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Day 10 · ~11 min●

Fourth verb: expand. The opposite of summarize — take a brief and produce more text from it. Outlines → paragraphs, bullets → prose, scaffolds → drafts.

python

outline = """
- Python is easy to learn
- It has a huge standard library
- It runs everywhere
"""
result = Agent(model).run_sync(f"Turn this outline into a 3-sentence paragraph:\n{outline}")
print(result.output)

Use expand for first drafts you'll edit. The hallucination risk is real (the model fills in plausible details that may not match the source intent), so review before shipping.

Expand — generate from a brief

Inverse of summarize. Input: a brief or outline. Output: more text.

python

result = Agent(model).run_sync(f"""
Write a 200-word product description from this brief:

- Product: time-tracker app
- Audience: freelancers
- Tone: friendly, practical
- Key features: hourly rates, invoice export, mobile app
""")

The constraints (length, audience, tone, features) anchor the model to your intent.

When to use expand

First drafts for emails, descriptions, posts — fast iteration starting point
Boilerplate with variable details — terms of service, status updates
Brainstorm seeds — "give me 5 different angles for..."
Filler with structure — outline → poetry → blog post

Risks

Hallucinated detail is much higher than in summarize/transform — the model has to invent content. It will invent confidently.
Generic-sounding output — without strong constraints, expansion can read like every other AI-written text.
Length drift — "about 200 words" gives ~150-300 in practice. Test before relying on the count.

Mitigations

Constrain heavily — every "key feature" you specify reduces invention
Provide examples of the tone you want (few-shot — day 10)
Always edit — treat expand output as 60% of a draft, not 100%

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Day 10 · ~11 min●

Fourth verb: expand. The opposite of summarize — take a brief and produce more text from it. Outlines → paragraphs, bullets → prose, scaffolds → drafts.

python

outline = """
- Python is easy to learn
- It has a huge standard library
- It runs everywhere
"""
result = Agent(model).run_sync(f"Turn this outline into a 3-sentence paragraph:\n{outline}")
print(result.output)

Use expand for first drafts you'll edit. The hallucination risk is real (the model fills in plausible details that may not match the source intent), so review before shipping.

Expand — generate from a brief

Inverse of summarize. Input: a brief or outline. Output: more text.

python

result = Agent(model).run_sync(f"""
Write a 200-word product description from this brief:

- Product: time-tracker app
- Audience: freelancers
- Tone: friendly, practical
- Key features: hourly rates, invoice export, mobile app
""")

The constraints (length, audience, tone, features) anchor the model to your intent.

When to use expand

First drafts for emails, descriptions, posts — fast iteration starting point
Boilerplate with variable details — terms of service, status updates
Brainstorm seeds — "give me 5 different angles for..."
Filler with structure — outline → poetry → blog post

Risks

Hallucinated detail is much higher than in summarize/transform — the model has to invent content. It will invent confidently.
Generic-sounding output — without strong constraints, expansion can read like every other AI-written text.
Length drift — "about 200 words" gives ~150-300 in practice. Test before relying on the count.

Mitigations

Constrain heavily — every "key feature" you specify reduces invention
Provide examples of the tone you want (few-shot — day 10)
Always edit — treat expand output as 60% of a draft, not 100%