New Cohort Starts:

Donate
← Back to the skill map
AI Systems/AI & reliability

Model Integration

12 micro-topics in AI Systems, each with the evidence that proves you have it and the written reason behind every link. Before you start, it rests on 4 other domains. Downstream, it holds up 9 domains.

12 topics  ·  depth 4–8 of 16  ·  11 internal links  ·  9 in  ·  11 out

Before you start

Load-bearing links first. Each one says what in this domain rests on what outside it, and why.

Model Foundations

4 links

load-bearing

Configure a model client rests on Navigate the model landscape

You configure a specific model.

load-bearing

Tune generation parameters rests on Reason about nondeterministic output

Sampling parameters control the variation.

load-bearing

Maintain chat context rests on Explain the context window

History consumes the window.

load-bearing

Enforce spend caps in code rests on Compute token economics

A cap requires knowing what a call costs.

Production Python

3 links

load-bearing

Apply a circuit breaker to model calls rests on Apply rate limiting and backoff

A breaker is the escalation of a retry policy.

load-bearing

Choose sync or async calls rests on Write async Python

The async path requires async Python.

supporting

Configure a model client rests on Call HTTP APIs asynchronously

Provider clients are HTTP clients with a wrapper.

Prompt Engineering

1 link

load-bearing

Write system instructions rests on Write direct instructions

A system instruction is an instruction.

Validation & Pydantic

1 link

load-bearing

What you will be able to do

In prerequisite order. Each idea names the artifact that closes it, the market demand that put it on the map, and what it stands on.

Depth 4  ·  procedural  ·  unassisted  ·  M17 §17.1

Configure a model client

Authenticates and instantiates a client

Evidence
Calls a model from application code
Market anchor
Google Gemini · AI integration
Rests on
load-bearing

Navigate the model landscape · Model Foundations

You configure a specific model.

supporting

Call HTTP APIs asynchronously · Production Python

Provider clients are HTTP clients with a wrapper.

Depth 5  ·  conceptual  ·  unassisted  ·  M17 §17.1

Tune generation parameters

Adjusts temperature and sampling deliberately

Evidence
Explains a parameter change by its effect on output
Market anchor
AI integration
Rests on
load-bearing

Configure a model client

Parameters are set on a configured client.

load-bearing

Reason about nondeterministic output · Model Foundations

Sampling parameters control the variation.

Depth 5  ·  procedural  ·  scaffolded  ·  M17 §17.1

Configure safety settings

Sets model-side content controls

Evidence
Justifies each safety threshold chosen
Market anchor
AI safety
Rests on
load-bearing

Configure a model client

Safety settings are client configuration.

Depth 5  ·  conceptual  ·  unassisted  ·  M17 §17.2

Maintain chat context

Carries history across turns deliberately

Evidence
Multi-turn conversation stays coherent within budget
Market anchor
AI integration
Rests on
load-bearing

Configure a model client

Sessions carry state across calls.

load-bearing

Explain the context window · Model Foundations

History consumes the window.

Depth 5  ·  procedural  ·  scaffolded  ·  M17 §17.4

Process images and documents

Sends non-text inputs to a model

Evidence
Answers a question about an uploaded PDF
Market anchor
Multimodal AI
Rests on
load-bearing

Configure a model client

Non-text input is sent through the same client.

Depth 5  ·  conceptual  ·  scaffolded  ·  M23 §23.4

Enforce spend caps in code

Blocks calls that would exceed a budget

Evidence
A runaway loop hits the cap, not the invoice
Market anchor
AI cost management
Rests on
load-bearing

Compute token economics · Model Foundations

A cap requires knowing what a call costs.

load-bearing

Configure a model client

The cap wraps the call.

Depth 6  ·  conceptual  ·  unassisted  ·  M17 §17.2

Choose sync or async calls

Matches call style to the workload

Evidence
Converts a blocking model call to async
Market anchor
AI integration · Python
Rests on
load-bearing

Configure a model client

Both call styles use the same client.

load-bearing

Write async Python · Production Python

The async path requires async Python.

Depth 6  ·  representational  ·  unassisted  ·  M17 §17.2

Write system instructions

Sets durable behavior separate from user input

Evidence
Behavior holds across varied user messages
Market anchor
AI integration
Rests on
load-bearing

Maintain chat context

System instructions are separated from turn history.

load-bearing

Write direct instructions · Prompt Engineering

A system instruction is an instruction.

Depth 7  ·  procedural  ·  unassisted  ·  M17 §17.2

Stream model output

Consumes a token stream from the provider

Evidence
Streams a completion end to end
Market anchor
Streaming · AI integration
Rests on
load-bearing

Choose sync or async calls

Streaming is the async call style.

Depth 7  ·  procedural  ·  unassisted  ·  M17 §17.3

Get structured output

Constrains responses with a response schema

Evidence
Parses a typed object with no string cleanup
Market anchor
Structured output · Pydantic
Rests on
load-bearing

Configure a model client

Structured output is a request configuration.

load-bearing

Define schemas with Pydantic · Validation & Pydantic

The schema is a model.

Depth 8  ·  conceptual  ·  scaffolded  ·  M17 §17.3

Handle schema validation failures

Recovers when output does not match the schema

Evidence
Retries or degrades instead of crashing
Market anchor
AI engineering · reliability
Rests on
load-bearing

Get structured output

Failure handling assumes you asked for a schema.

Depth 8  ·  conceptual  ·  scaffolded  ·  M23 §23.4

Apply a circuit breaker to model calls

Stops calling a failing upstream

Evidence
Repeated upstream failure trips the breaker
Market anchor
Reliability engineering
Rests on
load-bearing

Apply rate limiting and backoff · Production Python

A breaker is the escalation of a retry policy.

supporting

Handle schema validation failures

Both are failure paths around an unreliable call.

What rests on this domain

Everything downstream that names an idea here as a prerequisite, grouped by where it lives.

Agents

1 link

load-bearing

Bound loops with budgets rests on Enforce spend caps in code

Spend caps are the same mechanism at the loop level.

Context Engineering

1 link

load-bearing

Carry structured state instead of transcripts rests on Maintain chat context

You replace history replay with state.

LLM Evals

1 link

load-bearing

Use a model as a judge rests on Get structured output

A judge returns a structured score.

Observability

2 links

load-bearing

Trace LLM applications rests on Configure a model client

You trace model calls.

supporting

Track and control AI cost rests on Enforce spend caps in code

Caps and attribution are two halves of budget control.

Prompt Engineering

1 link

load-bearing

Write direct instructions rests on Configure a model client

You need something to prompt.

Retrieval (RAG)

1 link

load-bearing

Inject retrieved context rests on Maintain chat context

Retrieved text is placed into the request.

AI Safety & Governance

1 link

load-bearing

Implement content safety filters rests on Configure safety settings

Provider settings are the first filter; yours is the second.

Tool Use & MCP

1 link

load-bearing

Declare tools for a model rests on Get structured output

Tool arguments arrive as structured output.

AI Interfaces

2 links

supporting

Manage conversation history in the UI rests on Maintain chat context

The UI mirrors how context is carried on the server.

supporting

Handle multimodal file input rests on Process images and documents

Upload UI exists to feed multimodal input.

Retool. Retrain. Relaunch.

375 ideas. 17 weeks. No tuition, ever.

Vets Who Code is a veteran-run 501(c)(3). The accelerator is free, remote, and we don’t take a share of your first paycheck.

Free · Remote · 17 weeks · EIN 86-2122804