[agentic-token-optimizer] Daily AI Poem — optimization recommendations (2026-08-14)

[github-actions]

Target Workflow

Daily AI Poem (daily-ai-poem.md) — selected as the highest-AIC eligible workflow after excluding all candidates optimized within the last 14 days (Agentic Workflow AIC Usage Optimizer, Daily Agentic Workflow AIC Usage Audit, Daily Agentic AI Research Digest, Daily XKCD Comic all excluded).

Analysis period: 2026-08-08 → 2026-08-14 · 7 runs

---

Spend Profile

Metric	Value
Runs analyzed	7
Total AIC	111.65
Avg AIC / run	15.95
Avg tokens / run	~48,990
Avg turns / run	2.0
Avg duration	4.1 min
Avg GitHub API calls / run	10
Failure rate	0% (7/7 success)
Cache efficiency	N/A — single-turn creative generation; no repeated context

The workflow is highly stable and simple: the agent generates a poem in a single turn then posts it as a GitHub Discussion. Nearly all token spend is in that one generation step.

---

Ranked Recommendations

#1 — Pin a smaller model for creative generation

Estimated savings: ~8–11 AIC/run (~50–70%)

The workflow does not specify a model. It currently runs on the default (claude-sonnet-class), which is well above what a simple creative-writing task needs. The task has no branching logic, no external data to synthesize, and no tool use beyond creating one discussion. A smaller/cheaper model (e.g., claude-haiku-4) is fully adequate for writing 3–4 stanzas of themed poetry.

Action: Add model: claude-haiku-4 (or the equivalent lightweight model) to the workflow frontmatter.

---
description: Daily poem about AI, agents, and developer life — posted as a GitHub Discussion
model: claude-haiku-4   # ← add this line
on:
  schedule:
    - cron: "daily around 08:00"
...

Evidence: All 7 runs produced quality output on the first turn with 2 total turns and zero failures. The task is extractive/formulaic (pick theme by date, apply writing rubric, emit fixed-format output) — a smaller model handles this class of task well.

---

#2 — Trim redundant quality guidance in the Instructions section

Estimated savings: ~0.5–1 AIC/run (~3–6%)

The ## Instructions section contains two overlapping directives that say essentially the same thing:

• "Have a clear voice — playful, clever, and warm"
• "Be funny or touching, not generic — a developer reading this should nod and smile"

And the trailing Output note — "A developer should be able to share this on their team Slack without embarrassment 🚀" — restates what the quality bullets above already convey.

Action: Collapse the quality bullets from 4 to 2 and remove the trailing Slack remark:

## Instructions

1. Pick today's theme using the formula above (use today's date from the environment).
2. Write a poem of **3–4 stanzas** (4 lines each). It should:
   - Have a clear, playful, and clever voice — use concrete details (tool names, concepts, emojis welcome)
   - Prefer rhythm over strict rhyme; be memorable, not generic
3. Give the poem a punchy, memorable title (3–8 words).
4. Write a one-sentence "Inspiration Note" explaining what sparked today's theme.

Evidence: The existing output quality is already high and consistent across all 7 runs; the extra guidance adds token overhead without measurably improving results.

---

#3 — Simplify Theme Selection section

Estimated savings: ~0.2–0.5 AIC/run (~1–3%)

The ## Theme Selection section first says "Rotate through these in a roughly round-robin order" and then gives an exact formula anyway. The prose preamble is redundant given the formula.

Action: Remove the prose sentence; keep only the list and formula:

## Theme Selection

Pick today's theme using `(day of month) mod 7`:

- **0**: AI agents and their curious habits
- **1**: The joy and pain of debugging
...

Evidence: A deterministic formula needs no additional framing. Removing 12–15 tokens of preamble per run is noise but contributes to cumulative prompt compression.

---

Tool Usage Audit

Tool	Observed	Recommendation
create_discussion (safeoutputs)	Every run	Keep — the only output mechanism
No other tools observed	—	No tool removal needed

All 10 GitHub API calls per run appear to be safeoutputs infrastructure overhead (discussion creation, auth, expiry checks). This is not reducible from the prompt side.

---

Structural Optimization

No inline sub-agents recommended. The workflow has only 3 sections (Theme Selection, Instructions, Output), 2 turns per run, and a single atomic task. Splitting into sub-agents would add orchestration overhead that exceeds any savings. The workflow already has a near-ideal structure for its purpose.

No setup-prefix extraction needed. There are no repeated setup calls across sections.

---

Combined Estimated Savings

Recommendation	Est. AIC saved / run	Confidence
Smaller model (#1)	8–11 AIC	High
Prompt trim (#2)	0.5–1.0 AIC	Medium
Theme section simplification (#3)	0.2–0.5 AIC	Low
Total	~8.7–12.5 AIC/run

At 7 runs/week, recommendation #1 alone would save ~60–80 AIC/week.

---

Caveats

• Token counts from run metadata are aggregates; per-section breakdown is not available.
• Model availability (claude-haiku-4) should be confirmed against the platform's supported model list before applying.
• The workflow is already extremely lean; gains beyond recommendation Add CI workflow to compile agentic workflows via gh-aw-actions #1 are marginal.
• All 7 sampled runs used the same code revision (1115d071) — no variance from code changes in this window.

Run reference table

Run	AIC	Duration	Conclusion	GitHub API Calls
§31248452121	15.86	4.0m	success	10
§31303593242	16.00	4.4m	success	10
§31371792234	15.93	3.6m	success	10
§31473855192	15.93	3.8m	success	10
§31579619342	16.01	3.8m	success	10
§31683514876	16.01	4.5m	success	10
§31784972486	15.92	4.2m	success	10

Generated by Agentic Workflow AIC Usage Optimizer · 213.9 AIC · ⊞ 21.6K · ◷

• expires on Aug 21, 2026, 2:48 PM UTC

[github-actions]

This issue is being closed as outdated. A newer issue has been created: #430

View newer issue

---

This action was performed automatically by the Agentic Workflow AIC Usage Optimizer workflow.