Articles 61–70 of 101
A simple, repeatable method to estimate LLM API spend before launch: tokens per task, tasks per month, caching and model mix — with a worked example.
Custom machine learning model costs by type — classifiers, forecasting, vision — from $8k to $120k, with the data, accuracy and MLOps factors behind each.
What a retrieval-augmented (RAG) chatbot costs to build and run in 2026 — by tier — and the four factors that move the price: data, accuracy, access and scale.
Budget 15–25% of the build cost per year to keep an app healthy. What that money buys — hosting, updates, security, OS changes — and how to keep it down.
How WhatsApp Business API pricing works in India — message categories, the free service window, provider fees — and what an AI agent on top costs to build.
What a voice AI agent really costs per minute of call — telephony, speech-to-text, the LLM, text-to-speech — plus the build cost and when it beats a human.
Our step-by-step method for cutting LLM API spend on a production agent — measure, cache, trim inputs, tune effort, route models, batch — with typical savings.
Our process for shipping a production MCP server in two to four weeks — tool surface design, descriptions, auth, security testing, evals and handover.
Step-by-step tutorial for building an AI agent eval suite: sourcing scenarios, defining expected actions, choosing graders, wiring into CI, keeping it alive.
How we build a production voice AI agent in four weeks — call-reason analysis, streaming stack, latency budget, barge-in, escalation, shadow mode, launch.
We reply within 24 hours at hello@truecodeai.com with how we would build it.