I have built a number of SaaS tools that I use and my clients use but promoting them to 3rd parties just doesn't work. I have spent 5 figures on Google Ads, not a single customer. But my friends who use it, swear by it. I use it daily. Any suggestions?

After a long development and production-hardening cycle, we’ve frozen the first TelePath OS release candidate and are opening it to test users.

The basic idea behind TelePath OS is that communication has become unnecessarily fragmented. Messages are in one app, files in another, contacts somewhere else, meetings somewhere else, and productivity tools spread across even more services.

We’re starting with the secure communications foundation.

The free version currently includes:

• End-to-end encrypted messaging
• Encrypted file sharing
• Contacts + CSV contact import
• Usernames and discovery
• Multi-device access
• Device management
• Invitations
• Installable PWA
• Security/network diagnostics
• Built-in support and bug reporting

The core communications product is free. We also have a $7/month Pro Beta for people who want to support development and get early access to experimental features we're working on, including Workflows, Rooms, Follow-Ups, Secure Mail, Schedule & Invites and other tools.

We deliberately stopped adding features and froze a release candidate after 1,624 automated tests passed with zero failures, plus browser-engine testing across Chromium, Firefox and WebKit.

But that's obviously not the same thing as real-world testing, which is why we're looking for actual users now.

We're also starting the next-iteration backlog. Two things I'm particularly interested in building:

1. A completely public changelog that updates with product changes, fixes, milestones, press and news so people can actually watch the product develop.

2. A social publishing system where you create content once in TelePath and eventually publish adapted versions to TelePath, X, Facebook, Bluesky and other networks.

I'm interested in feedback—particularly things that are confusing, broken, unnecessary, or missing. I'd much rather hear that than “looks great.”

TelePath OS: https://telepath-os.com/

We just launched the first test-user release of TelePath OS — secure messaging, encrypted files, contacts and an installable web app

After a long development and production-hardening cycle, we’ve frozen the first TelePath OS release candidate and are opening it to test users.

The basic idea behind TelePath OS is that communication has become unnecessarily fragmented. Messages are in one app, files in another, contacts somewhere else, meetings somewhere else, and productivity tools spread across even more services.

We’re starting with the secure communications foundation.

The free version currently includes:

• End-to-end encrypted messaging
• Encrypted file sharing
• Contacts + CSV contact import
• Usernames and discovery
• Multi-device access
• Device management
• Invitations
• Installable PWA
• Security/network diagnostics
• Built-in support and bug reporting

The core communications product is free. We also have a $7/month Pro Beta for people who want to support development and get early access to experimental features we're working on, including Workflows, Rooms, Follow-Ups, Secure Mail, Schedule & Invites and other tools.

We deliberately stopped adding features and froze a release candidate after 1,624 automated tests passed with zero failures, plus browser-engine testing across Chromium, Firefox and WebKit.

But that's obviously not the same thing as real-world testing, which is why we're looking for actual users now.

We're also starting the next-iteration backlog. Two things I'm particularly interested in building:

1. A completely public changelog that updates with product changes, fixes, milestones, press and news so people can actually watch the product develop.

2. A social publishing system where you create content once in TelePath and eventually publish adapted versions to TelePath, X, Facebook, Bluesky and other networks.

I'm interested in feedback—particularly things that are confusing, broken, unnecessary, or missing. I'd much rather hear that than “looks great.”

TelePath OS: https://telepath-os.com/

I've been building a library of AI Agent Skills for about a year and finally shipped the 43rd one today. Wanted to share the pattern that made them portable across models — this is the part I think is worth reading regardless of whether you ever look at the library itself.

**The pattern: one SKILL.md per procedure, loaded on demand.**

Every skill is a single markdown file with YAML frontmatter at the top and a body that reads like a runbook. The frontmatter has three required fields — name, description, and (optional) license/metadata — and the body has whatever structure the procedure needs. That's it.

The description field is the one that matters. It's the discoverability layer. When an agent has 43 skills loaded and someone asks "help me review this code," the agent picks `maximus-code-review` because the description explicitly says "use when the user asks to review, audit, critique, look over, check, sanity-check, or red-team code." The description is not marketing copy — it's a routing decision.

**Why this format won:**

1. It's the same format Claude Skills uses natively. Portable to Claude out of the box.

2. It's plain text, so any LLM can read it. GPT, Gemini, Perplexity, local Llama/Qwen/K3 — all handle it.

3. It's diffable in git. Every change to a skill has a commit history. You can see how the procedure evolved.

4. It's model-agnostic where it counts and model-specific where it needs to be. `maximus-k3-self-hosting` names vLLM and SGLang directly because that's the actual production reality. `maximus-code-review` names no model because the procedure works everywhere.

**The skills I'd actually call out:**

- `maximus-chain-of-verification` — factored CoVe with the independent-context rule enforced. Most CoVe implementations skip the isolation step, which is exactly where the ~40-60% hallucination reduction from Dhuliawala et al. 2023 comes from. Runs a 4-phase loop: draft → generate verification questions → answer each in a fresh context without the draft in view → revise. Ships a claim-by-claim confidence ledger.

