Pazi - Vibe code business operations
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Pazi is an AI team for that idea you keep coming back to — a book, a shop, an app, a skill you want to sell. Tell Pazi what you're trying to do and it builds a team of agents around your idea and starts making things happen: a website, first outreach, content, the next step. Every time you come back, something has moved. You stay in control; your team does the rest alongside you, one real step at a time. Like vibe coding but for business operations.
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AgentKey
Pythagora
@luki_notlowkey Exactly—that’s how we think about it too. Today, Pazi’s agents can use live web search and connect to external APIs when access is provided, using those signals for research, competitor monitoring, lead discovery, and planning. Making that market awareness increasingly continuous and reliable is a major part of where we’re taking Pazi.
Since Pazi is running similar business loops across many ideas, how do you think about transferring knowledge between users? For example, if one agent discovers that a particular outreach strategy consistently works, does that make every other agent smarter while still preserving user privacy?
Pythagora
@tarqiya_forgah Great question. Today there’s no knowledge transfer between users—or even between separate businesses on the same account. Each business and its agents are fully isolated, so strategies, results, and private context never carry over automatically. We may add opt-in sharing between businesses within one account, while cross-account transfers would most likely remain manual through export and import.
Congrats on the launch, Zvonimir. The "build vs. figure out what to actually do with the business" gap is something I run into constantly between managing a dealership and building a property management site. Honestly, half the challenge isn't the build itself, it's knowing which of the ten things I could do next actually moves the needle. Curious how Pazi decides what to prioritize when someone gives it a vague goal like "grow the business." Does it ask clarifying questions first or just start proposing a plan?
Pythagora
@andre_ajemian Thanks, Andre! It does both: the COO learns about your business and asks targeted questions when important context is missing, then turns a vague goal like “grow the business” into concrete opportunities. You choose which opportunity to pursue and can discuss the tradeoffs with your COO before the team starts executing.
For me personally, coding is the easiest part of building a product, but content writing or marketing-related tasks are really too difficult. They are often the parts that take me the most time. The appearance of Pazi just helped me out 🥳, thank you so much!!
Pythagora
Thank you, Gary! That’s exactly the gap we built Pazi for. Building the product is often only the beginning—content, marketing, and distribution can take far more time. We’re excited to see what your Pazi team helps you move forward 🥳
Congrats on the launch! "Every time you come back, something has moved" is the angle that sold me — most agent tools still just sit and wait for prompts. Curious how you balance agents acting autonomously vs. asking for approval on things like outreach?
Pythagora
@alex_tomilin Thanks, Alex! The main boundary is the opportunity itself: you choose what the team should pursue, then the agents work autonomously within that direction. They come back when they need access, credentials, or a decision that materially changes the plan. For outreach, you can shape the approach upfront and then let the team execute without approving every individual step.
@leon_ostrez got it, thanks for clarification!)
Pythagora
@alex_tomilin You are welcome! Let me know if you have any other questions
Love it! My app is built, ready to launch, but I feel very unsure on where to start, social media handlers are taken (including Product Hunt), videos recorded an paid for, iterations, PlayStore published, AppStore under review, yet I feel insecure... I will give this a go, so far exhausted my first 5k credits and intend to go for a bit more testing, thanks @zvonimir_sabljic1
Pythagora
@igor_torrealba Thanks, Igor! We’d love to hear how the next round of testing goes and what we can improve.
Hi @leon_ostrez , morning next day, got the subscription and have been working with it. Gave it a few documents and it is working on it, even gave it videos to process but this didn't work, so I replaced with Gemini described videos and it is working with it again :). Looks promising! I look forward to sharing more soon!
Well done! I like Pazi because it was super quick to get started and I could feed it data from Excel or connect it to my database. It didn't ask for a bunch of redundant information. I'm just getting started but I really liked how it identified the "core activation" moment. I was surprised how accurate it was.
Pythagora
@matthewoz101 Thanks, Matt! Great to hear it identified the core activation moment so quickly. Please keep us posted as you test it with more real workflows—we’d love your feedback.
the research-grounded-vs-guessed question above is the one that matters most imo - when Brave search and browser-use turn up conflicting pricing data for the same niche, does the agent reconcile the sources or just pick one and run with it?
Pythagora
@sabber_ahamed Good question. Today, this is handled by the agent’s reasoning rather than a deterministic reconciliation layer. It should compare sources, favor recent primary data, and surface meaningful conflicts instead of silently choosing one—but it isn’t foolproof, and we’re continuing to improve it.
The "flag low confidence before asking for approval" question above is the crux of this whole category, I think. I've been building something adjacent (an AI Chief of Staff for founders running more than one business) and the hardest part by far wasn't the automation, it was getting the system to admit when it's unsure instead of presenting a guess with the same confidence as a verified fact. Once I added explicit confidence grading instead of a single "done" state, trust from actual users went up more than any new capability did. Curious whether Pazi's course-correction messages to users distinguish "this failed" from "this succeeded but I'm not fully sure why," those feel like very different signals.
Pythagora
@stacywycof83995 You’re right—those are very different signals. Pazi can surface uncertainty and ask for direction, but we don’t yet attach a consistent confidence grade to every outcome. Separating “failed,” “succeeded with evidence,” and “succeeded but unsure why” is a useful framing. Thanks for sharing what improved trust in your own product.
Congrats @zvonimir_sabljic1 @liliiashamraion the launch! "Every time you come back, something has moved" is such a specific promise, most tools ask you to move things and call themselves productivity.
Pythagora
@vaishnavi_goel Thank you, Vaishnavi! That distinction is exactly what we care about—Pazi should create progress while you’re away, not give you another tool to manage. Really appreciate you noticing it!