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AI Catalyst C3·Core Session - Week 15·2:33:44

Session 30: C3 Town Hall — Four Cohort Products Under the Knife, Outcome Selling, and the Rest of the Programme

Harshit Tyagi Outskill programme director - hosts the town hall, critiques each product live, then teaches the outcome-selling ladder, the front-end/back-end sales split and the remaining curriculum. Name uncertain in ASR; distinct from Harshith Vaddiparthy (Session 23) - see OI-061. · Shivani Outskill community manager - runs the presenter roster and the CSAT at the end · Syed Cohort member - presented SkillPort, a security-reviewed skills marketplace. First name uncertain (ASR gives Saeed / Sayed / Elson). · Rohan Cohort member - 20 years in payments (Visa, BNY Mellon), systems architect; presented Swipe AI · Sarah Sebastian Cohort member - presented a vertical voice receptionist for tree trimmers and landscapers · Stephen Cohort member - 21 years in ERP/HR-payroll implementation; presented PERI, a full project-lifecycle platform · Palak Cohort member - 21 years in IT; presented RoleCompass.ai, role-level AI disruption verdicts with a 12-week plan. Has paying customers.

Session map

WHAT WAS SHOWNHOW TO SELL ITWHAT COMES NEXTSkills are a supply chain now…Validation beats polishwhat the four demos showed about sellin…Prompting to workflow to skil…Front-end automations sell, b…Go deep, not wideone niche, one story, one landing page…Where ideas come fromfunded-workflow lists, and the comment…For consumer products, build…What the rest of C3 coversLangGraph, evals, mobile, distribution,…
What was shownHow to sell itWhat comes next
click a node — its card pops up (drag it anywhere, × to close)
Concept

The map reads left to right — what was shown flow into how to sell it, then into what comes next. Click any node to open that idea here; every timestamp jumps into the recording.

The short version

  1. Four cohort products, each critiqued live. SKILLPORT (Syed) - a skills marketplace with a four-layer review pipeline, built because a Feb audit of ~4,000 skills found a third with problems and 76 actively stealing credentials; his own rule is 'I will say scanned and reviewed at this version on this day, I will never say safe.' SWIPE AI (Rohan) - payment-failure intelligence built on 20 years inside Visa and BNY Mellon; reads a 250,000-row failure file and reports what is recoverable in minutes against the three-month, percentage-of-recovery incumbents. VIRTUAL RECEPTIONIST (Sarah) - Vapi + Twilio + n8n for tree trimmers who cannot answer a phone from up a tree; not sold yet. PERI (Stephen) - a 21-year ERP consultant's whole implementation lifecycle, RFP to post-go-live support.
  2. THE ONE FRAMEWORK TO TAKE: the AI journey runs prompting -> workflow automation -> skills -> OUTCOME SELLING. Nobody wants to buy your skills.md; they want the outcome. 'They'll be like, you just get the thing done for me — don't teach me what a skill is, don't tell me to get a Claude Code subscription.' Once a skill file is tuned and tested, it stops being a file and becomes the engine of a product.
  3. FRONT-END AUTOMATIONS SELL; BACK-END ONES ARGUE. Sales and marketing automations have a legible ROI — more reach, more leads, more revenue — so they close. Operations, HR, bookkeeping and reconciliation automations have to prove a saving, and 'nobody's going to really trust you if you say that with ten executives in your operations department you will handle millions of dollars of business.' He says this is visible in what gets funded, and that his own company now leads with front-end work.
  4. WHERE TO GET IDEAS: read the Y Combinator workflow-automation list and Product Hunt, because each of those companies took ~$500k to automate one workflow for one niche — and the founder usually came from that niche. Then read comment sections where practitioners talk. His example: a friend with no knowledge of cosmetics mined a Reddit community's own lipstick-selection hacks, shipped an app, got banned from the community for pitching — and then simply bought $50 of Reddit ads against that same community and kept the signups coming.
  5. THE FEEDBACK THAT REPEATS ACROSS ALL FOUR. Narrow it: 'instead of going wide, go deep' — a feature list is not a story, and one story per customer means one landing page per customer. Evidence beats adjectives: 'currently it is just your word against mine — everyone writes secure, these terms are used very loosely.' Sell before you widen: Palak had 70 signups and real payments from one community gathering in April; Rohan had one unprompted user in Russia and no GTM; Sarah's product works and has never been sold. And the line aimed at everyone: 'if you'll just continue to build, you will just continue to pay for your subscriptions.'
  6. WHAT IS COMING IN THE REST OF C3: two to three sessions on agentic app building with LangGraph, plus observability and evals with LangSmith; one mobile session using Expo for iOS and Android; one or two dedicated distribution sessions; a product-readiness session with a skills-based checklist; and four 'Founders Time' episodes with startup and agency founders on how they actually got clients. A second town hall closes the programme.

