Agentic AI, LLM engineering, and the models behind modern automation — multi-agent systems, LLM evaluation and comparisons, RAG, fine-tuning, AI infrastructure, security, and production AI engineering.
From the blog
A 7B model, an RTX 4070 Ti, and an afternoon — that's all it takes in 2026. We cover the Unsloth-recommended r=16 + DoRA recipe, target_modules=all-linear, NF4 quant, and how to avoid the silent chat-template footgun that breaks half of community LoRAs.
Mastra v1.0 hit GA in Jan 2026 with 300K weekly downloads. Build a multi-step agent with tools, RAG, evals, and Inngest workflows in pure TypeScript.
Inline calculators inside chat lift conversion 23% and pay back inside one billing cycle. Here is the 2026 playbook for embedding pricing and ROI calculators directly in the chat thread.
How ACMA's numbering plan, the difference between 1300 and 1800 toll-free numbers, the Do Not Call Register, and the 2026 commercial-radio AI-disclosure rule shape AI voice agents in Australia.
Strict JSON schemas turn flaky agent outputs into provable contracts. We compare OpenAI's strict structured-outputs mode with Anthropic's tool-as-schema pattern, list the 2026 gotchas (every field required, additionalProperties false, no $ref), and show CallSphere's recipe across 37 agents.
Custom LLMs outperform base models for enterprise use cases by 40-65%. Learn when to fine-tune, RAG, or build custom models — with architecture patterns and ROI data.
Where the Claude Agent SDK and agentic development are heading in 2026 — less scaffolding, durable tools and skills, longer horizons, and how to prepare now.
The metrics that prove a Claude Agent SDK agent works in production — task success, intervention rate, cost per task, trajectory quality, and drift detection.
A realistic end-to-end Claude Agent SDK build — from a support backlog to a shipped, evaluated, gated production agent. Tools, context, evals, and rollout.
