Hi everyone
Sharing a follow-up thought from the Barie team, building on what we discussed earlier around reliability-first AI.

As we ve gone deeper into agent design, one thing has become very clear: most failures don t come from bad models. They come from fragile systems around the model.

Context leaks.
Assumptions pile up.
Tools execute before understanding is complete.

In many agent setups today, the model is asked to reason, decide, and act in one tight loop. That s fast, but it s also where things quietly go wrong. Small misunderstandings compound into confident but incorrect actions.

Hey Product Hunt
I wanted to share a bit of what we ve been working on and get early thoughts from this community.

I m one of the makers behind Barie.ai. The problem that pushed us to build it is pretty simple but painful:

Most AI tools are great at fast answers.
They re not great at continuity.

In real work, context matters. Decisions stack. Assumptions change. And when an AI forgets earlier reasoning or invents missing pieces, things quietly break.

Hi everyone, glad to finally introduce myself.

I ve been working in and around artificial intelligence for a while now, mostly focused on one question that keeps bothering me:
Why does AI sound confident but fall apart the moment things get complex?

I m one of the makers behind Barie.ai, where we re exploring AI as a system that can reason, remember, and execute across steps instead of just replying fast. Less chatbot energy, more dependable teammate.

What pulled me into this space wasn t hype or demos, but the gaps:

Hi Product Hunt community!

I m part of the team behind Barie.ai and we re about to launch soon.

We built Barie to be a general AI agent focused on real-world reliability. While most AI tools are designed to generate fast answers, Barie is built with one simple rule: if it can t verify something, it doesn t guess.

Barie specializes in deep research, source-backed outputs, and multi-step execution, designed to connect directly with the tools people already use. It s AI you can trust to perform tasks, not just make suggestions.

Hey Product Hunters

I m Hanzlah, and I ve been deeply involved with artificial intelligence for quite a while. My focus has always been on the real-world reliability of AI, how we make it work for people in practical ways without the uncertainty that often comes with flashy AI.

Right now, I m part of the team building Barie.ai. We re developing an AI agent that goes beyond generating answers, it actually performs tasks within real workflows, all while ensuring that the outputs are verified and reliable. We re focusing on building AI that does the work, not just provides suggestions.

At Barie, we believe that AI should act with intent and precision. That s why we re pushing the boundaries with connectors, so Barie doesn t just analyze data, but can execute tasks inside the apps people already use.

Hey Product Hunt

We re getting close to launching Barie.ai, a general AI agent built with a simple constraint: if something can t be verified, it shouldn t be made up.

Barie focuses on deep research, source-backed outputs, and multi-step execution, with a strong emphasis on minimizing hallucinations. Instead of stopping at answers, it connects with real tools through connectors so research and reasoning can turn into actual work.

Hi Product Hunt

I ve been working closely with artificial intelligence for a while now, mostly around how AI reasons, how it makes decisions, and where it tends to go wrong. The more powerful AI becomes, the more important reliability and trust start to matter. Fast answers are easy. Correct, verifiable ones are not.

That s what I m currently working on with Barie.ai.

I m part of the team building Barie, a general AI agent designed for deep research, source-backed outputs, and multi-step execution with a strong focus on minimizing hallucinations. Instead of treating AI as a chat box, we re focused on making it a dependable system people can use for real work.

Quick heads up, Product Hunt

We re getting ready to launch Barie.ai, a general AI agent built with a different rule than most: if it can t verify something, it doesn t guess.

Barie is designed for deep research, source-backed answers, and multi-step execution across real tools through connectors. Less confident nonsense. More clarity you can actually act on.

We re putting the final touches on it and will be launching soon here on Product Hunt. If you care about trustworthy AI, real execution, and tools that work beyond demos, this one s worth keeping an eye on.

Hi Hunters
I m Hanzlah.

Over the last few years, while using and testing different AI tools, one issue kept showing up again and again: AI is getting faster and more impressive, but not always more reliable. Confident answers often fall apart when you try to verify them, which becomes a real problem when AI is used for research, planning, or decision-making.

That frustration is why I m building Barie.ai.

Barie is a general AI agent designed to research deeply, verify information with sources, and handle multi-step tasks with a strong focus on minimizing hallucinations. The goal is simple: build AI people can actually trust, not just be impressed by.

Hi everyone, I m part of the team at Barie.ai. I wanted to share a bit about what we re working on and the thinking behind it.

