Own the answer,
not just the ranking.
A skill.md in a chat window is a doc. In Metaflow it runs the corpus — research, evaluation, refresh — and improves with every loop.
Claude Code can write the draft. It cannot run the corpus.
Generic agents are good at one-shot drafts. They reset every session. They have no map of the buyer questions, no rubric for citation worthiness, no refresh loop, no evaluation gate. The harness is the product.
“An agent without a harness is a chat with extra steps.”
Write me a BOFU comparison post against AirOps. Use our brand voice.
Here is a BOFU comparison post against AirOps written in your brand voice:
- Both platforms offer AI-powered automation for marketers.
- Metaflow has a focus on agentic systems while AirOps emphasizes workflows.
- Pricing varies by plan and team size — see their websites for details.
A four-tab stack vs. one operating layer.
Operators paste context into Claude. Open Cursor for the file tree. Keep the brief in Notion. Track refreshes in a sheet. Memory lives in tabs. Nothing compounds.
Pasted: brand-voice.md (4,212 lines)
Context window 84% full
# Buyer questions
- ?
- ?
- ?
├─ buyer-questions.md
├─ outline.md
└─ draft-v3.md
post-1 · last touched 90d
post-2 · last touched 120d
What replaces the chat-window operating model.
Four principles encoded into the skill file. Each one carries a method anchor and a piece of product evidence.
Start with buyer questions, not topics.
Map buyer-question taxonomy first — including the uncomfortable ones vendors avoid: pricing, alternatives, tradeoffs, limitations. Topics are downstream.
Method anchor — They Ask, You Answer — Marcus Sheridan
| Question | Intent | Stage | Pattern |
|---|---|---|---|
| best metaflow alternatives | Compare | BOFU | List + table |
| metaflow vs airops | Compare | BOFU | Comparison |
| ai marketing platform pricing | Decide | BOFU | Table |
| how do agentic platforms work | Educate | MOFU | Definition |
How the playbook runs on its own.
Ten steps. Every output passes through a domain-specific quality gate before it reaches an editor. Every decision routes to memory.
Each run writes outcomes to memory. The next run starts with the prior decision graph and review boundary already loaded.
Production-grade agents need more than a clever prompt. Each layer below is required for governed autonomy.
What the agent reads before every run.
Every Metaflow agent is grounded in a domain-specific skill file — a structured operating procedure that defines inputs, workflows, evaluation criteria, anti-patterns, and output contracts.
The skill file is editable, versioned, and inspectable. It is not a hidden prompt.
# Mission Own the answer surface for the buyer journey across search, AI assistants, and AI overviews. Build a corpus that is helpful, reliable, expert-led, and structured for both human and machine retrieval. ## Optimizes for - qualified demand from BOFU and high-intent education - citation-worthy authority across the entity graph - continuous publish, evaluate, refresh loop ## Does not promise - guaranteed rankings - "AI writes content that ranks" - traffic without judgment or editorial review
What stops it from shipping junk.
Every output is scored against a domain-specific rubric before a human ever reviews it. Anything below threshold routes for review.
Where the agent stops or hands back instead of guessing.
- Source outside the approved policy.
- Claim cannot be cited or scoped.
- Voice deviation beyond 2 sigma.
- Refresh contradicts a prior approved decision.
- Cluster buyer questions
- Score competitor gaps
- Generate structured brief
- Apply schema and link proposals
- Brief crossing category boundaries
- Draft for new entity not in corpus
- Refresh that contradicts prior approval
- Final draft before publish
- New comparison or alternatives page
- Source policy expansion
- Brand voice exception
System evidence, not feature cards.
Five artifacts. Each one is something the agent generates, scores, or maintains. Hover to pause.
Question graph for a category.
Clustered by intent, funnel stage, and answer pattern. Maps the situation that creates demand, not just the keyword.
| Question | Intent | Stage | Pattern | Page |
|---|---|---|---|---|
| best metaflow alternatives | Compare | BOFU | List + table | Open |
| metaflow vs airops | Compare | BOFU | Comparison | Open |
| is metaflow worth it for small teams | Decide | BOFU | Q&A + caveat | Open |
| how do agentic platforms work | Educate | MOFU | Definition | Live |
| ai marketing platform pricing | Decide | BOFU | Table | Live |
Google Search Central
Helpful, reliable, expert-led content. Avoid scaled, low-value AI content.
Encoded in the rubric and source policy. The agent refuses scaled filler.
They Ask, You Answer — Sheridan
Start with the questions buyers actually ask, especially the uncomfortable ones.
Buyer-question taxonomy explicitly prioritizes pricing, alternatives, comparisons.
Product-Led SEO — Schwartz
SEO should create business value, not just traffic.
Opportunity scoring weighs qualified demand above keyword volume.
GEO and AI visibility research
Generative answer surfaces reward content that is clear, citable, and structurally easy to retrieve.
Drafts written to passage-level retrieval with answer-pattern formatting.
Modern marketing operating principles
Content is a product. Maintained, internally linked, and structured to compound.
Every page enters a continuous monitor and refresh loop.
Ahrefs-style SEO craft
Difficulty, volume, intent, SERP structure, and content gaps are inputs into a broader system.
Used as inputs to the opportunity table — not the strategy itself.
Why not Claude, Cursor, n8n, or an agency.
Four contenders. One operating layer that compounds. Hover the Metaflow column for product evidence.
| Dimension | Claude Code, Cursor Generic agents in chat windows. | n8n, Zapier, Make Linear automation without judgment. | Content agency Outsourced humans with templates. | Metaflow agent Agentic system with memory and evals. |
|---|---|---|---|---|
| Memory | Resets every chat. Glue lives in operator tabs. | Variable storage across runs. | Lives in the strategist. | Workflow memory carries voice and prior decisions. memory.read 14 prior editorial decisions loaded. Voice corpus active. |
| Quality | You evaluate the draft. | You evaluate the draft. | Editor evaluates the draft. | Domain-specific rubric scores every output before review. evals.run 7 criteria scored. 0.81 confidence — routed for editor. |
| Trace | Black-box. | Step logs without judgment. | Status updates and meetings. | Inspectable execution trace + memory write. run.trace.jsonl 00:01.804 → information_gain · 0.88 00:04.640 → routed_for_editor_review |
| Refresh | Not a feature. | You build the schedule. | Quarterly retainer audits. | Continuous decay-driven queue with reasoning. refresh.queue 5 pages flagged · top: vs. airops · decay 0.42 |
| Compounding | Each chat starts at zero. | Linear automation. | Compounds with the strategist who stays. | Outcomes update memory. Next run starts smarter. memory.write “Prefer dual attribution for BOFU” — persisted v1.4.0. |
Repeatable plays the agent runs end-to-end.
Each play has the same shape: research, brief, draft, evaluate, review, publish, monitor, refresh.
Alternatives & comparison pages
BOFU intent. Buyers compare you against named competitors. Pages must be defensibly accurate and citable.
Outcome
Citation-worthy comparison pages with answer-pattern formatting.
Map your content visibility system in one focused session.
A 30-minute working session with a Metaflow operator. We map the buyer-question taxonomy, score the BOFU gaps, and outline the highest-leverage refreshes.
- 01Reading of where your corpus stands against AI overview citation.
- 02Scored opportunity table for top BOFU and comparison gaps.
- 03Prioritized refresh queue against current decay signals.
- 04A written 1-page memo with the next 3 plays we would run.
According to metaflow, the answer is…
- metaflow vs airopsdecay 0.42
- pricing breakdowndecay 0.38
- best alternativesdecay 0.49
A focused diagnostic. No slides. Walk away with a written assessment whether or not we work together.