AI today is reactive: it waits for your next prompt. YAGNI is proactive agent Teams you manage like people. Give a Team responsibilities and guardrails, review its work, and it earns autonomy through a track record you can read, while you keep the calls that matter. Paste your company's URL and YAGNI drafts your first team in seconds. You aren't gonna need more software. You need a team that gets better every week. Become a self-improving company.
The best teams I've been on ran on trust. It's what makes a team fast, and it's the hardest thing to build and the easiest to break. I've spent twelve years building and running teams, through two acquisitions, a Techstars batch, and orgs across healthcare, government, and startups big and small, B2C and B2B. That lesson held everywhere.
AI changed my own output more than any tool ever has. But it brought the trust problem back in a new form. More output means a worse signal-to-noise ratio, and the moment you try to put agents to work inside a business you hit a wall: where do you even start? Every tool assumes you'll be directive. Either you prompt each task ("do this thing"), or you wire up an if-this-then-that graph and hope you predicted the work correctly. That's not how anyone actually runs a team.
YAGNI takes the approach I learned managing people. You hand a Team a real slice of the business to own and give it the structure you'd give a new hire: Responsibilities, a Number it's measured on, Commitments with real deadlines, and Rhythms (its recurring work). Then you manage the early work closely. It drafts, you edit and approve, and every correction teaches it how you'd do it next time.
As its track record grows, it climbs a ladder you control: Training → Supervised → Autonomous. At the top it carries the routine, reversible work on its own, every action leaves a Receipt from the source system proving where things actually stand, and you stay in the loop for the calls that matter. Irreversible and high-risk actions stay behind your approval forever, at every level. That's a design commitment, not a model limitation.
Two things I decided early, because I'd want to know them as a buyer. First, it runs exclusively on open-weight models, so it's cheap enough to let Teams work continuously instead of sparingly. Second, it only uses first-party, official integrations, so your data is read where it lives, never sold, never used to train a model.
Humans and Teams work off the same context, and it all collates onto your Front Page, published as a Brief morning, midday, and evening. Monday's status meeting starts at the decisions instead of the recap. Dive into any work with a persistent chat sidebar to so that you always have the context to make the decision.
Who it's for: founders and operators who've become the bottleneck (the person everything routes through), and lean teams who want real leverage from agents without babysitting them.
What to try first, and don't sign up: go to https://yagni.app/build-your-team, paste your company's website, and about 30 seconds later YAGNI hands you a Brief with your first Teams already drafted: what it would own, which tools it would read, and what it would do in week one. Free, anonymous, no card. If the Team it drafts is wrong for your business, I genuinely want to hear why.
Paid plans start at $99/mo when you're ready to put a Team to work. Get 60% off ANY plan for 6 months with code YAGNIPH (60% because we can offer AT LEAST 60% savings of frontier models).
I'll be here all day. Ask me the hard ones: pricing, security, "isn't this just a wrapper," what happens when it screws up. I'd rather answer those in public than in a sales call.
Congrats on the launch! "Earns autonomy through a track record you can read" is such a sharp answer to the trust problem with agents. What does the actual track record look like day to day, is it a log you review, or does the team surface its own wins and misses to you proactively?
@jackcollinshq Upvoted YAGNI today. "Manage agents like humans" is a concept that's easy to under-explain, curious how the onboarding handles that.
@jackcollinshq looking forward to seeing more on Yagni! clearly very thoroughly thought out product! I tested out the "Build your team" feature myself and the results it produced are all relevant and I can already see how impactful this will be. Congrats on the launch!
the 3-similar-edits threshold is a smart way to avoid over-fitting to one correction, but what happens after a rule gets promoted and it turns out to be wrong two weeks later, like it was right for the cases you saw but breaks on an edge case nobody corrected yet. is there a way to see which rules are actually firing and roll one back, or do you have to notice the bad output first and trace it back to the rule that caused it?
Great work! How quickly do teams tend to become autonomous and once they're autonomous what are the checks in place for new work?
The Training → Supervised → Autonomous ladder, and especially counting edits-you-shipped as stronger evidence than a silent approval, is a sharper solution than most "trust the agent" products attempt. I've been circling the same problem from the read-only side rather than the action side: an AI Chief of Staff for founders running multiple businesses, where instead of earning autonomy to act, it earns the right to state something as fact vs. flag it as "Needs Review." Reversals eating earned trust is a great mechanic. Have you found any Team types where even Supervised-level trust turned out to be miscalibrated in hindsight, cases where the reversal signal came too late to prevent real damage?
The track record model is the right idea, and honestly a better answer than most agent products give to the trust question. But the hard part is measuring it. How do you actually know a run went well?
In support this is where it gets tricky for us. A customer who got a wrong answer usually does not complain, they just leave, or reopen the same thing a week later. So the easy signals (no complaint, ticket closed) look fine while the agent is quietly doing damage. The track record can read clean and still be wrong.
What signal do you use to decide a run succeeded? Human review of every run at the start, or something the agent grades itself on?
Congrats on the launch, @jackcollinshq — framing this as "manage like humans" instead of "hire an AI employee" genuinely reframes the category for me.
The piece I keep circling on is the Number each Team is measured on. Giving a Team a single metric to own is exactly how you'd brief a real hire, but it's also how you get Goodhart problems: a Sales Team measured on "qualified meetings/mo" has every incentive to quietly loosen what counts as qualified over time, and the Receipts would all still look clean. How do you keep a Team from optimizing the metric at the expense of the intent behind it, is there anything watching the gap between the Number climbing and the actual downstream outcome (closed deals, not just booked meetings)?
