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Generative AI Mastermind International·Mastermind Session Recordings·2:11:51

Bonus Session (Day 3): No-Code Automation in Make.com - Form to Sheet to Email, the 7-Step Process, and a Daily AI Image-and-Caption Poster for Instagram and LinkedIn

Ritesh Hegre Guest trainer - automation consultant ('400+ automations, 100+ clients'); both live builds and the Q&A · Kasturika Outskill senior program associate - host, bonuses and program pitch

The short version

  1. Automation is 'if this, then that': a trigger and its actions. Build 1 in Make.com: a Google Form -> a linked Sheet -> 'Watch new rows' -> Outlook/Gmail 'Create and send a message' with dragged-in fields; a plain-text body arrives without line breaks, so ChatGPT converts it to HTML (0:09-0:29). Scheduling: every 15 minutes is the free-plan floor, a fetch limit per run queues the rest, nothing sends twice (0:29-0:34).
  2. Make vs Zapier vs n8n: Zapier ~8,000 integrations but a stingy free tier; Make ~3,000 and ~1,000 free credits a month; n8n fewer natives but the best for AI and agentic builds (0:34-0:37).
  3. The 7-step process for automating anything: capture the workflow, map the information flow, identify decision points, pinpoint bottlenecks, define triggers and actions, select tools, implement-test-monitor-optimise; worked on a lead-form -> email -> sales alert -> CRM example (0:37-0:47).
  4. Build 2: OpenAI 'Generate an image' (DALL-E 3) from a motivational-quote prompt -> OpenAI 'Analyze the image' writes the caption with no meta text -> Instagram 'Create a photo post' (business account via Facebook login); a Router adds a LinkedIn branch, which fails until an HTTP 'Get a file' module converts the image URL to binary - LinkedIn wants bytes, Instagram takes a URL; then the whole thing on a daily 6 PM schedule, under a dollar a run (0:48-1:28).
  5. Q&A: no-code wins on speed, code wins on granular control; Twilio for SMS; cross-platform chaining possible but costly (1:26-1:47). The last 25 minutes are the accelerator / fellowship pitch and bonus links (1:47-2:11).

At a glance, three clicks deep

Skim here first: the closed row is the glance, open is the study card with the key points and timestamps, and the ↓ link drops to that concept's full write-up below.

01If this, then that - and the 7-step process for automating any workflowTrigger -> actions;›

Trigger -> actions; seven steps from written workflow to monitored automation.

'If this, then that' (0:09-0:11)

Seven steps whiteboarded (0:37-0:47)

Worked lead-form example (0:43-0:47)

↓ Full write-up of this concept

02Build 1: Google Form -> Sheet -> Make 'Watch new rows' -> email, with the HTML fixForm -> Sheet -> watch rows -> email;›

Form -> Sheet -> watch rows -> email; HTML body; 15-minute polling; no duplicates.

Form + linked Sheet (0:14-0:18)

Watch new rows; spreadsheet ID; header range (0:19-0:24)

Email with dragged fields; HTML via ChatGPT (0:22-0:29)

15-minute floor; fetch limit; duplicate tracking (0:29-0:34)

↓ Full write-up of this concept

03Make vs Zapier vs n8n: integrations, free tiers, and which is best for AIChoose by integrations and budget;›

Choose by integrations and budget; n8n for AI-heavy flows; code only for granular control.

Zapier ~8,000 / Make ~3,000 / n8n ~1,000 (0:34-0:36)

Make's free credits (0:35)

No-code for speed, code for control (1:44-1:45)

↓ Full write-up of this concept

04Build 2: DALL-E image -> caption from the image -> Instagram post, dailyImage -> caption-from-image -> post -> schedule;›

Image -> caption-from-image -> post -> schedule; forbid meta text in unattended prompts.

OpenAI key, credits, org ID (0:50-0:53)

DALL-E 3 generation; caption via image analysis (0:52-0:57)

Instagram business via Facebook (0:58-0:59)

Daily schedule; under a dollar (1:24-1:28, 1:42)

↓ Full write-up of this concept

05Router branches, and the LinkedIn binary-vs-URL gotchaRouter for multi-destination flows;›

Router for multi-destination flows; know whether each API wants a URL or binary; Delay per branch.

Router + optional filters (1:00-1:02, 1:19-1:20)

HTTP Get a file -> binary for LinkedIn (1:06-1:09)

Per-branch delays (1:24-1:28)

↓ Full write-up of this concept

06What the free mastermind is selling, and what it hands outThree attendance bonuses;›

Three attendance bonuses; two paid programs; all time-bound.

Bonus links per day (2:04-2:09)

Accelerator and Fellowship terms (1:52-1:59)

↓ Full write-up of this concept

The concepts in full

01

If this, then that - and the 7-step process for automating any workflow

Before the tool: write the workflow down, find the decision points, name the bottleneck.

Every automation is a trigger and actions (an Amazon order -> confirmation email). Ritesh's PROCEDURE for any workflow: (1) capture it in writing; (2) map where information originates and must go (form -> sheet -> email -> Slack/CRM); (3) identify decision points ('automation consulting' vs 'web app' branches); (4) pinpoint the manual pain (sending emails, sales not knowing a lead came in, CRM re-keying); (5) define triggers and actions explicitly; (6) pick the platform that has the integrations; (7) implement, test, monitor, optimise - weekly at first, then monthly. Cross-platform chains are possible over webhooks but add cost.

