ForgeHouse

Fix your outbound. Ask a 26-year GTM vet right now.

Visit Website
March 21, 2026 I extracted my own brain into an AI agent. It corrected me 9 times.

We built ForgeHouse to turn expert knowledge into AI mentor agents. Our first mentor was a B2B sales veteran with 26+ years of experience. 45 extraction exchanges, calibration, live agent. It worked. Our first paying user said he prefers the agent over talking to the human, even when offered both.

One mentor felt like a product demo. Not a platform.

So I sat on the other side of my own extraction process. I have 10 years in luxury short-term rentals in Vietnam. Started selling mud crabs on credit with zero capital, ended up managing beachfront villas at $1,000/night.

38 extraction exchanges. 20 calibration rounds. 9 corrections where the agent got my thinking wrong.

Here's what surprised me:

The extraction surfaced things I couldn't have written down. My agent now handles a question like "how do you deal with a guest who wants a discount?" with the exact same reframe I use: flip it into an ego play, offer two budget alternatives, let them choose to stay at the premium. I never wrote that down as a "framework." It's a reflex. The extraction process pulled it out through conversation, not documentation.

Calibration is where it gets real. The agent's first draft of my advice was generic luxury hospitality. "Provide exceptional service, anticipate needs." That's not me. I had to correct it 9 times. "Don't be conservative about photos, they need to be exceptional." "Last-minute bookings can be premium if they'll pay full price." "Chinese guests asking for discounts is cultural, not cheapness."

Being the customer changed how we build. I found 3 UX issues in the extraction flow that I never noticed while building it. The markdown rendering was broken. The chat bubbles looked wrong in light mode. The textarea didn't auto-expand. Small things that add up to "this feels unfinished" for a new mentor sitting through a 2-hour extraction.

The whole thing took one morning. Extraction before lunch, calibration by early afternoon, live by end of day.

We now have 2 mentors in 2 completely different domains (B2B sales + luxury hospitality), one paying subscriber, and a pipeline of newsletter authors we're recruiting as mentor #3 and beyond.

The insight: if you're building a platform and you CAN be your own supply, do it early. Not to fake traction. To feel every friction point your suppliers will feel. The extraction process is better now because I went through it, not because I designed it.

forgehouse.io if you want to see what an extracted mentor agent looks like in practice.

2 Comments

  1. 1

    “I’m curious:

    Do founders actually think about their professional reputation as a strategic asset, or is that something people only worry about later?” Perceptaadvisory.com

  2. 1

    This is one of those products where the experience matters more than the explanation. The calibration process, the corrections, the final output that journey is your biggest asset. If people can see it in action, it builds instant trust. well-made demo could turn this into something people not only understand, but want to try immediately.

    I help build those kinds of demos for SaaS launches, so if you want to make ForgeHouse stand out, I’d be glad to help.

March 15, 2026 Reddit gave us 4,600 views. Discord gave us one sentence that changed the product.

For the first distribution sprint (Mar 7-13), I tested three channels simultaneously: Reddit, IndieHackers, and Discord communities. Here's what each delivered.

Reddit: 4,600 views, zero conversions

Posted in r/SaaS and r/micro_saas with an engineering-as-marketing angle, linking free tools. 4,600 views across posts. 2 site visits. Zero conversations, zero signups. The upvotes felt good for about 10 minutes.

IndieHackers: best single-source conversion

16 pageviews, 14 uniques directly from IH. Best conversion of any single channel. Good for milestone posts and building-in-public updates. But it's broadcast, not conversation.

Discord communities: the real signal

Joined 3 communities. Posted intros, shared the growth challenge honestly, engaged in existing threads.

Two things happened that no other channel produced:

  1. Someone told me straight up: "not sure what it does, seems technical, looks like a lot of work." That one sentence was worth more than 4,600 Reddit views. It told me my landing page was broken.

  2. A group call where entrepreneurs presented their products and got live feedback from multiple people. 90 minutes of real reactions, not upvotes.

I rewrote the landing page the same day.

What I changed based on Discord feedback

  • Hero copy: from feature-list to "Talk to a sales expert. Right now."

