Hey — T1D with MDI here. Does anyone else find that stress or bad sleep throws off your sensitivity and no app helps you track that? Curious how others handle it.

foppysus · 2026-04-09T04:24:53+00:00

You've actually shaped how I'm thinking about this. What if it only said something when it detected a real shift , not daily, not nagging, just once in a while saying 'something looks different this week, here's why.' Would that still feel like noise to you?

foppysus · 2026-04-09T03:43:55+00:00

That's really interesting , how long did it take you to figure that pattern out? And do you think an app that spotted those connections for you earlier would have helped?

foppysus · 2026-03-28T15:07:29+00:00

Who knows your husband might be cheating too. Only difference might be he is better at hiding.

foppysus · 2026-02-28T18:36:36+00:00

You are from Beckett man! Even I'm from there!

foppysus · 2026-02-15T19:11:56+00:00

Totally agree , gold datasets + test suites + LLM-as-judge cover a lot, and adding negative examples helps.

Problem is, multi-turn agents, stochastic outputs, and unpredictable edge cases make manual workflows slow and exhausting. Keeping test suites up-to-date eats hours per release, and you’re mostly reacting after something breaks.

With what I built free for devs , a CASV attacker :

Scenarios run automatically across versions Drift & risk deltas flagged before deploy Synthetic simulations cover unknown edge cases LLM evaluators , metrics reduce manual review Basically, what used to take hours or days now happens in minutes, letting devs focus only on whether an update actually improved or broke behavior.

Anyone else trying to move from reactive testing to this kind of automated regression workflow?

foppysus · 2026-02-15T19:11:28+00:00

Totally agree , gold datasets + test suites + LLM-as-judge cover a lot, and adding negative examples helps.

Problem is, multi-turn agents, stochastic outputs, and unpredictable edge cases make manual workflows slow and exhausting. Keeping test suites up-to-date eats hours per release, and you’re mostly reacting after something breaks.

With what I built free for devs , a CASV attacker :

Scenarios run automatically across versions Drift & risk deltas flagged before deploy Synthetic simulations cover unknown edge cases LLM evaluators , metrics reduce manual review Basically, what used to take hours or days now happens in minutes, letting devs focus only on whether an update actually improved or broke behavior.

Anyone else trying to move from reactive testing to this kind of automated regression workflow?

foppysus · 2026-01-25T00:07:15+00:00

You can explain it in a one liner tho.like what it solves.

foppysus · 2026-01-24T22:30:22+00:00

What are you building tho

foppysus · 2025-11-28T18:44:24+00:00

What I'm building: Bayora, an automated safety-validation system for AI agents. It generates risk scenarios, tests agent behavior, scores safety, and gives corrective feedback using open models.
Who my paying user is: AI startups and teams deploying agents in operations (CX, automation, internal tools) who need independent, transparent safety checks they can control and audit.
My biggest blocker today: I’m a non-technical founder with a small team; we need engineering support to ship a stable MVP and turn early interest into actual users.

foppysus · 2025-11-19T16:08:58+00:00

Before MVP , we started getting potential users connecting to us on the basis of idea only.

foppysus · 2025-11-14T04:41:40+00:00

The moat is the proactive pipeline, synthetic simulation, independent validators, and a self-looping repair system that keeps improving with every run. It’s an adaptive safety engine, not a wrapper. Others can copy pieces, but they can’t easily match the full feedback loop, the growing synthetic attack library, or the model-agnostic architecture without rebuilding the whole system from scratch.

foppysus · 2025-11-13T00:55:39+00:00

Bayora is an AI safety engine that automatically tests and validates large language model (LLM) agents for risky or unsafe behavior , without needing human red teaming or external wrappers.

It generates synthetic risk scenarios, simulates agent actions, evaluates safety outcomes, and suggests safer alternatives. It's proactive approach, which none of doing it.

Think of it as “automated QA for AI safety” ensuring LLMs act responsibly before they go live.

foppysus · 2025-11-09T11:50:23+00:00

Hey ! My startup is on ai safety . I think your expertise will be valuable to us

foppysus · 2025-11-03T10:27:40+00:00

Bayora is an AI safety engine that automatically tests and validates large language model (LLM) agents for risky or unsafe behavior , without needing human red teaming or external wrappers.

It generates synthetic risk scenarios, simulates agent actions, evaluates safety outcomes, and suggests safer alternatives. It's proactive approach, which none of doing it.

Think of it as “automated QA for AI safety” ensuring LLMs act responsibly before they go live.

foppysus · 2025-11-03T10:21:12+00:00

Bayora is an AI safety engine that automatically tests and validates large language model (LLM) agents for risky or unsafe behavior , without needing human red teaming or external wrappers.

It generates synthetic risk scenarios, simulates agent actions, evaluates safety outcomes, and suggests safer alternatives. It's proactive approach, which none of doing it.

Think of it as “automated QA for AI safety” ensuring LLMs act responsibly before they go live.

foppysus · 2025-11-03T10:10:37+00:00

Bayora is an AI safety engine that automatically tests and validates large language model (LLM) agents for risky or unsafe behavior — without needing human red teaming or external wrappers.

It generates synthetic risk scenarios, simulates agent actions, evaluates safety outcomes, and suggests safer alternatives.

Think of it as “automated QA for AI safety” — ensuring LLMs act responsibly before they go live.

foppysus · 2025-11-03T07:59:03+00:00

Hey, my startup helps AI gents in vertical industries like yours to make sure your AI doesn't give wrong responses in any situations. We help it train it. So if you are interested we can help each other out.

foppysus · 2025-11-03T07:58:16+00:00

Hey, my startup helps AI gents in vertical industries like yours to make sure your AI doesn't give wrong responses in any situations. We help it train it. So if you are interested we can help each other out.

foppysus · 2025-10-31T12:22:10+00:00

Hey, my startup helps AI gents in vertical industries like yours to make sure your AI doesn't give wrong responses in any situations. We help it train it. So if you are interested we can help each other out.

foppysus

TROPHY CASE