Solanasis Docs

solanasis_claude_code_cold_outreach_playbook_2026-03-10

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Solanasis Playbook: Claude Code + Baserow + Gmail for Founder-Led Cold Outreach

Date: 2026-03-10
Purpose: A verified guide another AI can use to help Dmitri design and implement a cold outreach system that feels authentic, stays founder-led, and still removes as much manual work as possible.

1) The bottom line

Baserow as CRM + Claude Code / Claude Cowork for research and drafting + n8n for orchestration + Gmail as the actual sender

That is the best fit for the real goal:

  • emails should feel like Dmitri actually wrote them
  • Claude should do the research, structuring, and drafting
  • the system should preserve a human approval gate
  • Gmail should remain the visible sending layer whenever possible

Why this wins

Because after checking the live docs, the important architectural fact is this:

  • Claude’s Google Workspace connector can create Gmail drafts
  • Claude’s Google Workspace connector cannot send emails on Dmitri’s behalf

That pushes the design toward a draft → approve → send workflow, which is actually the right move for authentic founder-led outreach.

2) What was verified live

Anthropic / Claude

Verified from Anthropic docs and support:

  • Claude Code can connect to external tools and systems through MCP (Model Context Protocol)
  • Claude Code can also use hooks and tool integrations as part of broader workflows
  • Claude’s Google Workspace connector can create email drafts
  • Claude’s Google Workspace connector does not send emails automatically

Implication: Claude should be treated as the researcher + drafter + CRM updater, not the final sender.

Baserow

Verified from Baserow docs:

  • Baserow is API-first
  • Baserow supports Database API
  • Baserow supports webhooks
  • Baserow supports workflow automation
  • Baserow now has an official MCP Server
  • Baserow supports row change history
  • Baserow supports row comments and mentions

Implication: Baserow can stay as the system of record for outreach without becoming a dead-end spreadsheet.

n8n

Verified from n8n docs:

  • n8n has built-in Baserow and Gmail nodes
  • n8n supports AI workflows
  • n8n supports human-in-the-loop approval for gated tool calls
  • the Gmail node can participate in human review / approval patterns

Implication: n8n is the cleanest orchestration layer between Baserow, Claude-generated output, and Gmail sending.

Brevo

Verified from Brevo docs:

  • Brevo’s deliverability guidance is centered around contacts expecting to receive emails
  • Brevo emphasizes clean contact lists, consent-oriented best practices, sender reputation, and compliance

Implication: Brevo is much better as a newsletter / nurture / transactional system than as the core engine for founder-led cold outbound.

Smartlead / Instantly

Verified from their live docs:

  • Smartlead supports variables / personalization fields and API-driven automation
  • Instantly has an active API v2 and supports custom variables on leads
  • both are legitimate tools for sequence-driven cold outbound infrastructure

Implication: these are viable Phase 2 tools when scale matters more, but they should not be the starting point if “sounds exactly like me” is the priority.

Google Workspace CLI (gws)

Verified from the GitHub repo:

  • Google Workspace CLI is now positioned as one CLI for Google Workspace
  • it is built for humans and AI agents
  • it supports structured JSON output
  • it ships with MCP support / gws mcp
  • the repo explicitly notes it is not an officially supported Google product

Implication: gws is interesting and worth watching, but for production sending I would still lean toward boring/stable integrations first.

3) What current operators appear to be doing

This section blends live Reddit / community observations with official product docs. Treat this as anecdotal but useful signal, not gospel.

The pattern that keeps showing up

Across current cold-email communities, the recurring split is:

  • CRM / research system
  • sequencing / sending system
  • deliverability infrastructure
  • human editing on the important messages

The strongest themes I saw

A. People are separating personalization from sending

Operators increasingly use one tool to:

  • enrich data
  • identify triggers
  • draft context
  • write snippets

And a different tool to:

  • send
  • sequence
  • warm domains
  • manage reply tracking

That separation is healthy.

B. “Hyper-personalization” is losing credibility when it gets creepy

A repeated community theme is that bad personalization feels invasive, fake, or over-engineered.

The better pattern is:

  • one relevant observation
  • one reason for reaching out now
  • one clear next step

That fits Dmitri’s style anyway.

C. Founder-led outreach still benefits from a partial manual layer

For small-volume, high-value outreach, current operator chatter still supports:

  • plain-text emails
  • smaller daily volumes
  • a real reply-to identity
  • manual review on first touches
  • automation mainly for research, tracking, and follow-up logic

D. Clay is often used for enrichment, but many operators still see it as expensive

Clay is clearly part of the modern outbound stack, especially for enrichment waterfalls and signal-based workflows, but community reports still frame it as powerful and expensive.

