Marcel Folaron

Marcel Folaron

CoChatCoChat
Founding Engineer CoChat

Badges

Top 5 Launch
Top 5 Launch
Tastemaker
Tastemaker
Veteran
Veteran
Gone streaking
Gone streaking
View all badges

Maker History

  • CoChat
    CoChatOpenclaw for Teams that is secure, collaborative, autonomous
    Mar 2026
  • Leantime
    LeantimeOpen source project management system
  • 🎉
    Joined Product HuntDecember 6th, 2015

Forums

How does your team actually use AI day-to-day? (Not the pitch deck version)

I've been talking to a lot of early-stage SaaS teams about how they use AI internally (not the "we're AI-native" marketing version, but the real day-to-day).

What I keep hearing is:

  • Half the team is on ChatGPT, the other half uses Claude, nobody shares context

  • Prompts that work well live in someone's Notion doc (maybe)

  • There's no visibility into what the team is actually using AI for

  • Onboarding a new hire means "here's a $20/seat subscription, good luck"

We're building something in this space and I'm genuinely curious whether this matches what others are seeing, or if some teams have actually figured it out.

Marcel Folaron

23d ago

CoChat MCP – Let your team review what your coding agent is building

I built an MCP server that connects coding agents (Claude Code, Cursor, OpenCode, Codex) to a collaborative workspace where your team and other AI models can review what the agent is planning.

The problem: When Claude Code creates an implementation plan, it lives in your terminal session. Nobody else sees it until it becomes a PR. If you want GPT to check the architecture or a teammate to flag issues, you're copy-pasting between windows.

This MCP server fixes that.
When your agent creates a plan, it gets shared as a collaborative thread in CoChat. Engineers comment on it, other AI models review it, and you pull all the feedback back into your agent's context with one command. Decisions can be saved as project memories that persist across sessions and are searchable by anyone.

What it does:
Plans: Auto-shared as collaborative threads. Pull feedback back into your terminal. Cross-model review: Have GPT review your Claude plan, or vice versa.
Project memories: Semantic memory that persists across sessions, models, and people.
Ask: Query your project's knowledge base from the terminal.
Auto-scoping: Detects your project from git remote. No config needed. Setup is one command per agent. Auto-share behavior is configurable (off/plan/all).

Marcel Folaron

8yr ago

Awemama - Monthly Subscription Service for Baby Carriers

Awemama is made by babywearers for babywearers. We're caregivers that have benefited from babywearing in our lives and we all struggled to find the right carrier. We wanted to simplify the experience and make babywearing more accessible and affordable by offering a monthly subscription service tailored to your needs.

View more