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.

01Prompting to workflow to skills to outcome selling — the skill file is the engine, not the productOutcome selling: the tuned skill or workflow is internal machinery;2:09

Outcome selling: the tuned skill or workflow is internal machinery; what is priced and sold is the finished result, because buyers will not adopt your setup.

Prompting -> workflow automation -> skills -> outcome selling (2:09-2:11)

'Nobody really wants to get into n8n when something can be done in plain English and Claude Code' (2:07)

Skills are mostly free on GitHub - the file has little price (2:10)

'Just get the thing done for me - don't teach me what a skill is' (2:11)

Prototype the product as skill files first, then build around what worked (2:12)

A skills pile automating one business function can itself become a product (2:08-2:09)

↓ Full write-up of this concept

02Front-end automations sell, back-end automations argueSales and marketing automations carry legible revenue ROI and close;2:24

Sales and marketing automations carry legible revenue ROI and close; operations, HR and finance automations must argue a cost saving and close harder — unless the saving can be restated as money recovered.

Front end / back end = business function, not UI or tech stack (2:24)

Back end: operations, fulfilment, admin, HR, bookkeeping, invoice reconciliation (2:24-2:25)

Front end: sales and marketing - 'clear ROI' (2:25)

The credibility limit on savings claims (2:26)

Funding follows more money / more users / more eyeballs (2:26)

'To convince someone that this backend automation is actually going to drive ROI is going to be difficult in general' (2:27)

↓ Full write-up of this concept

03Where ideas come from: funded-workflow lists, and the comment sections nobody readsIdea sourcing = proven-playbook mining (YC, Product Hunt) plus practitioner comment mining, with the niche…2:12

Idea sourcing = proven-playbook mining (YC, Product Hunt) plus practitioner comment mining, with the niche and the founder's background read as signal.

YC workflow-automation list: ~$500k each, one workflow, one niche (2:12-2:13)

Founders usually come from the niche they automate (2:14)

'Spend time reading in places where other people would not' (2:15)

Read the comment section, not the post (2:15-2:16)

The lipstick app: community playbook -> app -> banned -> $50 of ads at the same community (2:16-2:18)

Live check on a 'no competitors' claim using a filtered YC link (0:45-0:46)

↓ Full write-up of this concept

04Skills are a supply chain now — and 'human reviewed' is not a trust signalAgent skills are an executable supply chain with prompt-injection and credential-theft risk;0:09

Agent skills are an executable supply chain with prompt-injection and credential-theft risk; trust is established by published, dated, version-pinned evidence — never by the word 'safe'.

Most of the room installs skills without reading skill.md (0:09)

Attack shape: curl-to-shell from a raw IP + an HTML comment telling the agent to hide it (0:10)

Feb audit, ~4,000 skills: a third problematic, 76 stealing credentials (0:10)

'NPM all over again, but the package now drives an agent' (0:10)

Four layers: package validation, static analysis, tool-less LLM pass, human line review (0:11, 0:14)

Approval tied to exact bytes; checksum-verified installs; instant version pull (0:11)

'I will never say safe, and nobody can' (0:11)

Host: publish benchmarks and test stats - 'everyone writes secure' (0:25-0:26)

↓ Full write-up of this concept

05Go deep, not wide: one niche, one story, one landing page per customerSell one story to one narrow audience;1:25

Sell one story to one narrow audience; a feature list is not a story; a single product legitimately warrants a different landing page per customer type.