Practical reading: Clay is an optional later-stage enrichment layer, not something Solanasis must adopt on day one.

Core architecture

Baserow (CRM / source of truth)
    ->
n8n trigger (webhook / row change / schedule)
    ->
Claude step (research + summarize + draft + score)
    ->
n8n approval gate
    ->
Gmail draft or Gmail send
    ->
Baserow update
    ->
follow-up workflow / thread tracking

Role of each system

Baserow

Use Baserow for:

  • people
  • companies
  • accounts
  • relationship source
  • outreach stage
  • notes
  • personalization fragments
  • thread IDs
  • next action dates
  • do-not-contact flags
  • handoff status

Claude Code / Claude Cowork

Use Claude for:

  • account research
  • company summary
  • why-now identification
  • writing subject lines
  • drafting 2 to 3 message variants
  • rewriting messages in Dmitri’s voice
  • converting messy notes into structured fields
  • deciding whether a lead is worth a custom first-touch

n8n

Use n8n for:

  • triggers
  • routing
  • approval
  • scheduling
  • sending to Gmail
  • syncing results back to Baserow
  • branching follow-up logic

Gmail

Use Gmail for:

  • founder identity
  • final drafts
  • sending
  • reply threading
  • trustworthy “sent from me” behavior

5) Why I do not recommend Brevo as the primary cold-outreach engine

Brevo is good for:

  • newsletters
  • nurture sequences
  • announcements
  • website signups
  • transactional email
  • operational campaigns

Brevo is not my recommended primary engine for this exact use case because:

  • its own deliverability guidance is centered on expected recipients
  • it is naturally more “campaign platform” than “founder-crafted outbound”
  • it introduces a marketing-system feel too early

Best use of Brevo for Solanasis

Use Brevo later for:

  • newsletter distribution
  • warm follow-up lists
  • educational nurture after opt-in
  • referral partner updates
  • downloadable lead-magnet follow-up

Not for the first, sharp, founder-led cold email.

6) Two-track strategy for Solanasis

Track 1 — founder-authentic outreach

Use this for:

  • warm intros
  • lightly cold outreach
  • partner outreach
  • nonprofit / SMB prospects
  • higher-value accounts
  • referrals and friend-of-friend paths

Stack

  • Baserow
  • Claude Code / Cowork
  • n8n
  • Gmail

Sending style

  • plain text
  • short
  • relevant
  • 1 clear pain observation
  • 1 soft ask
  • manual review before send

Track 2 — scaled outbound infrastructure

Use this only after messaging is proven.

Stack

  • Baserow as source of truth
  • Claude for personalization fields
  • Smartlead or Instantly for sequences
  • optional Clay for enrichment
  • n8n for sync / control / approvals

Why delay this

Because scale before signal usually creates:

  • lower-quality messaging
  • deliverability headaches
  • more fake-sounding AI output
  • less founder voice

7) Baserow schema I recommend

Table: companies

Fields:

  • company_id
  • company_name
  • website
  • industry
  • employee_range
  • hq_location
  • nonprofit_or_forprofit
  • tech_stack_notes
  • security_signal
  • ops_signal
  • ai_signal
  • why_now_signal
  • fit_score
  • notes

Table: contacts

Fields:

  • contact_id
  • first_name
  • last_name
  • title
  • email
  • linkedin_url
  • company_id (link)
  • relationship_strength
  • source
  • owner
  • timezone
  • personal_notes
  • do_not_contact

Table: outreach_records

Fields:

  • outreach_id
  • contact_id (link)
  • company_id (link)
  • campaign_type
  • stage
  • status
  • draft_subject
  • draft_body
  • draft_variant_b
  • hook_line
  • why_now
  • offer_angle
  • credibility_line
  • cta_line
  • confidence_score
  • requires_manual_review
  • approved_to_send
  • sent_at
  • gmail_thread_id
  • last_reply_at
  • reply_status
  • next_follow_up_at

Table: touch_log

Fields:

  • touch_id
  • outreach_id (link)
  • touch_number
  • touch_type
  • content_snapshot
  • sent_at
  • result
  • notes

Table: playbooks

Fields:

  • playbook_id
  • segment
  • pain_pattern
  • offer_mapping
  • message_pattern
  • examples
  • last_updated

8) Workflow design

Workflow 1 — new lead to founder-ready draft

Trigger

A row is created or updated in Baserow with:

  • status = new
  • owner = Dmitri
  • approved_to_research = true

Steps

  1. Pull company + contact data from Baserow
  2. Gather external context:
    • company website
    • recent announcement or funding if relevant
    • job posting / hiring signal if relevant
    • any previous interaction notes
  3. Claude produces:
    • company summary
    • likely pain point
    • why-now angle
    • relevant Solanasis service
    • subject line options
    • 2 message variants
    • confidence score
  4. Write all of that back into Baserow
  5. Mark row as awaiting_approval

Output standard

The system should produce structured fields first, not just one blob of email text.