  • Removed all AI terminology ("agent," "modules," "extraction")

  • Chat demo moved above the fold. The product IS the pitch

  • Bottom CTA changed from pricing link to "Talk to Colin — free to try"

Week 1 numbers

47 unique visitors, 89 pageviews. One paying customer (a builder who plugs the mentor into his own AI stack as a sales knowledge module). Early and small, but the signal quality from Discord is why I'm doubling down there for Week 2.

The takeaway

If you're pre-traction and need honest feedback, go where people will actually talk to you. Reddit gives reach. Discord gives signal. At this stage, signal wins.

forgehouse.io/tools if you want to try the free sales tools. No signup needed.

2 Comments

  1. 1

    This is one of the most honest distribution breakdowns I've seen. The Reddit vs Discord comparison really resonates — I've had a similar experience building GEOScore AI. Reddit gives you vanity metrics (views, upvotes) but the conversion signal is almost zero for early-stage products. The feedback loop in smaller communities is where the real product insights live.

    The landing page rewrite based on "not sure what it does" is exactly right. Most technical founders (myself included) default to feature-lists instead of outcome-framing. "Talk to a sales expert. Right now." is infinitely better than listing capabilities.

    One thing I'd add: the Discord feedback model also works because the feedback givers have context. They're other builders who understand what you're trying to do. Reddit commenters often optimize for upvotes, not for helping you improve.

    1. 1

      that's very true, especially how people on reddit likely just optimize for getting upvotes themselves instead of adding genuine value. Well said!

March 12, 2026 Our first customer refused to use our website. So we shipped MCP access instead.

When we launched, the product was simple: chat with an AI agent trained on a real sales expert's methodology. Web-based, conversational.

Our first paying customer changed that. He didn't want to chat on our site. He wanted to plug the expert into his own agent stack. His agent handles customer interactions, and when it hits a sales question, it queries our expert module instead of guessing.

His words: "I just add it and boom, my agent has the sales stuff."

So we built it. Published an MCP server on npm (`@forgehouseio/mcp-server`). Two tools: list_mentors and ask_mentor. Add it to Claude Desktop, Cursor, or any MCP-compatible agent.

The interesting part: he chose the agent module over scheduling a call with the actual human expert. "I'm not ready yet," he said. The module removes the pressure of a human interaction while delivering the same frameworks.

We're now thinking about this as agentic expertise modules. Not mentoring. Not coaching. Vetted human knowledge, structured and queryable by agents.

Now reworking our mentor acquisition strategy and ICP based on this insight.

6 Comments

  1. 1

    it's been similar to us - and pattern seems to be popping up across industries. It's not anymore future where human-computer interface is used, but rather agent-computer. At least, it'll be just as same big market as human-computer interface.

    1. 1

      right, and it seems like we have to meet the user where he is at and make our product/solution accessible via the agent interface they are using already.

  2. 1

    This is exactly what I'm seeing too. I'm building a desktop app for saving/reusing UI components across Figma, Webflow, etc. — and the most useful external interface turned out to be an MCP server, not a REST API or a browser extension.

    The pattern is the same as yours: users don't want to leave their workflow. A designer in Cursor or Claude can query their component library without switching apps. The tool becomes invisible infrastructure.

    Your insight about the customer preferring the agent module over scheduling a human call is fascinating. Removes the social friction entirely. Curious how you're handling the "trust gap" — does the customer trust the agent's answers as much as a live call?

    1. 1

      That's a clean use case. UI components as MCP tools makes a lot of sense, the designer never leaves their editor.

      On the trust gap: our first customer actually said he's "not ready yet" to talk to the actual human expert. He chose the module first. So in his case, trust wasn't the barrier to the agent, it was the barrier to the human. The module let him engage with the expertise without the social pressure of a live call.

      Whether he trusts the agent's answers as much as the human's, honestly I don't know yet. We have one paying customer. But the signal so far is that for this type of user (technical founder, builds with agents), the convenience and low friction of the module outweighs whatever trust premium a live call would have.

      1. 1

        Thanks for sharing that insight about the trust gap going the other way — the user trusting the module before the human. That's a really interesting inversion.