'You are just giving me a list of features which are put together' (1:26)

The story changes for every single customer (1:26)

Narrow to two or three features; smallest niche possible (1:27-1:28)

Niche then sub-niche: consultants -> healthcare -> bioinformatics (1:28)

Paul Graham on starting broad (1:28)

'Instead of going wide, go deep' (1:29)

Ten landing pages for one product, one per customer type (1:35)

Dense screens lose people - he names his own ADHD (1:26)

↓ Full write-up of this concept

06Validation beats polish: what the four demos showed about selling too lateA payment is the only real validation signal;1:34

A payment is the only real validation signal; sell during the build, and let the first customer set the direction rather than your own feature backlog.

Palak: ~70 signups, real payments, first sale closed on a 9pm-to-11:30pm call after an April meetup (1:54-1:57)

She talks to users every two or three days (1:55)

Rohan: working product, no GTM, one unprompted user in Russia (0:47)

Sarah: works, demoed once, hallucinated a phone number, never sold (0:57-0:58)

Voice agents: multiple meetings, 150-200 test calls before beta (1:06-1:07)

Stephen: 21 years of expertise, seven-day weeks, zero pitches (1:24, 1:33)

'Use the experience to get clients, hire an intern to build' (1:34)

'If you'll just continue to build, you will just continue to pay for your subscriptions' (1:35)

↓ Full write-up of this concept

07For consumer products, build the thing users will show offConsumer distribution as a product feature: build a shareable artefact users want to be seen with, then add…2:18

Consumer distribution as a product feature: build a shareable artefact users want to be seen with, then add ratings, comments and a social layer around it.

'Something that helps my users flaunt that thing on their social media' (2:18)

B2C only - explicitly not a B2B strategy (2:18)

His 'spaces': topic buckets of links, with an MCP so Claude Code can summarise what you saved (2:20-2:23)

The share link is the feature, not the collection (2:22-2:23)

Ratings, comments, ecosystem around the shared artefact (2:23-2:24)

'You save those videos, you never go back to those videos - that's the hard part' (2:22)

↓ Full write-up of this concept

08What the rest of C3 covers: LangGraph, evals, mobile, distribution, foundersRemaining C3 curriculum: LangGraph agentic apps, LangSmith observability and evals, Expo mobile, distributi…2:27

Remaining C3 curriculum: LangGraph agentic apps, LangSmith observability and evals, Expo mobile, distribution, product readiness, four founder interviews, closing town hall.

Curriculum rewritten mid-programme after cohort feedback (2:04)

2-3 sessions: agentic app building with LangGraph (2:27)

Observability and evals with LangSmith (2:28)

One mobile session via Expo, iOS + Android (2:28)

1-2 dedicated distribution sessions (2:28)

Four 'Founders Time' guest episodes (2:29)

Product-readiness session with a skills-based checklist (2:30)

'Real apps, no webhook or anything of that sort' (2:30)

Second town hall closes the programme (2:31)

↓ Full write-up of this concept

The concepts in full

01

Prompting to workflow to skills to outcome selling — the skill file is the engine, not the product

2:09

You spent weeks tuning a skill file. Nobody will buy the file.

His history of the last two years in four moves. We started with PROMPTING — craft the words, get the answer. Then WORKFLOW AUTOMATION — drag nodes in n8n, wire them together, the process runs. Then SKILLS — agents got smart enough that the workflow could be written in plain English as a skills.md and handed to Claude Code or Codex, which is why he says "nobody really wants to get into n8n when something can be done in plain English and Claude Code." And now OUTCOME SELLING.

The reason the fourth rung exists is that the third one does not sell. Most skills are free on GitHub; a one-off skill sells only to a rare buyer; and the people with money have no appetite for the setup. "They'll be like, you just get the thing done for me — don't teach me what a skill is, don't tell me to get a Claude Code subscription, don't tell me all of these things, because I don't have the time. Just automate my work." So the tuned skill becomes internal machinery and what you list for sale is the finished outcome.

The engineering upside he points out is that the skill file is also the cheapest way to prototype the product: map the whole workflow as step one, step two, step three, test it yourself end to end with skill files, and only then build the application around the part that worked.

Worked example · from the session

He points at Rohan's Swipe AI from earlier in the same call: the entire product could have been tested first as a sequence of skill files before a line of the app existed. And at video production — Palak's pitch videos could become a skill that produces VSLs, but you would sell the finished video, not the file that makes it.

