Thirty days. From cosine on stub vectors to a versioned, observable, guarded agent that grounds answers in retrieved context, redacts PII, gates risky actions on human approval, recovers from tool failures, and persists its trace. Same six prompts you saw on day 1 — rate yourself again.
What's next?
The v1 arc is complete. You now have all three primitive layers — Python (language), Composio (acting on the world), AI (LLMs + RAG + guardrails). Compose them onto any task you bring.
From here the platform's role shifts: not new concepts, but recipes and projects — "how to apply this kit to a specific real-world goal." That's a separate content tier.
Beyond v1?
Vector databases, fine-tuning, multi-modal (vision + audio), multi-agent orchestration frameworks, streaming UI. All extensions of the kit you have now. Your move is to build something — pick a real task and reach for the primitives.
24 small AI-mastery scripts across four weeks plus the two synthesis lessons. Your kit:
| Capability | Lessons |
|---|---|
| Embeddings & RAG | L1 (cosine), L2 (API shape), L3 (chunking), L4 (storing), L5 (semantic search), L6 (RAG) |
| Quality & evaluation | L8 (citations), L9 (failure modes), L10 (eval at scale) |
| Cost & latency | L11 (model routing), L12 (caching), L13 (parallel calls) |
| Production guardrails | L15 (PII), L16 (rate-limit retry), L17 (fallback chains) |
| Approval & recovery | L18 (HITL), L19 (multi-step recovery) |
| Synthesis | L20 (RAG + cache + PII + tool + eval) |
| Observability | L22 (versioning), L23 (A/B), L24 (cost), L25 (guardrail compose), L26 (trace), L27 (final integration) |
Any AI-using script you'll read or write from here is a composition of these.
Python Foundations → Python Patterns → Python Mastery
↓ ↓ ↓
Automation Foundations / Patterns / Mastery
↓ ↓ ↓
AI Foundations / Patterns / Mastery ← you are here
Nine tracks. Three primitive layers. The composition skill — reach for the right primitive when shaping data, reading/writing the world, or reasoning — is what the curriculum has been building toward.
Deferred to v2:
None of these are required for the first dozen useful AI scripts you'll ship. You have enough.
→ Build something. The kit you have can: ground answers in your data (RAG), classify or extract structured info from messy text (week 2 of AI Foundations + caching from here), detect and redact PII before sending to a model, route between cheap and strong models, run a multi-step agent with recovery, persist an audit trail. Pick a task and reach.
→ Combine with Automation tracks if the task needs to read/write the world. The composition pattern is what week 3 synthesis demonstrated.
Rate the prompts below as honestly as you did on day 1.
Thirty days. From cosine on stub vectors to a versioned, observable, guarded agent that grounds answers in retrieved context, redacts PII, gates risky actions on human approval, recovers from tool failures, and persists its trace. Same six prompts you saw on day 1 — rate yourself again.
What's next?
The v1 arc is complete. You now have all three primitive layers — Python (language), Composio (acting on the world), AI (LLMs + RAG + guardrails). Compose them onto any task you bring.
From here the platform's role shifts: not new concepts, but recipes and projects — "how to apply this kit to a specific real-world goal." That's a separate content tier.
Beyond v1?
Vector databases, fine-tuning, multi-modal (vision + audio), multi-agent orchestration frameworks, streaming UI. All extensions of the kit you have now. Your move is to build something — pick a real task and reach for the primitives.
24 small AI-mastery scripts across four weeks plus the two synthesis lessons. Your kit:
| Capability | Lessons |
|---|---|
| Embeddings & RAG | L1 (cosine), L2 (API shape), L3 (chunking), L4 (storing), L5 (semantic search), L6 (RAG) |
| Quality & evaluation | L8 (citations), L9 (failure modes), L10 (eval at scale) |
| Cost & latency | L11 (model routing), L12 (caching), L13 (parallel calls) |
| Production guardrails | L15 (PII), L16 (rate-limit retry), L17 (fallback chains) |
| Approval & recovery | L18 (HITL), L19 (multi-step recovery) |
| Synthesis | L20 (RAG + cache + PII + tool + eval) |
| Observability | L22 (versioning), L23 (A/B), L24 (cost), L25 (guardrail compose), L26 (trace), L27 (final integration) |
Any AI-using script you'll read or write from here is a composition of these.
Python Foundations → Python Patterns → Python Mastery
↓ ↓ ↓
Automation Foundations / Patterns / Mastery
↓ ↓ ↓
AI Foundations / Patterns / Mastery ← you are here
Nine tracks. Three primitive layers. The composition skill — reach for the right primitive when shaping data, reading/writing the world, or reasoning — is what the curriculum has been building toward.
Deferred to v2:
None of these are required for the first dozen useful AI scripts you'll ship. You have enough.
→ Build something. The kit you have can: ground answers in your data (RAG), classify or extract structured info from messy text (week 2 of AI Foundations + caching from here), detect and redact PII before sending to a model, route between cheap and strong models, run a multi-step agent with recovery, persist an audit trail. Pick a task and reach.
→ Combine with Automation tracks if the task needs to read/write the world. The composition pattern is what week 3 synthesis demonstrated.
Rate the prompts below as honestly as you did on day 1.
Create a free account to get started. Paid plans unlock all tracks.