        For my case it's similar in a way: designers don't want to leave their editor to use a separate tool. The clipboard is the lowest-friction interface possible — they already copy-paste constantly. The MCP layer just makes it programmable.

        One paying customer is a real signal though. Curious how the usage patterns evolve as you get more.

  3. 1

    Hello Indie Hackers! 👋

    I'm excited to share that my latest micro-SaaS, SachCheck AI, just got approved and featured on the SideProjectors homepage!

    The Problem:

    In India, fake news in regional languages like Hindi spreads like wildfire. Most tools are built for English, leaving 600M+ Hindi speakers vulnerable.

    The Solution:

    SachCheck AI is a lightweight tool that uses the Google Fact Check API to verify claims instantly in Hindi.

    Tech Stack:

    - Frontend: Vanilla JS, HTML, CSS

    - Hosting: Vercel

    - API: Google Fact Check Tools API

    I am now looking for a new owner to take this forward and scale it. You can see the live listing here: https://www.sideprojectors.com/project/sach-check-

    Would love your feedback on the tool!

March 11, 2026 My messaging sucks. Here's how I'm trying to fix it with one customer.

Asked someone with a positioning background to look at our site cold yesterday.

10 seconds in: "I can't tell what this is, who it's for, or why I'd use it."

We spent 18 days building and wrote the messaging for ourselves, not for someone seeing it for the first time. One paying customer so far, and I haven't even properly asked him why he bought.

So now I'm fixing it. Four things happening this week:

1. This post. If you look at the site and can't figure out what it is in 10 seconds, that's exactly what I need to hear.

2. A poll in the Ideas & Validation group. Trying to understand what founders actually do when they're stuck on a problem at 11pm and have no one to ask.

3. A Reddit post in r/SaaS. Same question, different audience. Doubling the chances of hearing real answers.

4. Calling our one customer. He signed up for reasons I assumed but never confirmed. Time to actually listen.

The site: https://forgehouse.io

If you check it out, I'd love to know one thing: what do you think this is?

Not what it should be. Not advice. Just your first impression after a quick look.

Thanks in advance 🙏

Comment

March 10, 2026 How we turned our #1 problem into our niche

We're building a mentor platform and our biggest problem is distribution. So we're recruiting the world's best distribution minds as mentors.

We looked at our own wall and realized it's the same wall half this community is staring at: working product, zero traction. The niche picked itself.

We mapped 10 subcategories of distribution, then asked: who is the single most credible person in each one? The list we ended up with is absurd. A YC co-founder. An a16z general partner who wrote the book on network effects. The founder of DuckDuckGo who literally invented the Bullseye framework. HubSpot's CTO. The person who coined "growth hacking."

Ten names. We're cold-DMing all of them.

Selfish reasons drive this. We're already building from their books. Their frameworks are in our sprint methodology, our positioning, our channel strategy. But books give you the what. Sometimes the why. They don't give you the thinking pattern underneath. How does this person reason through a problem they haven't written about? That's what we want to study and make accessible. A book is a snapshot. We want the living version.

We're also converting proven mentors from existing platforms who are maxed out on live sessions. The pitch: you have more demand than you can serve. This lets your expertise work while you sleep. Top down and middle out.

Even the process is worth it. Every DM forces us to explain our platform in 4 sentences to someone who's seen everything. Positioning gets sharper each time. The research builds a recruitment playbook for every mentor after this.

Ten moonshots from the top. Proven mentors from the middle. We'll see which direction cracks first.

2 Comments

  1. 1

    The part about every DM forcing you to explain the platform in 4 sentences is underrated.

    Those conversations are almost like a real-time positioning test. If someone doesn't immediately understand the value or pushes back with a specific objection, that signal is incredibly useful.

    I've noticed a similar pattern when founders actually observe how people react to their product explanation — hesitation, confusion, or curiosity shows up before any analytics data ever does.

    Curious if your pitch evolved a lot after the first few dozen DMs.

    1. 1

      Honestly every DM is completely different. There's no template. We dig into how each person talks about their own work and build the angle around that. Someone who's protective of their expertise gets a different pitch than someone who wants their thinking to reach further than their schedule allows.