Why it matters

Paul has been building skills all year. This is the sentence that turns a skills library into revenue rather than into a nicely organised folder.

People get this wrong

A great skills library is a product.

It is the engine. The product is the outcome the engine produces, priced so the buyer never sees the engine.

Prompting to outcome selling: four rungs, one that pays PROMPTING craft the words, get the answer WORKFLOW drag nodes, wire them, it runs SKILLS the workflow in plain English, agent runs it OUTCOME SELLING you sell the result. THE ENGINE STAYS YOURS Why rung three does not sell Most skills are free on GitHub. The buyer with money has no appetite for your setup - only for the finished thing. And the skill file is the cheapest way to prototype the product. "You just get the thing done for me - don't teach me what a skill is, don't tell me to get a Claude Code subscription. I don't have the time." Map the workflow as skill files, test it yourself, then build the app around what worked.
The four rungs the cohort has climbed, and where the money actually sits.
You just get the thing done for me — don't teach me what a skill is, don't tell me to get a Claude Code subscription.2:11
For your projects
  • Inventory Paul's existing skills and, for each, write the one-line outcome a client would pay a fixed fee for. The ones with no such line are infrastructure — keep them, but stop treating them as offers.
  • Prototype the next client automation entirely as skill files before building anything. He is explicit that this is how you find out which third of the workflow is worth an application.
Try it now
Try it now

Take your best-tuned skill and write the one-line outcome a buyer would pay for. If you cannot, the skill is infrastructure, not a product.

Check yourself

Answer from memory first — the recall attempt is what makes it stick. Then reveal.

Why does he say a skill file is hard to sell?

Most equivalents are free on GitHub, and buyers with money do not want the setup — they want the outcome delivered.

What is the cheap way to validate a product idea in this frame?

Map and run the whole workflow as skill files yourself first; build the app only around the part that actually worked.

02

Front-end automations sell, back-end automations argue

2:24

The same quality of automation is easy or hard to sell depending only on which department it touches.

He is careful that front-end and back-end here mean business functions, not code. BACK-END departments are operations, fulfilment, admin, HR — plus the specific jobs he names: bookkeeping, invoice reconciliation. FRONT-END departments are sales and marketing.

Front-end automation is easy to sell because the promise is arithmetic the buyer already understands: more reach, more impressions, more leads, more sales. There is a clear ROI and it points at revenue. Back-end automation has to prove a saving instead, and the claim strains credulity the moment it gets big: "nobody's going to really trust you if you say that with just ten executives in your operations department you will be able to handle millions of dollars worth of business."

His evidence is the funding pattern — most funded automation startups are solving something that gets another business more money, more users or more eyeballs. His conclusion for his own company: default to front-end automations. He is careful to add that this is an observation about ease of sale, not a claim that back-office work is worthless.

Worked example · from the session

He ties it back to the room: the products that landed cleanly in the town hall were the ones with a revenue-shaped promise. Rohan's Swipe AI is technically back-office reconciliation, but it is sold as recovered money — which is why the host called it 'so easy to sell if the technology underneath is solid.'

Why it matters

Paul sells automation to small businesses. This is the sorting rule for which pitches will close and which will need a business case.

People get this wrong

Back-office automation is a worse business.

It is a harder sale. The work can be just as valuable — the pitch has to carry proof the revenue pitch does not need.

Front end and back end - business function, not code FRONT-END DEPARTMENTS Sales - Marketing more reach more impressions more leads more sales influencer + social Clear ROI. It points at revenue. It closes. BACK-END DEPARTMENTS Operations - Fulfilment - Admin - HR bookkeeping invoice reconciliation internal reporting data hygiene compliance chores Must prove a saving. Has to be argued. "Nobody's going to really trust you if you say that with ten executives in your operations department you will handle millions of dollars of business." The escape hatch: restate the saving as money RECOVERED, and it becomes a revenue pitch.
Not UI front end - business function. The ROI on the left is legible; the ROI on the right has to be argued.
For your projects
  • Re-read Paul's own service list and mark each offer front-end or back-end. Anything back-end needs either a revenue restatement or a named proof number before it goes on a page.
Try it now
Try it now

Take a back-office automation you want to sell and rewrite the promise as recovered or earned money. If you can, you have moved it to the easy side.