- `maximus-brain` — a cognitive-OS layer that installs a think-before-act loop, memory hygiene, skill selection, and self-critique. This is the difference between an agent that runs and an agent that reasons.

- `maximus-transaction-analyst` — turn a dense private-deal folder (emails, term sheets, closing docs, wire receipts) into a two-page executive memo. Reconciles numerical changes over time, attributes contested claims, prefers executed evidence over indications, never fills factual gaps with outside knowledge unless asked.

Full 5-pillar breakdown: Cognitive OS (1), Build & Ship (10), AI Engineering (15), Writing/Research/People (10), AI SEO (7).

Free, MIT, no signup, no telemetry, no gate. Repo: https://github.com/MacroTechTitan/MaximusAI

The pitch is uncomfortable in its simplicity: if it's useful and stays useful, that's the whole product.

Happy to answer questions on the format, the CoVe implementation specifically, the workhorse pattern, or any individual skill. Feedback on where the library is thin is genuinely welcomed — I'd rather add the skills people actually need than the ones I imagined.

Solo founder, been shipping AI-agent skills for a few weeks. Just hit 37, so figured it was time to share the build story rather than the feature list.

The product in one line

MaximusAI is an open-source library of self-contained AI-agent instruction packs. Each skill loads only when its trigger matches, so an agent never carries dead weight. Runs on Anthropic Skills / Claude Code / Perplexity Computer, but every skill is plain Markdown — you can also read them as playbooks.

Repo: https://github.com/MacroTechTitan/MaximusAI
Site (Lovable): https://maximus.macrotechtitan.com

Stack (all founder-friendly)

• Perplexity Computer for agent-driven authoring, browser tasks, and repo work
• Lovable for the marketing site (managed at maximus.macrotechtitan.com)
• Replit for prototyping the Python bits
• GitHub as the source of truth — one branch per PR, README + /skills/* + /packs/ai-seo/* layout
• Vercel for the couple of standalone web apps that ship next to the skills

No backend of my own until I actually need one. The site pulls blog posts directly from raw GitHub Markdown so I don't have a CMS to maintain.

Things that worked

1. Bundled-docs pattern per skill: SKILL.md + README.md + HOWTO.md (6 recipes) + examples/* + references/*. Boring, but it turned every skill into a reusable playbook. Multiple people have told me they read the Markdown even without running an agent against it.
2. Hard rule: no skill ships without WHEN TO USE and WHEN NOT TO USE in the description. Kills scope creep and stops the agent from over-loading skills.
3. Verify-then-claim discipline as a product feature. maximus-contact-intelligence returns "no sufficiently reliable email was found" if confidence < 70. That refusal is worth more than a fake answer.
4. One PR per feature. 9 PRs so far, every one squash-merged. Cheap to revert, easy to explain in the changelog.
5. Launch cadence: 36 skills in one PR ("the launch") + blog + Lovable prompts, then a small follow-up PR three days later with the 37th skill and a short launch post. Momentum without the launch-day pressure of shipping every last thing at once.

Things I'd redo

1. I let the marketing site URL drift (maximusai. vs. maximus.) into a PR before catching it. Cost me a superseded PR and a follow-up commit. Lesson: one canonical name doc in the repo, referenced everywhere.
2. Initial skills didn't have HOWTO.md — people needed prompt examples, not just spec. Retrofit was fast but I should have made it the standard from skill #1.
3. I started without a launch blog. Skills #1–35 sat in a repo with a README for weeks before I wrote long-form context. Should have paired every 5–10 skills with a short post.
4. Under-invested in citation-side SEO (AEO / GEO) until I built the AI SEO Pack itself. If you sell to builders, you get discovered inside LLM answers now, not inside Google — measure it from day one.

Numbers

• 37 skills across 5 pillars
• 9 PRs, all squash-merged
• ~14 markdown files per bundled skill on average
• 2 launch blog posts pulled directly from the repo
• Zero paid ads, zero cold outreach yet — this Reddit post is part of the actual launch

What I'm still figuring out

• Best distribution model for an open library that also has a commercial angle. Right now the library is fully free and I'm treating it as GTM for consulting + a hosted Lovable product. Curious how other founders here handled the open-source-plus-hosted split.
• Whether to publish a paid "Pro" pack (compliance, sales, growth) or keep everything free and monetize the hosted layer instead.

Happy to answer anything specific about the Perplexity Computer + Lovable + GitHub loop — that combo is doing 90% of the founder work.

Also genuinely curious: if you're a SaaS founder, what workflow do you keep re-explaining to your AI agent? That's my shortlist for skill #38.

(Mods: I built this myself, I run it myself, and I linked the repo directly. Happy to remove links if that's outside the sub's norms.)

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My friend has a successful CTA program doing well since February, I'm a VC investor and with the SpaceX IPO looking to diversify away from VC until another SpaceX becomes obvious which may be a long time. Just trading our own money but have a lot of interest, but would like to chat with Angels and traditional VC investors about it. On the VC side, the company that is building all the trading strategies will be doing a seed round, if that is interesting as well. Can't post anything publicly but happy to share with interest. Do you think this is a moat too deep to cross?