Learning routes

Learn AI by connecting concepts with real decisions.

Technical guides, patterns and readings to go from explanation to verifiable implementation.

01

Practical guides

Complete tours to resolve a specific decision.

LOCAL AI

How to choose a local model

Memory, quantization, context and speed without buying blindly.

Complete guide ASSESSMENT

How to read a benchmark

Dataset, metrics, conditions and limits before comparing results.

Method DECISION

How to compare models

A common table for capacities, prices and traceability.

Comparator
02

APIs and development

Decisions that appear when taking a prototype to production.

CONTRACT

Structured Outings

Schemes, validation and recovery from invalid responses.

Integration CONTEXT

Window and recovery

What to send to the model, what to recover and what to keep outside.

Architecture OPERATION

Budget and observability

Cost per task, latency, failures and end-to-end quality.

Production
03

Agent patterns

More autonomy requires better boundaries and observability.

PLAN

Plan and execute

Separates intention, tool selection and verification.

Control MEMORY

Task status

Keep only the necessary information and define its expiration.

Context REVISION

Humans in the circuit

Stop sensitive actions before producing external effects.

Supervision
04

Research explained

Technical readings without turning an isolated result into a universal conclusion.

CONTEXT

More tokens do not always provide more signal

Attention, recovery and degradation in extensive tasks.

Assessment AGENTS

Measure processes as well as results

Traces, intermediate decisions and recovery from failures.

Evals LOCAL

Inference moves to device

Small models, multimodality and real restrictions.

Deployment