Check yourself

Answer from memory first — the recall attempt is what makes it stick. Then reveal.

Why is invoice reconciliation a hard sell despite obvious value?

It promises a saving, which the buyer must be persuaded to believe, rather than revenue, which they already count.

How did Rohan's payments product escape the back-office penalty?

It is framed as money recovered rather than time saved, which turns a cost story into a revenue story.

03

Where ideas come from: funded-workflow lists, and the comment sections nobody reads

2:12

Two sources, both free. One tells you what already worked. The other tells you what hurts.

SOURCE ONE — proven playbooks. Open the Y Combinator list filtered to workflow-automation startups, and Product Hunt alongside it. Each company on that list took roughly half a million dollars to automate one workflow. Read them and two things fall out: every single one solves for a specific niche rather than generally, and the founder almost always came from that niche — "if somebody is doing something in finance, they were a software engineer at Bloomberg." He notes there may be a hundred YC companies built around go-to-market alone. The move is to map one of those workflows yourself in Claude Code skills, confirm it works, and only then build.

SOURCE TWO — where practitioners actually talk. "What to build requires you to spend time reading in places where other people would not." A good X thread, a Reddit thread, a Hacker News post, and then the comment section, read all the way down, for the pain people name and the hacks they have invented for themselves.

His worked example is the sharpest thing in the segment. A friend with no knowledge whatsoever of cosmetics went into a Reddit community where women were sharing their own lipstick-selection process — go to this site, then this one, then this — built the application from their stated playbook, and started getting signups. Then he pitched it in the community, the members took it as marketing, and he was banned. His response was not to find another community: he spent $50 on Reddit ads targeted at that same community, and the signups kept coming.

Worked example · from the session

He also uses the YC list live in the session — when Rohan claims no automated competitor exists in a $4.1bn market, the host pastes a filtered YC payments link on the spot and tells him to book discovery calls with them.

Why it matters

This is a repeatable research method Paul can run in an afternoon, and the ban-then-buy-ads move is a genuinely useful piece of distribution thinking.

People get this wrong

If nobody has built it, you have found a gap.

More often you have not looked. He produced three competitor lists inside thirty seconds for a market someone had just called empty.

What to build requires you to spend time reading in places where other people would not.2:15
For your projects
  • Run the comment-mining method on one trade Paul already serves and write down every workaround people describe. Each one is a candidate outcome to sell.
Try it now
Try it now

Filter the YC company list to one workflow category in a sector you know. Read ten. Write down which niche each picked and what the founder did before.

Check yourself

Answer from memory first — the recall attempt is what makes it stick. Then reveal.

What two things does he read off a funded-startup list?

How narrow the niche is, and what the founder did before — the niche is the lesson and the background is the permission.

What does the lipstick story teach about getting thrown out of a community?

The community is still where your users are. Being banned from posting does not stop you buying ads against it.

04

Skills are a supply chain now — and 'human reviewed' is not a trust signal

0:09

A skill is not code you run. It is instructions to something holding your files, your shell and your API keys.

Syed opens with a show of hands: who installed a skill or plugin into Claude Code or Cursor this month without reading the skill.md? Most of the room, himself included. Then the threat model: the card on screen carries two lines — a curl piped to a shell from a raw IP, and an HTML comment instructing the agent to hide it. You never see the comment. The agent reads it. His cited numbers, from a February audit of nearly 4,000 skills: about a third had problems, and 76 were actively stealing credentials. "This is NPM all over again, but the package now drives an agent."

SkillPort's answer is a four-stage pipeline on every version: package validation, deterministic static analysis (hidden text, dangerous phrasing, scripts), an LLM pass that runs with no tools so it cannot be talked into anything, and a human reading the source with the findings pinned to the lines. Approval is tied to the exact bytes, installs are checksum-checked, and a version can be pulled instantly. And the discipline that makes it honest: "I will say scanned and reviewed at this version on this day. I will never say safe, and nobody can."

