W49–W50: Publishing Strategy (MetalHatsCats content engine)

W49–W50: Publishing Strategy (MetalHatsCats content engine)

What you’re doing

You stop “finishing projects and hiding them”.

If nobody sees your work:

• it doesn’t help your career
• it doesn’t attract opportunities
• it doesn’t build reputation

So you build a small publishing engine:

• repeatable
• low effort
• consistent
• tied to your real work (not generic blog spam)

Time: 4–6 hours/week
Output: a publishing system + 10 content ideas + 3 published pieces + a simple cadence you can maintain

The promise (what you’ll have by the end)

By the end of W50 you will have:

• A clear content pillar structure (what you publish about)
• A repeatable post template (so writing is fast)
• A “content backlog” of 10 real topics
• 3 published pieces linked to your projects
• A simple distribution checklist (so posts actually get seen)

The rule: publish proof, not opinions

Nobody cares about “AI will change the world”.
People care about:

• what you built
• how it works
• what problem it solves
• what you learned

So every post must connect to:

• a repo
• a demo
• a metric
• a case study artifact

Content pillars (keep it focused)

Choose 3 pillars max:

1. **AI for SAP Operations (AMS)**

• ticket triage, routing, recurring issues, eval

1. **Data Quality & Integrations**

• extraction, mapping, DQ rules, overwrite protection, monitoring

1. **Knowledge Systems (RAG)**

• runbooks, governance, retrieval quality, safe answers

Everything you publish should fit one of these.

Post template (fast and useful)

Use this structure:

• The pain (1 paragraph)
• The approach (bullets)
• The artifact (link to repo/demo)
• The result (numbers or benchmark)
• The lesson (1–3 bullets)
• Next step (what you’ll improve)

Short. Dense. Practical.

What to publish (minimum)

Publish 3 pieces:

Post 1 — AI Ticket Analyzer: routing that doesn’t hallucinate

Include:

• strict JSON output
• needs_human fallback
• eval numbers on golden set

Post 2 — SAP pipeline: DQ gate + mapping layer

Include:

• rule_id taxonomy
• mapping as single source of truth
• report example

Post 3 — KB/RAG: retrieval benchmark + governance

Include:

• top-5 hit rate
• “cite or refuse” policy
• ingestion pipeline

These three make you look like a serious engineer, not a hype guy.

Distribution checklist (simple but consistent)

For each post:

• publish on your site (MetalHatsCats)
• share on LinkedIn (or equivalent)
• add to GitHub README “Featured”
• optionally share to one niche community (optional)

Do not spam 10 places. Just be consistent.

Deliverables (you must ship these)

Deliverable A — Publishing system

• content pillars defined
• post template created
• backlog list exists

Deliverable B — 3 published posts

• published on your site
• each links to a repo/demo

Deliverable C — 10-topic backlog

• real topics from your work
• each mapped to a pillar

Deliverable D — Distribution checklist

• a short checklist you follow every time

Common traps (don’t do this)

No. Short proof posts win.

• Trap 1: “I need to write long articles.”

Perfect means never. Publish when it’s real and reproducible.

• Trap 2: “I’ll publish when it’s perfect.”

Generic content is noise. Publish artifacts and metrics.

• Trap 3: “Generic AI content.”

Quick self-check (2 minutes)

Answer yes/no:

• Do I have 3 clear content pillars?
• Do I have a post template that makes writing easy?
• Did I publish 3 proof-based posts linked to projects?
• Do I have a backlog of 10 topics from real work?
• Do I have a distribution checklist I can sustain?

If any “no” — fix it before moving on.