As AI adoption grows, one issue keeps showing up across tools: confidently incorrect outputs. For casual use, that s annoying. For research, planning, or decision-making, it becomes a real risk. At Barie, we started with a simple question: what would AI look like if trust was the primary constraint, not speed or flair?

Barie is being built as a general AI agent that focuses on deep research, source-backed answers, and multi-step task execution, with a strong emphasis on minimizing hallucinations. We re designing systems that verify information, expose reasoning through citations, and prioritize correctness over instant responses.

Another core part of Barie is connectors. Instead of working in isolation, Barie can connect to the tools and apps people already use. Once connected, users can ask Barie to research, reason, and then perform actions directly within those apps. The idea is to move from AI that answers to AI that reliably executes, while keeping humans in control.

Over the last year, AI tools have become incredibly powerful, but also increasingly unreliable. I ve seen tools confidently generate answers that sound right but fall apart the moment you try to verify them. That s frustrating for casual use, but risky when AI is used for research, planning, or real decisions.

That frustration is what led us to build Barie.ai.

Instead of optimizing for flashy responses, we focused on something less exciting but far more important: trust. Barie is designed to research deeply, verify information, cite sources, and execute multi-step tasks while actively minimizing hallucinations. The goal isn t to replace humans, but to support them with outputs people can actually rely on.

One thing we realized early on: trustworthy AI shouldn t stop at answers. it should take action. That s where Barie Connectors come in. Barie can connect with the apps and tools you already use, and once connected, you can perform real tasks inside those apps through Barie. Whether it s researching information, organizing data, or executing workflows across tools, Barie acts as a reliable layer that thinks, verifies, and then executes.

We just shipped multi-provider support in @Mnexium AI so you can change LLMs without resetting conversations, user context or memories.

The problem

When teams switch providers, they usually lose everything:

I think the biggest AI boom was in 2023-2024, but only now have I noticed improvements that have positively helped many businesses.

If I had to name three things that have had a very positive impact on business, they are:

• Improved image creation using GPT Chat

• Realistic videos through AI, where costs are reduced by hundreds, sometimes thousands of dollars (production video agency vs. a few custom prompts)

• "vibe coding" tools that show me a visual and I can reverse query and learn why the code is written in such a way that I got a certain result.

Teams aren t just adding AI into existing workflows.
They re reshaping the workflows themselves with the AI agent in the loop.

Steps get removed.
Objectives become clearer.
Old constraints disappear.
Processes reorganize around what the system can now do natively.

The real productivity gain isn t automation.
It s rethinking the architecture entirely.

Curious to hear from this crowd:
What s one workflow you rebuilt because AI made the old version irrelevant?

Hi Product Hunt community, I m Gohar Sultan Shah.

Founder at One Call a platform connecting people with everything around them using artificial intelligence. I m currently based between London and Lahore, working to solve a problem that 5 million people search for every day: near me .

My journey started in 2001 as a 3D animator, then moved through software engineering, broadcast tech, and leading digital initiatives like News channels, developing games, web infrastructure.

I love designing products that make sense and help people.

I m currently working on SentiSnap, a platform that combines simplicity, design, and artificial intelligence to help people easily create surveys and understand feedback.

I m glad to be part of the Product Hunt community. I enjoy sharing my experiences and thoughts in the forums, and I m also grateful for the insights and experiences of other makers. It s truly inspiring.

The AI researchers at Andon Labs, the people who gave Anthropic Claude an office vending machine to run, and hilarity ensued, have published the results of a new AI experiment.

They wanted to see if LLMs were technically capable of functioning as a robot s brain, that is, connecting their thinking (textual decision-making) with real sensors and movement.

Yesterday, Meta announced that they have released a new collection of AI models, Llama 4, in its Llama family.

(It consists of Llama 4 Scout, Llama 4 Maverick, and Llama 4 Behemoth.)

Historically, Open AI with its ChatGPT has been on the market for the longest period.

There are so many new AI agent platforms ( @Wordware @Lindy @CrewAI @zapier and so on) that I'm finding myself curious how everyone is using them.

What AI agents are you using in production? What do they do? Are they working and reliable? What would make them better? Are they replacing roles? Augmenting existing ones?

With AI agents and assistants are becoming more advanced, we're seeing them handle everything from scheduling meetings to managing entire workflows.

But here s the big question would you fully trust an AI to run tasks autonomously, or would you prefer keeping an eye on things just in case?