Workflow 2 — approval gate

Rule

Nothing sends without approval on first-touch founder outreach.

Approval options

Use n8n to route an approval request through one of these:

  • Gmail
  • Slack
  • Telegram
  • internal n8n chat
  • another review endpoint

Approval decision

  • approve: create Gmail draft or send
  • revise: send back to Claude with notes
  • reject: mark as hold / archive / do-not-contact

Workflow 3 — Gmail execution

Best practice

For first-touch outreach, default to:

  • create Gmail draft
  • Dmitri reviews it
  • Dmitri sends manually

This preserves authenticity and keeps risk down.

Optional later mode

Once trust in the system is high:

  • allow “approved auto-send” only for lower-risk follow-ups
  • still keep manual review for the best accounts

Workflow 4 — reply tracking and CRM sync

When a reply arrives:

  1. thread gets identified
  2. reply status gets classified:
    • interested
    • not now
    • referral
    • unsubscribe
    • not a fit
  3. Baserow updates:
    • reply_status
    • last_reply_at
    • next_action
  4. Claude can draft the reply
  5. Dmitri reviews and sends

9) Authenticity rules

If the priority is “sounds like I typed this myself,” the system needs explicit rules.

Hard rules

  • keep the body in plain text
  • do not overuse marketing formatting
  • no fake friendliness
  • no synthetic compliments
  • no “noticed your impressive work” fluff
  • no exaggerated personalization
  • no pretending Dmitri personally researched details he did not actually verify

Preferred message structure

  1. relevant opener
  2. one grounded observation
  3. one plausible pain / risk / opportunity
  4. one line on why Solanasis is relevant
  5. soft CTA

Tone rules

  • direct
  • calm
  • informed
  • low-hype
  • not pitchy
  • not too polished
  • not robotic
  • not needy

10) Prompt pattern for Claude

Prompt: research + outreach pack

You are helping generate a founder-led outreach draft for Solanasis.
 
Goal:
Create a short, plain-text cold email that feels like Dmitri actually wrote it.
 
Inputs:
- Contact record
- Company record
- Website notes
- Recent signals
- Relationship notes
- Allowed offers:
  - Security Assessment
  - Disaster Recovery Verification
  - Data Migrations
  - CRM / systems integration
  - Responsible AI implementation
 
Requirements:
- Do not sound like a marketing platform
- Do not over-personalize
- Do not flatter
- Use one relevant observation only if it is grounded
- Prefer specificity over cleverness
- Keep email under 120 words unless there is a clear reason not to
- Produce structured output first
 
Output fields:
- hook_line
- why_now
- likely_pain
- best_offer
- subject_v1
- subject_v2
- email_v1
- email_v2
- confidence_score (1-10)
- send_recommendation: send / revise / skip

Prompt: rewrite into Dmitri’s tone

Rewrite this draft so it feels founder-led, direct, lightly raw, and human.
 
Rules:
- Keep it plain text
- Keep it grounded
- Make it feel like a real person typed it
- Remove anything that sounds like marketing automation
- No hype, no clichés, no obvious AI phrasing
- Prefer strong nouns and verbs over adjectives
- Keep the CTA soft

Prompt: follow-up email

Write a follow-up that adds one fresh angle instead of repeating the first email.
 
Rules:
- Plain text
- Short
- Respectful
- No guilt-tripping
- No “just bumping this up”
- Either add a useful observation, narrow the ask, or give an easy out

11) What to automate vs what to keep human

Automate aggressively

  • research collection
  • website summarization
  • signal extraction
  • CRM updates
  • status changes
  • task creation
  • draft generation
  • follow-up scheduling
  • thread syncing

Keep human longer

  • final first-touch send
  • approval of messaging
  • high-value account targeting
  • partner/referral outreach
  • replies to nuanced objections
  • escalation paths

12) Suggested phased rollout

Phase 1 — manual-but-assisted

Goal: create great emails faster without sacrificing feel.