Why it matters

A tool-independent checklist that outlives Make, Zapier and n8n.

02

Build 1: Google Form -> Sheet -> Make 'Watch new rows' -> email, with the HTML fix

The registration email arrived as one long line. ChatGPT turned it into HTML and it arrived right.

PROCEDURE: forms.new with name, email and a multiple-choice source question; publish 'anyone with the link'; link responses to a new Sheet. In Make: new scenario -> Google Sheets 'Watch new rows' (OAuth; spreadsheet ID is the string between /d/ and /edit; header range A1:D1; row limit) -> Outlook (or Gmail) 'Create and send a message', subject 'Registration Successful', drag name and email into the body. Paste the body into ChatGPT for HTML so line breaks render; re-test. Scheduling: 'every 15 minutes' on the free plan (per-minute on paid), fetch limit per cycle queues the rest, processed rows are tracked so nothing sends twice.

Why it matters

The simplest end-to-end automation a beginner can copy, including its one gotcha.

03

Make vs Zapier vs n8n: integrations, free tiers, and which is best for AI

Eight thousand integrations, three thousand, or a thousand and the best agents - pick by what you need to connect.

Zapier: the most integrations (~8,000), most mature, least generous free tier. Make: ~3,000 integrations, ~1,000 free credits a month, the demo platform. n8n: fewer native integrations but strongest for AI and agentic automation, and self-hostable. Chain platforms only when one lacks an integration; each hop costs. And the coding question: no-code wins on speed; code wins when every detail must be controlled.

Why it matters

The tool-choice answer for Technology On Call's client automations.

04

Build 2: DALL-E image -> caption from the image -> Instagram post, daily

Tell the caption model not to include any supporting text - nobody is going to edit it before it posts.

PROCEDURE: connect OpenAI in Make (API key from platform.openai.com, billing credits added, organisation ID); 'Generate an image' with DALL-E 3 from 'a motivational quote for entrepreneurs, shareable on Instagram'; pass the image URL to 'Analyze the image' with a caption prompt that forbids meta text; 'Create a photo post' on Instagram (business account connected via Facebook login). Convert the start into a daily schedule (6 PM) and the pipeline runs unattended; per run 'probably less than a dollar', usage visible per step. OpenAI API billing is separate from a ChatGPT subscription.

Why it matters

A complete, cheap content automation - and the caption-prompt discipline any unattended step needs.

05

Router branches, and the LinkedIn binary-vs-URL gotcha

'Missing value: file name and data.' Instagram took the URL. LinkedIn wanted the bytes.

A Router module splits one flow into parallel branches so the same image feeds an Instagram caption and a LinkedIn post without regenerating; filters on a branch route by a field (e.g. service type). The LinkedIn 'Create a user image post' module failed repeatedly until an HTTP 'Get a file' module fetched the image URL into binary data - LinkedIn's API needs the file, Instagram's accepts a link. Per-branch delays and schedules (Instagram at noon, LinkedIn two hours later) are set with a Delay module.

Why it matters

A transferable API-integration gotcha, caught live.

06

What the free mastermind is selling, and what it hands out

Twenty-five minutes of the bonus session are the pitch. Recorded so the rest can be judged.

Attendance bonuses: Day 1 a 3,000-prompt library, Day 2 a 'make money with AI' kit, Day 3 a personalised AI toolkit; a combined link; recordings, certificate, roadmap and workbook by email the next day. The Accelerator (14 days, five levels, weekday and weekend live sessions, discounted 'from 9,995 to 2,995', cohort Oct 25) and the Fellowship (six months, weekends, interview entry, 5,995, Klarna instalments, Nov 30). Prices spoken digit-by-digit; treat as approximate and expired.

Why it matters

Context for the mastermind's structure, not a lesson.

Tools referenced

ToolCoverageMomentContext
Make.comdemonstratedBoth scenarios built live
Google FormsdemonstratedLead form
Google SheetsdemonstratedTrigger source
OutlookdemonstratedSend action
ChatGPTdemonstratedPlain text -> HTML
OpenAI PlatformdemonstratedAPI key, billing, org ID
DALL-EdemonstratedDALL-E 3 image generation
InstagramdemonstratedPhoto post via business account
LinkedIndemonstratedImage post; binary data required
ZapierexplainedComparison
n8nexplainedBest for AI / agentic flows
GmailmentionedAlternative send action
TwiliomentionedSMS example
GumloopmentionedAsked about; unused

Action items

    Resources mentioned

    Resources
    • docMake.com scenarios built
    • docMentioned in Q&A

    Extraction notes

    This page was built from an auto-generated transcript, which garbles product and people's names. Those were corrected silently in everything above and logged here for transparency. The warnings flag claims that were true on the recording day but change fast.

    Transcript corrections applied

    The transcript saysThe trainer actually means
    Hritesh / Pratesh / RakeshRitesh Hegre
    Ritz (his company)unresolved company name
    Natal / Anytime / an 8 10n8n
    o 4 minuteio4-mini

    True on recording day — verify before relying