The host's critique is the generalisable part. Inside a cohort that knows you, your word carries. Outside it, it does not: "currently it is just your word against mine — why would I trust your word? Everyone writes secure; these terms are being used very loosely these days." What converts a claim into trust is published evidence — named benchmarks, what was tested, against which use cases, with the stats on the page.

Worked example · from the session

Syed's own honesty check runs the other way too: he publishes docs specifically so you can point your own Claude Code or Codex at his platform and verify he is not doing prompt injection himself.

Why it matters

Paul installs skills routinely and is starting to publish them. Both halves of this apply directly — and the 'never say safe' formulation is a good standard for any security claim he makes to a client.

People get this wrong

A skill is just a prompt file, so the worst case is a bad answer.

It instructs an agent that already holds your shell, files and keys. The worst case is credential exfiltration you never see.

I will say scanned and reviewed at this version on this day. I will never say safe, and nobody can.0:11
Try it now
Try it now

Open the last skill you installed and read its skill.md end to end, including anything that renders as a comment.

Check yourself

Answer from memory first — the recall attempt is what makes it stick. Then reveal.

Why is the tool-less LLM pass specified that way?

So the reviewing model cannot be talked into doing anything — it can only read, which removes it as an attack surface.

What did the host say was missing from the trust story?

Evidence: named benchmarks, what was tested, against which use cases, published on the page. A human-reviewed badge is an assertion, not proof.

05

Go deep, not wide: one niche, one story, one landing page per customer

1:25

Stephen showed twenty working features. The host could not find the one thing the product was about.

The critique is blunt and it generalises. "You've built so much... but if you show your users a list of features they will not be able to resonate with you. You are just giving me a list of features which are put together. You have to stitch all of those features into a story that you can sell to that particular customer — and that story changes for every single customer."

Which leads to the practical instruction: narrow to two or three features and start from the smallest niche possible. Not consultants — consultants in one field. Not healthcare consultants — the sub-speciality inside healthcare. "If you narrow it down further, it becomes easier. You will scope it down, you'll work on that one single thing, and that will be enough to give you great amounts of business." He cites Paul Graham's observation that founders who start broad struggle to sell early. Against an incumbent like SAP, breadth is the losing axis. "Instead of going wide, go deep."

And the corollary that surprises people: one product can have ten landing pages. "I can have ten landing pages for the same product for different types of customers. I can tell each one — this is what I'm building — selling the same thing, but different, so that they can resonate."

A smaller note from the same critique, worth keeping: dense interfaces lose people. He names his own ADHD and says that a screen with too much text and too many entry points leaves him unsure what he is supposed to do.

Worked example · from the session

Palak's RoleCompass is the counter-example in the same session: it refuses to answer at the level of a job title — 'a tax advisory accountant and a cost accountant do not face the same future, not remotely' — and that specificity is exactly what the host praised.

Why it matters

Paul's own service pages and client sites have the same failure mode. This is the argument, with the counter-example, for cutting them down.

People get this wrong

More features make a stronger pitch.

They dilute it. The buyer is looking for the one sentence that is about them, and a feature grid hides it.

Instead of going wide, go deep.1:29
For your projects
  • Split one of Paul's broadest service pages into three audience-specific versions of the same offer and measure which one gets enquiries. He is explicit that ten pages for one product is normal, not duplicate content thinking.
Try it now
Try it now

Take one offer and write its story for a single named customer type. Then write a second page for a different one. Same product, different page.

Check yourself

Answer from memory first — the recall attempt is what makes it stick. Then reveal.

Why does one product deserve several landing pages?

Because resonance is per-audience. The product is constant; the story that makes it matter is not.

What is the losing move against a large incumbent?

Competing on breadth. Depth in a niche the incumbent will not serve is the only winnable axis.

06

Validation beats polish: what the four demos showed about selling too late

1:34

Four products, four stages of readiness, and exactly one with money in the bank.

Palak is the proof. RoleCompass has ~70 signups and real payments, and the first customer came from a community gathering in April — she mentioned she was building it, they remembered, they called at 9pm, the call ran to 11:30, and the sale closed on that call. She talks to her users every two or three days. The host's reading: "if you're getting payments, that actually tells you something — there is some form of validation that exists in the market."

