---
myst:
  html_meta:
    description: >-
      Build a Python application from generated source with Melder: validate,
      materialize, import, bind, and resolve objects with controlled lifetimes.
---

# Validate → materialize → import → bind → meld

Prerequisites: [an eligible agent room](agent-rooms.md),
[configuration](../advanced/posture.md), and [lifetimes](../beginner/lifetimes.md).
The complete application lesson starts with source strings and ends with working
Python objects: a tokenizer, counter, reporter, and a population of independent workers.

## Each verb answers a different question

| Step | Result to inspect |
| --- | --- |
| `validate_codegen` | `accepted`, the selected frame, and any validation issues |
| `execute_codegen` | The execution payload, including `result` and error information |
| `materialize_codegen` | `materialized` and the named module's publication result |
| Import | The generated module's real classes |
| Bind and meld | Objects managed through the normal registration and lifetime rules |

Validation checks the room's policy before execution; it does not prove arbitrary
Python safe. Malformed requests and policy refusals have different result/error
contracts. Inspect the returned payload before treating a call as completed work.

## The complete application

Run Expert 36. It validates and materializes the generated modules, imports and
binds the classes, then computes a word-frequency report. The assertions check
that `record` occurs four times, that each object has the expected state, that
`unique` reuses the tokenizer, and that five `many` workers have independent totals
`[1, 2, 3, 4, 5]`.

The core function below uses the source strings defined earlier in the saved file.
Open the complete linked lesson to copy or download that setup.

## Executing and keeping are separate

Materialization gives code a module address. A subsequent bind records its version
and custody. The iteration lesson compares room memory with research history:
running code does not itself declare a new research version. Subscribe to the
room's memory system before operations when you want to observe those command records.


## The workflow in code

These are the core steps from the saved example. Use its complete linked script for all class definitions and setup.

```{literalinclude} ../downloads/04_expert/36_an_agent_builds_a_working_system.py
:language: python
:pyobject: main
:linenos:
```


## Runnable examples

- [An agent builds a working system](../examples/expert/36-an-agent-builds-a-working-system.md) — Expert 36
- [The codegen room agents writing code](../examples/expert/07-the-codegen-room-agents-writing-code.md) — Expert 07
- [The codegen loop end to end](../examples/expert/12-the-codegen-loop-end-to-end.md) — Expert 12
- [Codegen create modify iterate](../examples/expert/26-codegen-create-modify-iterate.md) — Expert 26
- [What a synthetic module actually is](../examples/expert/33-what-a-synthetic-module-actually-is.md) — Expert 33
- [Deep overrides paths through a graph](../examples/expert/10-deep-overrides-paths-through-a-graph.md) — Expert 10

[All expert examples](../examples/expert/index.md) · [Level contents](index.md) · [Full contents](../contents.md)

[Canonical page source](https://github.com/Synaptic724/melder/blob/4b364a338debcb1c010d0f6e9dcbbabb62945ba0/docs/expert/codegen.md)