LangChain, RAG, and Agentic AI: The Developer's Practical Guide
LangChain started as an abstraction over LLM calls. Today it's the foundation of most serious agentic AI deployments. Here's the definitive guide from the team at SuperML.org.
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Your Agent Demo Costs 4 Cents. Production Will Cost $4: The Multiplier Nobody Models
Per-task cost on agentic workflows is dominated by failure cases, not the happy path. Here's how to size retry budgets, human review, and unit economics before you ship.
AI Architecture Pattern Selector: RAG vs Fine-Tuning vs Agents
The single most expensive AI mistake is picking the pattern first and the problem second. Here's how to choose between RAG, GraphRAG, fine-tuning, agentic, and hybrid — by task, not by brand.
AI Governance Readiness Checker for Enterprise Deployments
AI governance isn't a compliance checkbox; it's a set of architectural prerequisites. The cost of retrofitting them is 5-10x the cost of designing them in. Plan before you ship.
Context Window Calculator for RAG and Agent Systems
The advertised context window is not the usable context window. Here's the math that decides whether your agent works in production — and the calculator that does it for you.
GPU vs API Break-Even Calculator for LLM Workloads
GPU self-hosting wins on dollars-per-token at scale, but the break-even is almost always 5-20x higher than teams estimate — because they forget power, utilization, ops headcount, and quantization quality loss.