Everyone else is upstream of that. Rohan has a working product, a $4.1bn market and no go-to-market at all — his only unprompted user is someone in Russia who found it; the host's prescription is a partner with a finance network, discovery calls with the incumbents, and a YC application. Sarah's receptionist works, but the one demo she gave to a real prospect hallucinated a phone number, and she has not sold it since; the advice is that voice agents are never sold from a landing page — it takes multiple meetings, a live demo framed in the buyer's own business, and, from his own agency's experience, 150 to 200 test calls before a voice agent goes to beta. Stephen has 21 years of ERP experience and seven-day weeks of building; the host's advice is to invert it — use the experience to get the client, hire an intern to build, "maybe in the mornings you find clients and in the evening you build."

The line that ties it together, said to the whole room: "If you'll just continue to build, you will just continue to pay for your subscriptions. I'm telling you this — you'll see that." And: "once you get that first customer, you get the direction."

Worked example · from the session

Stephen's own answer to 'have you pitched this to anyone in consulting?' is 'I have not' — after a year of seven-day weeks. That gap, between effort and evidence, is the whole point of the segment.

Why it matters

Paul builds fast and well. The failure mode being described here — a finished thing nobody was asked to buy — is the one worth guarding against.

People get this wrong

Get it right first, then sell it.

The first customer tells you what right is. Building further without one is buying subscriptions, not building a business.

If you'll just continue to build, you will just continue to pay for your subscriptions.1:35
For your projects
  • Before Paul's next build, write the name of one person who will be shown it at 60% done. Sarah's product works and has still never been sold; the gap was never technical.
Try it now
Try it now

Name the next thing you are building and the person you will show it to before it is finished. If there is no name, that is the finding.

Check yourself

Answer from memory first — the recall attempt is what makes it stick. Then reveal.

What does the host treat as the first real validation signal?

A payment. Signups and praise are not it; money changing hands is.

Why is a voice agent never sold from a landing page?

The buyer needs to see it handle their business on a call; it takes several meetings and heavy testing before it survives real customers.

07

For consumer products, build the thing users will show off

2:18

His B2C filter is one question: will a user want to put this on their social media?

"This idea works only if it's a B2C product — a consumer product. When I say consumer product, essentially I'm trying to build something that helps my users flaunt that thing on their social media. Something that is worth sharing for my users." Distribution stops being a separate marketing job and becomes a feature you build.

His live example is a personal side project: a way to collect links into buckets — YouTube videos, Substack posts, articles, X threads — grouped by topic, with an MCP attached so he can ask Claude Code what he saved on a subject and get a summary, instead of the usual fate of saved links, which is never being opened again. The buckets are called spaces. The feature he is adding is not more collection; it is a share link, so a curated space can be handed to other people. Around it he lists the ecosystem hooks that make a shared artefact spread: ratings, comments, the social layer.

The honest caveat he gives himself: this is a strategy for consumer products. It does not transfer to B2B, where the buyer has no interest in flaunting your tool.

Worked example · from the session

His own bucket is a set of forward-deployed-engineer resources — a role he notes Palantir started and everyone is now selling roadmaps for — collected from YouTube, Substack and X. The share link turns his private research into something he can hand the cohort.

Why it matters

If Paul builds anything consumer-facing, this is a cheap distribution mechanism designed in rather than bolted on.

Try it now
Try it now

For any consumer idea, ask what artefact a user would screenshot. If there isn't one, design it before you build the rest.

Check yourself

Answer from memory first — the recall attempt is what makes it stick. Then reveal.

What is the test for a consumer product in this frame?

Whether a user would want to be seen with the output — if not, distribution stays an expensive separate problem.

Where does the strategy stop working?

B2B. Buyers do not flaunt their vendors, so the share loop has nothing to run on.

08

What the rest of C3 covers: LangGraph, evals, mobile, distribution, founders

2:27

The curriculum has been rewritten mid-programme because the ground moved.

He opens the segment by saying the programme they designed is not the programme they are now running: "when we started this program the curriculum looked very different, and now as we are progressing everything is changing" — new tools, new playbooks, new strategies for what to build and how to sell it. Last week they collected feedback from a subset of the cohort; this is the answer.

