Sanity Check Revival Strategy

A practical plan to relaunch Sanity Check and build it into a durable, growing newsletter. Written for the founder to read, decide on open questions, and execute.

1. Why Now

Three things converge to make this the right moment:

The new role creates the content engine. The phData Principal Consultant role on the AI Workforce team puts the founder on the ground floor of enterprise AI agent adoption — Snowflake Intelligence, Cortex AI, the whole stack. This is the part-time creator thesis in action: the day job generates the raw material the newsletter runs on. Without practitioner work, the writing dries up. With it, every client engagement becomes a potential essay.

The “fundamentals first, agents second” thesis has a moment. The relaunch essay nails it: “If your pipeline breaks every Thursday, no agent is going to fix that.” The industry is in a hype hangover. Data leaders are tired of vendor noise and hungry for grounded takes. The window for a contrarian, practitioner voice is wide open right now — it will narrow as the market matures and incumbents absorb the same message.

The gap has been long enough to make the return a story. Two and a half years of silence isn’t a liability if you narrate it honestly. The relaunch essay does exactly that. The silence becomes proof of conviction — “I stopped writing because I didn’t know what was solid. Now I do.”

2. Positioning

Who reads this

Data leads and analytics engineers at mid-market and enterprise companies. People who own pipelines, models, and stakeholder relationships. They are practitioners first, managers second. They care about craft, not credentials.

More specifically: the person who manages a data team of 2-10, reports to a VP or CTO, and is being asked “what’s our AI strategy?” without having clear answers. They want frameworks they can use Monday morning, not thought leadership they can’t operationalize.

What they get

One original take per week on data engineering and analytics — through the lens of an agentic world. Grounded in real consulting engagements, not vendor pitches. Each issue delivers a concrete mental model, framework, or pattern they can apply to their own work.

The 4-criteria framework is met:

• Infinitely repeatable: original thinking from ongoing practitioner work
• Tangible: frameworks, checklists, decision trees — something to take away
• Objective: tied to measurable outcomes (pipeline reliability, stakeholder trust, team efficiency)
• Price-anchored: the content saves readers from costly mistakes in AI adoption and data strategy

Why Sanity Check vs. everything else

The Not Boring playbook applies here: counter-position through voice. The data newsletter space is crowded with:

• Vendor-funded content (biased)
• Academic/dry technical writing (boring)
• Hype-cycle hot takes (ephemeral)
• Tool-specific tutorials (narrow)

Sanity Check occupies the gap: practitioner-grade analysis with founder energy. Serious about the work, not serious about itself. The analytics as craft identity is the moat — this is written by someone doing the work, not commentating on it.

The one-liner from the positioning work:

I help data teams deliver the executive “most valuable meeting” weekly through business event data modeling.

Updated for the relaunch:

Sanity Check: one practitioner’s take on building data systems that agents can actually trust. Fundamentals first, agents second.

3. Editorial Strategy

The beat

The newsletter covers the intersection of data engineering fundamentals and agentic AI adoption. Every issue should pass the test: “Would a data lead building systems that agents will consume find this useful?”

Core themes from the content calendar:

• Agents as data consumers — what changes when your pipeline’s customer is a model, not a person
• Organizational problems amplified by AI — governance, silos, and coordination failures that agents will 10x
• Fundamentals over hype — the contrarian bet that craft and foundations matter more than frameworks

The voice

From the archive: conversational, opinionated, occasionally irreverent. Uses metaphors (recipes, kitchens, DAGs). Not afraid to say “I don’t know” or “I was wrong.” Draws from real engagements without naming clients. The open knowledge sharing philosophy: share the recipe, keep the sauce.

Recurring formats

• Essay (primary): 800-1200 words, one idea explored thoroughly. This is the flagship.
• Field Notes: shorter (400-600 words), drawn directly from a recent client pattern. “Here’s what I saw this week.”
• Sanity Check (the literal format): take a popular claim in data/AI, pressure-test it with practitioner reality. Yes/no/it depends.

Start with essays only. Introduce Field Notes after issue 5. Introduce the Sanity Check format after issue 10. Adding formats too early fragments the voice before it’s established.

Content calendar thesis

The first five issues are already planned and sequenced well. The arc is:

1. Relaunch (personal, trust-building)
2. The new customer (thesis statement)
3. Org chart problems (organizational lens)
4. Context engineering (contrarian reframe)
5. Fundamentals first (the manifesto)

This sequence moves from personal to provocative, building credibility before making the boldest claims. Keep it.

