From understanding automation to building intelligent systems.
A clear path through APIs, intelligent decisions, agents, orchestration, platforms, and the operational discipline that makes modern systems dependable.
Connect. Think. Act. Operate.
Connect
Learn how applications, automations, and agents communicate with the outside world.
APIs · webhooks · structured data · authentication · events · MCPThink
Learn how intelligent systems use context, knowledge, and models to reach useful conclusions.
models · prompts · RAG · embeddings · memory · groundingAct
Learn how workflows, agents, robots, tools, and people complete real work together.
tools · agent loops · approvals · orchestration · retries · fallbackOperate
Learn what separates an impressive demo from a system that can safely run in the real world.
evals · tracing · guardrails · security · cost · observabilityBridge lessons
APIs: How systems talk
Understand the controlled doorway one system uses to request data or an action from another.
Webhooks: When systems react
Learn how one system notifies another immediately after an event.
JSON and structured data
Read the shared format that APIs, workflows, and AI tools use to exchange information.
Authentication and permissions
Separate proving identity from deciding what that identity may do.
Deterministic workflows versus AI decisions
Choose fixed logic for known paths and AI only where interpretation adds value.
Workflow, copilot, or agent?
Distinguish a fixed process, a person-facing assistant, and a bounded system that chooses actions.
Advanced foundations
Models and model selection
Choose a model by task quality, latency, cost, privacy, and reliability—not reputation alone.
Structured outputs
Turn probabilistic model responses into fields a workflow can validate and use.
Context engineering
Assemble the smallest, clearest set of instructions, evidence, examples, and tool results needed for a task.
RAG and grounding
Retrieve relevant evidence and ask the model to answer from it with visible sources.
Embeddings and vector databases
Understand semantic similarity and when vector search is actually useful.
Tool calling
Give a model a small set of described actions while software keeps execution control.
The agent loop
See how an agent observes, decides, acts, receives results, and stops.
Human in the loop
Place people at deliberate review points where uncertainty or consequence is high.
Orchestration
Coordinate workflows, agents, robots, APIs, and people across time and failure.
Evals, tracing, guardrails, and observability
Build the evidence, controls, and feedback loops required to run intelligent systems safely.