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Month 9-Week 4: Q3-closing post + Q4 capstone planning + profile update

Week summary

  • Goal: Publish the Q3-closing specialty post. Plan the Q4 capstone in writing. Update public profiles to reflect the new identity.
  • Time: ~9 h over 3 sessions.
  • Output: Ninth public blog post; Q4 capstone DESIGN.md; updated GitHub profile, LinkedIn, CV; Q3 retrospective.

Why this week matters

Q3 closes here. The specialty post compounds the year's work into one referenceable piece. The Q4 capstone plan is what makes Q4's first day a working day, not a planning day. The profile update is what converts year-of-work into hiring signal.

Prerequisites

  • M09-W01–W03 complete.
  • Session A-Tue/Wed evening (~3 h): publish post + engage
  • Session B-Sat morning (~3.5 h): Q4 capstone DESIGN
  • Session C-Sun afternoon (~2.5 h): profile update + Q3 retro

Session A-Publish the Q3-closing post

Goal: Final edit + publish broadly + engage with feedback.

Part 1-Final edit (45 min)

Read aloud. Trim. Verify all numbers / links.

Part 2-Publish (45 min)

  • Personal blog.
  • Cross-post: HN (Show HN if applicable), r/MachineLearning (Project flair), r/LocalLLaMA, X, LinkedIn.
  • Email to 5 specific track-relevant practitioners politely (e.g., for Track A: Hamel Husain, Eugene Yan, Inspect AI maintainers).
  • Post in 2–3 relevant Discords/Slacks.

Part 3-Engage (90 min)

This is your most-engaged post of the year. Respond to every substantive comment. Note unexpected questions-those are gold for Q4.

Output of Session A

  • Ninth public blog post live, ≥4 channels.
  • Engagement under way.

Session B-Q4 capstone planning

Goal: Detailed plan for the Q4 capstone. Repo started.

Part 1-Pick the capstone (60 min)

Recommended capstone shape: an open-source project that ties together your specialty work in a referenceable artifact.

Examples: - Track A: A trajectory-evaluation framework for agentic LLM systems, with comparisons to Inspect AI on a public benchmark. - Track B: A reproducible SWE-bench Lite submission with novel architecture, posted leaderboard score, and methodology blog series. - Track C: A serving + quantization tool or benchmark suite that aspires to upstream adoption.

Document choice in Q4_CAPSTONE.md with reasoning.

Part 2-Capstone DESIGN.md (90 min)

Write 2000+ words, more rigorous than M07-W01's specialty DESIGN: - Problem (paragraphs). - Why incumbents don't fit (specific tools, specific gaps). - Goals (numbered). - Non-goals. - Approach (architecture sketch + key decisions). - Success criteria (quantitative + qualitative). - Anchor experiment (the headline result). - Roadmap by week (M10-W01 through M12-W04). - Risks.

Part 3-Repo scaffold (60 min)

mkdir <capstone-name> && cd <capstone-name>
# uv init, README placeholder, LICENSE, CI scaffolding.
git init && git add . && git commit -m "scaffold"
gh repo create --public --source=. --push

Output of Session B

  • Q4_CAPSTONE.md plus capstone repo scaffold.

Session C-Profile update + Q3 retro

Goal: Reflect the year's progress in your public profiles. Run the Q3 retrospective.

Part 1-GitHub profile README (45 min)

Update or create a profile README at github.com/<you>/<you>: - Pinned: 4 best repos (anchor project, specialty, capstone scaffold, ml-from-scratch). - One-line: who you are, what you build, what you write. - Link to blog and most recent posts.

Part 2-LinkedIn + CV (45 min)

LinkedIn headline: "AI Engineer | Specialty: | Backend & Observability moat"

About section rewrite: - 2 paragraphs. - Lead with specialty. - Reference shipped artifacts (links). - End with "open to collaboration on X."

CV (separate from LinkedIn): - Reorder: AI specialty → Backend / SRE → other. - Add a "Selected Public Artifacts" section: 3-5 best blog posts + capstone link.

Part 3-Q3 retrospective (60 min)

Q3_RETRO.md: 

# Q3 Retrospective: Specialization + Infra

## Artifacts shipped
- Specialty repo at v0.5-public, README, tests, comparison vs incumbent
- vLLM benchmarks + AWQ comparison
- LoRA + QLoRA + DPO adapters with eval
- Multi-GPU FSDP run
- 3 substantive blog posts (M07-W04, M08-W04, M09-W04)
- 1 OSS PR
- ~12 paper notes

## KPIs vs Q3 targets (and Q1+Q2 cumulative)
| Metric | Q3 Target | Q3 Actual | Year cumulative |
|---|---|---|---|
| Public repos | 1–2 | 2 | 6 |
| Blog posts | 2 | 3 | 9 |
| Papers read | 12 | 12 | 32 |
| OSS PRs | 1+ | 1 | 2 |

## Lessons
1. Specialty depth is built by repeated source-reading + experimentation.
2. The bridge story (SRE → AI) is real and resonant in posts.
3. OSS contribution is awkward at first; gets easier each PR.

## Q4 capstone committed
- See Q4_CAPSTONE.md.

## Q4 plan
- M10: capstone build sprints.
- M11: long-form post + talk.
- M12: job-market reconnaissance + year-end retro.

## Confidence calibration before Q4
- [ ] I can speak with a practitioner in my specialty for 30 minutes without bluffing.
- [ ] I have at least one repo I'd point to in interviews.
- [ ] I have at least 3 posts I'd link in interviews.

Output of Session C

  • Updated GitHub, LinkedIn, CV.
  • Q3 retrospective committed.

End-of-week artifact

  • Ninth public blog post published, ≥4 channels
  • Q4 capstone DESIGN.md + scaffold
  • Updated profiles (GitHub README, LinkedIn, CV)
  • Q3 retrospective written

End-of-week self-assessment

  • I have a coherent professional identity that's legible publicly.
  • My Q4 capstone plan is specific enough that day 1 of M10 is execution, not deciding.
  • My specialty is named and defended by artifacts.

Common failure modes for this week

  • Vague Q4 capstone. "Polish things" is not a plan. Specific artifact + criteria.
  • Profile updates as cosmetic. Treat them as serious-they're the front door.
  • Skipping the engage phase. The Q3 post compounds when you reply.

What's next (preview of M10-W01-Q4 begins)

Capstone build kickoff: repo, DESIGN, eval target, first end-to-end feature.

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