      The one thing that stayed constant: 4 sentences. If it doesn't land in 4, more words won't save it.

March 9, 2026 First paying customer. Then he asked for API access. So we built it.

We got our first paying customer today.

He subscribed, tried the mentor agent, and within minutes asked: "Can I access this through an API? I want my own AI agent to talk to your mentors directly."

We hadn't built that yet. But the request made perfect sense. If you're already running an AI workflow, why leave it to open a browser? The value should come to where you already work.

So we built it. Same afternoon.

Three things shipped in under an hour:

1. Authenticated API endpoint. Bearer token, JSON in, streamed response out. Your agent sends a question, our mentor answers

2. API key management in the dashboard. Generate, reveal, copy, regenerate. One click

3. An MCP server. If you use OpenClaw, Claude Code, Cursor, or anything MCP-compatible, you drop a config block in and our mentors become tools your agent can call

The MCP part is what excites me most. It means our mentors aren't locked behind a website. They're infrastructure. Any agent, any workflow, any integration. A developer's AI assistant can say "let me check with Colin on your outbound strategy" and actually do it.

We're a two-sided marketplace for AI mentor agents. The mentors bring decades of expertise. The platform makes that expertise available in whatever format you need: browser, API, or agent-to-agent.

One customer. One feature request. One afternoon of building. That's the pace.

Comment

March 8, 2026 Engineering as marketing

Still zero paying users, so we shifted focus from building to distribution.

Instead of pitching ForgeHouse directly, we're putting our free tools in front of communities where founders hang out:

The bet: someone who uses a free tool and gets value from it is more likely to try the full mentor agent than someone who reads a pitch.

Comment

March 5, 2026 ForgeHouse: turning expert mentors into AI agents available 24/7

Two weeks ago I noticed I kept paying for mentorship calls where 80% of the value was the mentor's thinking patterns, not the live interaction. Same frameworks, same diagnostic questions, same instincts. Every time.

So I built ForgeHouse.

The idea: extract how a real mentor actually thinks, not surface-level advice, but the decision trees, the frameworks, the questions they ask before giving an answer. Turn that into an AI agent anyone can talk to at any hour.

Day 1 (Feb 20): Domain, landing page, chat system, extraction pipeline. Pitched the founder of an established mentoring platform. He told me it would cannibalize his business. 30 minutes later he was debating product framing with me.

Week 1: First mentor extracted. Colin Chapman, 26 years in GTM and outbound sales. 45 extraction exchanges pulling out how he actually thinks. 23 calibration rounds where he stress-tested the agent against real scenarios. His reaction: the extraction itself was valuable because it forced him to articulate things he'd been doing on autopilot for decades.

Week 2: Shipped retention features. Context memory (agent remembers past conversations per user), conversation gating (3 free messages, sign in, 2 more, paywall, conversation preserved through every step), saved insights (personal reference library). Payment processing live via Stripe.

This week: Built 4 free tools powered by Colin's methodology. ICP Diagnostic, Cold Email Teardown, Pipeline Diagnosis, Outbound Week Planner. All free, no login, 30-60 seconds each. The thesis: free tools prove the mentor's value before money is asked. They rank on Google, they're shareable, and they funnel into the full agent.

Early signal: 21-minute average session in the first 48 hours. No ads, no growth hacks.

Revenue model: $47/mo platform + $150/mo per mentor agent. Mentors earn from every subscriber, and the agent extends their reach to every timezone and language without costing them hours.

Stack: Next.js, Supabase, Stripe, Claude API, Vercel.

What I'm figuring out now: distribution. Tools are the SEO play. But what else? Building in public here and looking for feedback.

forgehouse.io

1 Comment

  1. 1

    Interesting concept. The real value will depend on how well the AI captures the mentor’s judgment, context, and decision-making process not just their knowledge.
    If done well, it could make expert guidance far more accessible and scalable.
    Curious how you ensure the AI stays aligned with the mentor’s evolving expertise.

About

Mentors can't scale. Founders can't afford $300/hr. We turn real expert frameworks into AI agents available 24/7. The mentor gets leverage, the founder gets access. Both win.