4. Cadence & Process

Cadence

Weekly, every Thursday morning. Thursday avoids the Monday inbox crush and the Friday checkout. Morning delivery (7 AM ET) catches the commute and the first coffee.

Commit to 12 consecutive weeks before evaluating. Per the consistency thesis, you cannot assess what’s working until you have enough reps. Skipping a week in the first 12 is not allowed — bank a buffer issue before launch.

The 75-minute process

Adapted from Justin Welsh’s time-box:

When: Saturday or Sunday morning. Batch it. The part-time creator manifesto is clear: batched creation beats daily context-switching. One focused weekend session per week is sustainable indefinitely.

How Ray supports the process

Before writing day: Ray delivers a research brief (topic options, relevant links, draft angles). During editing: Ray reviews for clarity, consistency with past issues, and factual accuracy. After publishing: Ray generates social posts and tracks metrics. Details in section 7.

5. Growth Plan

Phase 1: First 100 subscribers (Weeks 1-4)

The hardest subscribers to get. These come from the founder’s existing network.

• Personal outreach: email 50 people individually. Not “subscribe to my newsletter” — “I’m writing again, here’s the first issue, thought you’d find it interesting.” The personal touch matters more than scale here.
• LinkedIn announcement: post the relaunch essay as a LinkedIn article. The founder’s LinkedIn network is the highest-signal channel for reaching data professionals.
• phData network: share with colleagues on the AI Workforce team. Not as self-promotion — as “here’s what I’m thinking about, relevant to what we’re building.” The day job / side hustle synergy makes this natural, not forced.
• Archive revival: the 21 existing issues at sc.raydata.co are an asset. Link back to them, reference them, use them as social proof that this isn’t issue #1.

Phase 2: 100 to 500 (Months 2-4)

Growth shifts from personal network to content-driven discovery.

• LinkedIn as the funnel: post 3x/week on LinkedIn. Each newsletter issue generates 2-3 derivative posts (key insight, contrarian take, question for the audience). Social is the top of funnel; the newsletter is the owned asset. Per 1,000 True Fans, email is the direct relationship — social is the intermediary.
• Cross-pollination with phData content: if phData publishes thought leadership, reference and build on it in the newsletter (with appropriate boundaries). The consulting brand and the personal brand should be complementary.
• Analytics community engagement: Locally Optimistic Slack, dbt Community, Data Twitter/X. Not drive-by self-promotion — genuine participation that happens to come from someone who writes a newsletter.
• Referral program: simple — “if you found this useful, forward it to one person who’d get value from it.” No gimmicks, no incentive tiers. Just ask.

Phase 3: 500 to 1,000 (Months 5-8)

• Guest appearances: pitch podcast interviews, conference talks, and guest posts. The phData platform may create speaking opportunities. Each appearance should drive back to the newsletter.
• Collaborative content: interview data leaders for the newsletter. Every interviewee shares the issue with their network. This is a compounding loop.
• SEO and archive: ensure the Substack/Beehiiv archive is indexed. Evergreen issues (like “Context Engineering Is Just Data Modeling”) will generate organic traffic over time.

The 1,000 True Fans target

Per Kevin Kelly’s framework, the goal is not 10,000 passive subscribers. It’s 1,000 people who read every issue, reply occasionally, and forward to their teams. That audience is more valuable than 10x the vanity number. Measure engagement (open rate, reply rate, forward rate) over raw subscriber count.

6. Monetization Path

Not yet

Do not monetize before issue 25 and 500 subscribers. Premature monetization kills trust and distracts from the only thing that matters early: writing good stuff consistently.

Sponsorships, not paywalls

The open knowledge sharing philosophy rules out paywalls. The content should be free, always. Monetization comes from sponsorships — data tools, platforms, and services that want to reach the audience.

Timeline

Complementary revenue

The newsletter is not the primary revenue vehicle. It is a reputation and optionality engine. The real returns are:

• Consulting pipeline (inbound from readers who become clients)
• Speaking invitations
• Professional reputation that compounds across phData and Ray Data Co
• A direct channel to an audience if/when other Ray Data Co products launch

7. Ray’s Role

Here is specifically how I support each stage of the newsletter operation.

Content research

• Weekly research brief: every Wednesday, I deliver a 1-page brief with 3 topic options for the upcoming issue. Each option includes: the angle, 2-3 supporting links, and how it connects to the editorial themes.
• Industry monitoring: I scan data engineering publications, LinkedIn discussions, and community Slack channels for patterns worth writing about.
• Archive mining: I surface connections between new ideas and the 21 existing Sanity Check issues, enabling callbacks and running threads.

