Agent Budgets: How to Stop Runaway Costs Before Go-Live AI Agents AI Agent Budgets: How to Stop Runaway Costs Before Go-Live A practical framework for setting AI agent budgets, guardrails, and termination rules that keep enterprise agent programs cost-controlled and finance-team-friendly. Read
Production AI Agent Loops: Engineering Reliable Systems AI Agents Production AI Agent Loops: Engineering Reliable Systems Production AI agent loops explained: tool calling, verification, context management, budgets, and termination rules that turn demos into reliable enterprise systems. Read
Cross-Provider AI Brand Visibility Audit [Step-by-Step] AI Strategy Cross-Provider AI Brand Visibility Audit [Step-by-Step] Learn how to conduct a cross-provider AI brand visibility audit across ChatGPT, Claude, Gemini, and Perplexity using a persona-stratified methodology. Read