1-Month Agentic AI Developer Learning Plan 🚀

A clear, do-first roadmap from foundations to agentic systems and MCP/A2A interoperability.

Why this plan

• Outcome: Ship a small, real-world agentic app that calls tools, communicates with other agents, and syncs a simple frontend.

• Cadence: 4 weeks, ~4 hours/day.

• Tooling focus: Python + TypeScript, LangChain/LangGraph/OpenAI Agents, “vibe coding” tools (Cursor, Windsurf, Claude Code), MCP/A2A, TanStack Query, Convex.

High-level timeline 🗓️

The skills pipeline (at a glance) 🧭

Week 1 — Foundations 🧱

Goal: get productive in Python and TypeScript, set up clean environments, and lock a daily routine.
What “done” looks like: you can read docs fast, write small scripts, type confidently in TS, and commit with discipline.

Targets

• Python refresh: functions, OOP, async, packaging, venv/pipenv.

• TypeScript fundamentals for front-end ergonomics.

• Dev setup: VS Code/IDE, Git/GitHub, linters, formatters.

Daily loop (2×2 hours)

• Block 1: Python drills → mini script with CLI and a simple API call.

• Block 2: TypeScript drills → transform data + render in minimal UI.

• End: 10-minute journal of errors learned.

Week 2 — Agent frameworks 🤖

Goal: build agents that call tools, persist state, and hand off tasks.
Stack: LangChain for tools, LangGraph for stateful flows, OpenAI Agents SDK for multi-agent handoffs.

Targets

• LangChain: a tool-calling agent with one external API.

• LangGraph: state container, retries, guardrails; long-running flow.

• OpenAI Agents SDK: two agents with a triage→solve handoff.

Checkpoint: one repo with a CLI entry that runs the full flow end-to-end.

Week 3 — “Vibe coding” tools ⚡

Goal: accelerate with AI coding assistants without losing control.
Tools: Cursor, Windsurf, Claude Code.

Working rules

• Use AI to draft, but you own the diff.

• Keep prompts inside the codebase as .ai-notes/ for audit.

• Prefer small, reversible edits.

By Friday, the assistant can refactor a module, extend tests, and fix type errors on request.

Week 4 — Protocols + full-stack shipping 🛰️

Goal: Make your agent communicate with tools and other agents using open protocols, then display results in a compact, reactive UI backed by a managed backend.
Focus: MCP (Model Context Protocol), Google A2A, TanStack Query, Convex.

How MCP/A2A fit together

Frontend↔Backend data model

Capstone scope

• Feature: question triage + answer draft + optional tool call.

• Interop: one A2A handoff to a specialist.

• UI: list of requests with optimistic updates and cached detail view.

• Ops: simple logging, error paths, and a “retry” button.

Daily operating rhythm ⏱️

Milestones & proof of work ✅

• W1: TS + Py kata repo with clean tooling.

• W2: agent with tool calling + state + handoff.

• W3: assistant-driven refactor with auditable diffs.

• W4: capstone app with MCP/A2A interop and a minimal UI.

Risk controls 🧯

• Freeze scope weekly. No new tools mid-week.

• Keep every run reproducible with a single script and a short README.

• Track model/input/output and tool versions in a run log.

• Add circuit-breakers and timeouts on tool calls.

Visual index of the plan 🧠

Suggested courses to pair with each week 🎯

• Week 1 foundations → AI & Machine Learning Mastery for Python foundations and ML context. ( AI Trainings )

• Week 2 agents → Generative AI & LLMs / Mastering Large Language Models for LLM mechanics; pair with Mastering Prompt Engineering. ( AI Trainings )

• Week 3 vibe coding → Generative AI for Beginners for quick wins and mindset on GenAI tooling. ( AI Trainings )

• Week 4 automation + interop → n8n Automation & AI Agents Training to practice agent flows and orchestration. ( AI Trainings )

• Stretch/advanced → Mastering Advanced AI & Prompt Engineering for complex workflows and multi-model design. ( AI Trainings )

• Catalog overview → Browse all trainings and pick depth based on gaps. ( AI Trainings )

Final checklist before you ship 🧪

• Traces show every tool call and A2A exchange.

• Latency within target; add caching where safe.

• Frontend queries are cached and invalidated predictably.

• README documents how to run, test, and extend.

You’ve got the map. Build small. Integrate early. Ship weekly.