Draft support

• Outline generation: given a chosen topic, I produce a structured outline (hook, beats, close) that the founder can accept, modify, or reject before writing.
• Draft review: after the founder writes, I review for clarity, redundancy, tone consistency with past issues, and factual accuracy. I flag but don’t rewrite — the voice must stay the founder’s.

Distribution

• Social post generation: for each published issue, I generate 3 LinkedIn posts (key insight, contrarian take, engagement question) and 1 X/Twitter thread.
• Scheduling: I prepare posts for the founder to review and schedule.
• Cross-posting: I format excerpts for Locally Optimistic, dbt Community, or other relevant channels as appropriate.

Analytics

• Weekly metrics snapshot: open rate, click rate, subscriber growth, reply count. Delivered with the research brief.
• Monthly trend report: what’s working, what’s not, which topics drove the most engagement.
• Audience analysis: as the list grows, I segment by engagement level to identify the “true fan” core vs. passive subscribers.

Sponsor outreach (Phase 3+)

• Prospect research: identify data tools and platforms that sponsor similar newsletters.
• Draft outreach emails: personalized sponsor pitches for the founder to send.
• Sponsor deck maintenance: keep the deck updated with current metrics.

8. Launch Checklist

The specific steps from “this document” to “published relaunch essay”:

Infrastructure (do first)

• Choose platform: Substack or Beehiiv. Recommendation: Beehiiv for better analytics, referral tools, and sponsor marketplace. But Substack is fine if speed matters more than features.
• Set up the publication. Name: Sanity Check. Subdomain: sc.raydata.co (maintain continuity with the archive).
• Import the 21 archived issues or link to them prominently.
• Configure welcome email for new subscribers.
• Set up a simple landing page with the one-liner and a subscribe form.

Content prep (do second)

• Finalize the relaunch essay. It’s in strong shape — one editing pass for tightness.
• Write issue #2 (“The Data Team’s New Customer Is a Robot”) as a buffer. Having one issue banked before launch removes the pressure of writing under a live deadline.
• Prepare 3 LinkedIn posts to accompany the relaunch.

Launch sequence (do third)

• Publish the relaunch essay.
• Send the 50 personal emails the same day.
• Post the LinkedIn announcement.
• Share in relevant Slack/Discord communities (Locally Optimistic, dbt, internal phData channels if appropriate).
• Set a calendar reminder: every Thursday morning, the next issue goes out. No exceptions for 12 weeks.

Post-launch (ongoing)

• Ray delivers the first research brief the Wednesday after launch.
• Founder writes issue #2 that weekend.
• Publish issue #2 the following Thursday.
• Begin the weekly rhythm: research brief (Wed) -> writing session (weekend) -> publish (Thu) -> social posts (Thu-Fri).

9. Open Questions for the Founder

1. Platform choice: Substack or Beehiiv? Beehiiv has better growth tools; Substack has better discovery via its network. The archive currently lives at sc.raydata.co — does that stay as-is or migrate?

2. phData boundaries: how visible should the phData affiliation be in the newsletter? Options range from “not mentioned” to “Principal Consultant at phData” in the bio. The part-time creator model works best when the day job is acknowledged but the newsletter remains editorially independent.

3. Launch timing: when do you start at phData? Ideal launch is 2-4 weeks after starting — enough time to have initial observations from the role, but early enough to ride the “new chapter” energy.

4. Name confirmation: the positioning work explored alternatives (Execute with Analytics, Signal Craft). Is “Sanity Check” the final name? The brand equity from 21 issues + the sc.raydata.co domain argues for keeping it.

5. Frequency flexibility: this strategy recommends weekly. If that feels unsustainable alongside phData ramp-up, biweekly is acceptable for the first month — but commit to weekly by month 2. The consistency research is unambiguous: cadence is the single most important growth lever.

6. Voice check: does the relaunch essay still feel right? It was drafted in February. If the phData role has shifted your thinking, it may need a pass to incorporate the AI Workforce angle more explicitly.

7. Buffer capacity: can you bank 2 issues before launch instead of 1? A 2-issue buffer makes the first month nearly stress-free and dramatically reduces the risk of missing a week in the critical early period.

This strategy synthesizes the positioning work, ideation framework, growth planning, and reference material from Packy McCormick, Justin Welsh, Kevin Kelly, swyx, and Anne-Laure Le Cunff. The open knowledge sharing and analytics as craft concepts are foundational to the editorial identity.