Build Your First AI Agent: A Practical Guide to Tools, Memory, and Guardrails
Learn how to design an AI agent that plans tasks, calls tools, retains useful context, handles failures, and operates safely in a real production workflow.
LB
Tag: LLMs
RAG vs Fine-Tuning: How to Choose the Right Path for Your AI Product
Compare retrieval-augmented generation and fine-tuning across cost, accuracy, maintenance, privacy, and speed to determine which approach fits your use case.
PN
Inside LLM Reasoning: What Chain-of-Thought Can and Cannot Tell Us
Explore how language models approach complex problems, why visible reasoning may be unreliable, and which evaluation methods offer stronger evidence of capability.
LB
How to Benchmark LLMs for Your Workflow Instead of Trusting Leaderboards
Build a task-specific evaluation suite that measures accuracy, latency, cost, consistency, and safety using examples drawn from your actual business processes.
DM
From Prompt to Production: A Reliable LLM Application Architecture
See how routing, retrieval, structured outputs, observability, caching, fallbacks, and human review combine to make an LLM application dependable at scale.
AO
AI Agents at Work: Lessons From Automating a Customer Support Queue
This case study follows an agentic support system from prototype to rollout, revealing where automation saved time, where humans stayed essential, and why.
LB
Small Language Models Are Rising—Here Is Where They Beat Frontier AI
Smaller models can outperform larger rivals on cost, latency, privacy, and specialized tasks when teams optimize data, deployment, and evaluation carefully.
PN
The Hidden Cost of AI: A Field Guide to Tokens, Latency, and Scaling
Model fees are only the beginning; learn how retries, long contexts, retrieval, observability, and traffic patterns shape the true economics of an AI product.
AO
Claude vs GPT for Long Documents: A Hands-On Workflow Comparison
We compare Claude and GPT across document analysis, extraction, summarization, citations, context handling, speed, and cost using realistic knowledge-work tasks.
LB
Synthetic Data for AI: Powerful Shortcut or Expensive Dead End?
Examine when synthetic data improves coverage, privacy, and model performance—and when feedback loops, hidden bias, and weak validation make it a liability.
DM
Prompt Engineering After Agents: The Skills That Still Matter Most
As AI systems become more autonomous, clear instructions, context design, tool schemas, evaluation criteria, and failure handling remain essential disciplines.
LB
Can AI Replace Search? The New Battle for Answers, Trust, and Discovery
AI answer engines are reshaping how people find information, but citation quality, freshness, incentives, and verification will determine whether users stay.
PN