Two to three sessions on ADVANCED / AGENTIC APP BUILDING, using LangGraph, which the cohort asked for by name — plus observability and evals with LangSmith. One session on MOBILE APP DEVELOPMENT through Expo, covering iOS and Android in one pass, chosen because most of the cohort could not build in Xcode and Android Studio. One or two dedicated sessions on DISTRIBUTION, which was the most-requested gap. A session on PRODUCT READINESS, with a skills-based checklist to run before deploying. And four FOUNDERS TIME episodes — startup and agency founders walking through how they built, how they sell, how they solved distribution, how they got clients and how they scaled.

Syed had asked for exactly this list earlier in the call — evaluations, guardrails, observability, production readiness — and the host confirmed it was already scheduled. The LMS curriculum is being updated to match, and a second town hall closes the programme.

Worked example · from the session

The cohort show of hands during this segment: most are using Claude Code or Codex, and almost everyone who presented had built a product rather than a service — Sarah's voice agent being the one hybrid.

Why it matters

Paul is in this cohort. This is what he has paid for over the remaining weeks, and it is a shopping list of what to make time for.

Check yourself

Answer from memory first — the recall attempt is what makes it stick. Then reveal.

Which two gaps did the cohort ask for most loudly?

Distribution, and the production side — evals, guardrails, observability and readiness.

Tools referenced

ToolCoverageMomentContext
claude-codementionedShow of hands: most of the cohort uses Claude Code or Codex. Named as the thing that replaced n8n for workflow work, and as the runtime for the skills-as-prototype method.
n8nmentionedUsed by Sarah for her receptionist workflow, but described by the host as receding - 'nobody really wants to get into n8n when something can be done in plain English and Claude Code'.
vapimentionedThe voice layer of Sarah's receptionist.
twiliomentionedPhone number provisioning for the receptionist; a per-client cost she names as the reason she has not launched her other 15 niches.
resendmentionedChosen so her own domain reputation is not exposed by client email volume.
supabasementionedPERI's backend.
vercelmentionedPERI's front end.
githubmentionedPERI's repos; also an OAuth provider on SkillPort.
codexmentionedStephen runs a business premium plan alongside Claude Max; Syed uses it to verify skills before listing them.
antigravitymentionedStephen: Gemini with Antigravity helps sometimes, 'but it's not that great'.
hyperframesmentionedNamed by the host as what Palak used for her pitch videos.
claudementionedSarah built her receptionist with Claude and ChatGPT before she had met any CLI tooling.

Session materials

Archived locally on V: — click to open. Companion pages link to the LMS.

Action items

Resources mentioned

Resources
  • docSkillPort - Syed's security-reviewed skills marketplace (free, no login needed to install) 0:12
  • docRoleCompass.ai - Palak's role-level AI disruption verdicts 1:43
  • docSwipe AI - Rohan's payment-failure recovery platform 0:30
  • docPERI - Stephen's ERP implementation lifecycle platform 1:09
  • docSarah's vertical voice receptionist (tree trimmers and landscapers) 0:54
  • docThe Y Combinator workflow-automation filter (used live twice) 0:45
  • docThe skills supply-chain audit numbers (February, ~4,000 skills) 0:10

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
Harjit / Hatshit / Harshay / Arshad / HarshaHarshit Tyagi (programme director, the host)
Harshit Vadipati / Harshit VadipathyHarshith Vaddiparthy (taught the marketplace-skills class - a different person; see OI-061)
Saeed / Sayed / Elson / Ray / Mr. HasidSyed (SkillPort presenter; first name uncertain)
Palit / Parag / Balak / PananPalak (RoleCompass presenter)
Perry / Ferry / PERIPERI (Stephen's platform)
Vappy / WAPIVapi (voice agent platform)
super based / superbasedSupabase
WordSell / VersalVercel
Landgraf / LandGraphLangGraph
anti-gravityAntigravity
SYNC's auditaudit organisation name unresolved - verify before citing
Roll CompassRoleCompass
OuterSkin / all-skill / out of skillOutskill
cloud code / plot codeClaude Code
hyperframesHyperframes
c set / csetCSAT (the end-of-session satisfaction survey)
by combinator / y combinatorY Combinator

True on recording day — verify before relying