Congrats on the launch! Excited to see this in the wild. There's lots of "personal assistants" popping up, but figuring out how to manage context, guardrails and memory across an organization can be so tedious. I like that you can get started fast and train these teams over time.
@jackcollinshq@YAGNI I entered a website and clicked through the YAGNI workflow. It looks very sharp, impressive, and powerful. Great work, Jack & team!
I really like the idea that we need to 'recruit a team member' first, which sets the tone for the agent's role within the team.
The 3-step ladder feels more tangible than simply claiming that an all-star AI team will just work out.
the training→supervised→autonomous ladder is the honest part, most agent tools ship straight to autonomous. does a team ever drop back a rung, and why?
Obvious question: is YAGNI running launch day? Curious what you handed a Team and what you kept for yourself.
It's perfect step away from pathologically complex graph scripts that break the second a minor frontend changes. Awesome launch @jackcollinshq 🙌
"Don't hire an AI employee. Run a team." That positioning alone is fantastic. Congrats to the entire team on building something genuinely different. Excited to see where this goes 🚀
Really like this, @jackcollinshq, the "earn autonomy rule by rule" model is the part most agent tools get wrong. They expect you to trust the thing on day one, here it's earned off a track record instead. What was the hardest part of getting that Training -> Supervised -> Autonomous ladder right, and how do you keep reviews from sliding into rubber-stamping once a Team is approved for a lot of work?
Interesting approach. Does a team's autonomy score drop if it makes a costly mistake?
The Training → Supervised → Autonomous ladder is the part I keep thinking about — earning autonomy from a readable track record is such a thoughtful framing for trusting agents with real work.
A couple of gentle questions from an evals angle, if you have a moment. What signal actually promotes a Team up a rung — is it approval rate, and if so, how do you gently tell apart "approved because it was right" from "approved because I was busy and didn't look too closely"? I imagine that's a tricky line to draw.
And on the adversarial review step: does that reviewer run on the same open-weight model as the executor? Would love to understand how you keep it from leaning toward a rubber stamp when critic and author might share the same blind spots.
YAGNI launched on Product Hunt on July 15th, 2026 and earned 197 upvotes and 67 comments, placing #7 on the daily leaderboard. AI today is reactive: it waits for your next prompt. YAGNI is proactive agent Teams you manage like people. Give a Team responsibilities and guardrails, review its work, and it earns autonomy through a track record you can read, while you keep the calls that matter. Paste your company's URL and YAGNI drafts your first team in seconds. You aren't gonna need more software. You need a team that gets better every week. Become a self-improving company.
YAGNI was featured in SaaS (43.1k followers), Artificial Intelligence (473.7k followers) and Remote Work (4.1k followers) on Product Hunt. Together, these topics include over 159.4k products, making this a competitive space to launch in.
Who hunted YAGNI?
YAGNI was hunted by Jack Collins. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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Jack Collins
Hey Product Hunt 👋 Jack here, founder of YAGNI.
The best teams I've been on ran on trust. It's what makes a team fast, and it's the hardest thing to build and the easiest to break. I've spent twelve years building and running teams, through two acquisitions, a Techstars batch, and orgs across healthcare, government, and startups big and small, B2C and B2B. That lesson held everywhere.
AI changed my own output more than any tool ever has. But it brought the trust problem back in a new form. More output means a worse signal-to-noise ratio, and the moment you try to put agents to work inside a business you hit a wall: where do you even start? Every tool assumes you'll be directive. Either you prompt each task ("do this thing"), or you wire up an if-this-then-that graph and hope you predicted the work correctly. That's not how anyone actually runs a team.
YAGNI takes the approach I learned managing people. You hand a Team a real slice of the business to own and give it the structure you'd give a new hire: Responsibilities, a Number it's measured on, Commitments with real deadlines, and Rhythms (its recurring work). Then you manage the early work closely. It drafts, you edit and approve, and every correction teaches it how you'd do it next time.
As its track record grows, it climbs a ladder you control: Training → Supervised → Autonomous. At the top it carries the routine, reversible work on its own, every action leaves a Receipt from the source system proving where things actually stand, and you stay in the loop for the calls that matter. Irreversible and high-risk actions stay behind your approval forever, at every level. That's a design commitment, not a model limitation.
Two things I decided early, because I'd want to know them as a buyer. First, it runs exclusively on open-weight models, so it's cheap enough to let Teams work continuously instead of sparingly. Second, it only uses first-party, official integrations, so your data is read where it lives, never sold, never used to train a model.
Humans and Teams work off the same context, and it all collates onto your Front Page, published as a Brief morning, midday, and evening. Monday's status meeting starts at the decisions instead of the recap. Dive into any work with a persistent chat sidebar to so that you always have the context to make the decision.
Who it's for: founders and operators who've become the bottleneck (the person everything routes through), and lean teams who want real leverage from agents without babysitting them.
What to try first, and don't sign up: go to https://yagni.app/build-your-team, paste your company's website, and about 30 seconds later YAGNI hands you a Brief with your first Teams already drafted: what it would own, which tools it would read, and what it would do in week one. Free, anonymous, no card. If the Team it drafts is wrong for your business, I genuinely want to hear why.
Paid plans start at $99/mo when you're ready to put a Team to work. Get 60% off ANY plan for 6 months with code YAGNIPH (60% because we can offer AT LEAST 60% savings of frontier models).
I'll be here all day. Ask me the hard ones: pricing, security, "isn't this just a wrapper," what happens when it screws up. I'd rather answer those in public than in a sales call.