I built The Optimism Engine to explore something simple but powerful:
How can AI help people think more clearly - without sounding generic or robotic?
The Optimism Engine is designed to guide users through structured cognitive reflection. When someone shares a stressful thought, the system:
Identifies possible cognitive distortions
Maps the thought through progressive layers (Surface Trigger Emotion Core Belief)
Chooses a response mode (regulate, clarify, reframe, plan, or listen)
Returns a grounded, non-templated response
The goal isn t just therapy, It s structured thinking.
Instead of giving advice, it helps users examine their interpretation, underlying fear, and next actionable step.
It was an interesting exercise in combining psychology frameworks with deterministic system design.
Curious to keep building at the intersection of AI and human cognition.

Now live: https://optimism-engine.vercel.app/

We just launched our web-based, mobile-responsive app (Atmos App). We'd love feedback on what you like about other productivity apps you use (Notion, Tiimo, Motion...). Drop your comments on what you like and if you have time would love a look at my platform.
https://www.producthunt.com/prod...

Hello Product Hunt!

I m Joe Henzi, the creator of MLS Writer.

Awright, awright, sit down. We gotta tawk.
There s this narrative goin around you ve heard it, I ve heard it, ya mutha s heard it AI s gonna take all the jobs, we re all screwed, pack it up, game over.

Fuggedaboutit.

Here s what s actually happenin , and nobody wants to admit it: AI ain t the problem. How people are usin AI is the problem.
The Pattern Nobody s Talkin About

Look, there s a pattern in the narrative, and it goes like this:

Here's the problem: setting up AI agents like OpenClaw takes hours. Server configs, environment setup, networking, debugging... most people give up before they even start.

Summarize, suggest replies, send via Gmail. 10 hours/week saved. $0 subscriptions.
I built the NeuraClaw Email Agent because I was drowning in email.

50+ emails/day

2 hours reading and replying

Context switching destroyed my focus

We re letting users take over Votap
One thing that s been really cool lately? The emails.
People telling us what they like.
What they d change.
Which politicians we should add next.
I answer as many as I can, but it made me realize something:
If Votap is about public opinion
then the app itself should be shaped by public opinion too.
So in the next update (coming very soon), we re adding a proper feedback space directly inside the app.
You ll be able to:
Suggest features
Request politicians
Comment on ideas
Upvote what you want to see next
Other users can vote on suggestions too so we build what people actually care about.
Votap is a people platform first.
So the product should evolve with the people using it.
We want this live before our next bigger user acquisition push (aiming much higher next time ).
If you want to help shape it, download Votap from the App Store.
More tomorrow.

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).

Hey ProductHunt community!

I'm David, and I built SheerFit - an AI fitness coach that actually remembers you

Unlike generic fitness apps, SheerFit uses multi-agent AI with persistent memory to track your goals, injuries, and progress across every conversation. It's like having a personal trainer who never forgets what you told them last week.

Join Saposs Remote Sales Team $400/Month + Commissions

Company: Saposs
Location: Remote
Published: 30.01.2026