Build

  • Baserow schema
  • n8n trigger from Baserow
  • Claude research + draft step
  • Gmail draft creation
  • Baserow status updates

Success metric

  • Dmitri feels the drafts are at least 80% usable
  • outbound volume increases without obvious drop in quality
  • no weird robotic tone

Phase 2 — approval-driven automation

Goal: reduce friction.

Add

  • formal approval workflow
  • follow-up scheduling
  • reply classification
  • better state tracking
  • enrichment helpers

Success metric

  • founder review time per email drops sharply
  • replies stay high quality
  • CRM stays clean

Phase 3 — selective scale

Goal: move from 1:1 founder outreach to light sequencing where it makes sense.

Add

  • Smartlead or Instantly for lower-risk segments
  • optional Clay enrichment
  • sending-domain separation if needed
  • more systematic follow-up campaigns

Guardrail

Do not scale until the messaging already works manually.

13) Tool shortlist

Best current fit for Solanasis

Primary stack

  • Baserow — CRM / source of truth
  • Claude Code — research, structuring, drafting
  • Claude Cowork / Claude connectors — Gmail / Drive context, draft support
  • n8n — orchestration, approval, sync
  • Gmail — final sender identity

Good optional additions

  • Smartlead — later-stage outbound sequencing
  • Instantly — later-stage outbound sequencing
  • Clay — later-stage enrichment and signal workflows
  • Google Workspace CLI (gws) — emerging agent-native Workspace tooling
  • Playwright MCP — browser automation for research only

14) GitHub / repo shortlist for another AI to inspect

Highest-value repos / docs to re-check

  • Anthropic Claude Code MCP docs
  • Anthropic Google Workspace connector docs
  • Baserow official MCP docs
  • Baserow API docs
  • Baserow webhook docs
  • Baserow workflow automation docs
  • n8n Baserow node docs
  • n8n Gmail node docs
  • n8n human-in-the-loop docs
  • Google Workspace CLI repo (googleworkspace/cli)
  • Microsoft Playwright MCP repo
  • punkpeye/awesome-mcp-servers
  • modelcontextprotocol/servers
  • selected Gmail MCP repos

Important caution

The GitHub ecosystem around Gmail MCP is moving fast. Treat these repos as promising tooling, not as equivalent to a mature enterprise product.

15) Red flags and anti-patterns

Avoid these:

  • building the whole thing inside Brevo first
  • letting Claude auto-send first-touch cold emails
  • over-personalized first lines that feel creepy
  • HTML-heavy first emails
  • generic “AI SDR” copy
  • using a sequencer before the message actually works
  • letting the CRM become unstructured note soup
  • stuffing every possible signal into the email
  • optimizing for volume before trust, fit, and tone

16) My actual recommendation

Best next move

Build the founder-authentic path first:

  • keep Baserow
  • use Claude Code to research and draft
  • use n8n to orchestrate
  • use Gmail for drafts and sending
  • require approval before send

Why

Because that gives the highest chance of:

  • sounding like Dmitri
  • preserving trust
  • staying flexible
  • avoiding premature complexity
  • building a real outbound system instead of buying one too early

When to add a sequencer

Only after:

  • the offer is validated
  • reply patterns are known
  • the tone is dialed in
  • follow-ups are proven
  • deliverability basics are under control

17) First implementation sprint

Sprint objective

Get from “lead in Baserow” to “reviewable Gmail draft” with clean state updates.

Tasks

  1. Finalize Baserow tables and fields
  2. Create Baserow webhook or automation trigger
  3. Create n8n workflow
  4. Add Claude prompt templates
  5. Add Gmail draft creation step
  6. Write results back to Baserow
  7. Add approval status and logging
  8. Test on 10 real prospects
  9. Score output quality
  10. tighten prompts and field structure

Definition of done

  • one new lead can enter Baserow
  • system produces a strong draft
  • Dmitri can review it quickly
  • send happens through Gmail
  • Baserow updates cleanly after send

18) Source notes for another AI

This section intentionally separates official docs from community signal.

Official / primary docs

Community / user-reported signal

These are not source-of-truth, but they are useful for current practice and operator sentiment.

19) Final instruction to another AI

If you continue this project, do not jump straight into “automated cold email at scale.”

Instead:

  1. keep Baserow as the source of truth
  2. build the founder-authentic path first
  3. make Claude generate structured research fields, not just polished copy
  4. create Gmail drafts before sending
  5. preserve a human approval gate
  6. add sequencing tools only after the message quality is proven

That is the path most likely to produce outreach that feels real, useful, and actually worthy of Dmitri’s name.

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