... handle things like: Invoice processing and approvals Recruitment and candidate screening flows Lead enrichment, routing, and follow ups Travel desk and reimbursements Data cleanup, sync, and reporting agents Under the hood, it ships with 1000+ tools, native RAG, memory, guardrails, and observability baked in so you can actually trust agents in a live environment. We re live on Product Hunt today: https://www.producthunt.com/prod... Two asks from this group: If you have 2 3 minutes, I d really appreciate ... ... agent workflow in your world right now? I d love to hear ideas, edge cases, or this would only work for me if it did X/Y/Z. Happy to answer anything about how we re thinking about agent design, guardrails

... That can get complex fast and become a security nightmare. With Venn, we aim to fix that.  Venn is a universal connector: connect your apps to Venn once, use them with OpenClaw, Claude, ChatGPT, Cursor, and VS Code. Set guardrails

... Last week we did something stupid. We paused all human coding. Gave Claude (Anthropic) access to our GitHub repo. Told it to build new features, fix bugs, and ship. No human review. No guardrails. Just Claude and our codebase. For 7 days, it ran the engineering team. Here's what happened. Day 1: Confidence was high. Claude (Sonnet 4.6 then Opus 4.5) fixed a small CSS bug in 30 seconds. Then refactored a messy function into something readable. We felt ... ... review the logic and have it review the implementation before anything gets merged. Two things that I do almost every time that has significantly improved the quality is to have the agent do a gap analysis of the plan vs

... handling this in practice. Are you fully relying on your cloud provider s secrets layer? How are you handling rotation across multiple environments? Have you found a setup that actually eliminates drift, or is it mostly managed with guardrails? Would be especially interesting to hear if the move toward JWT signing keys is changing how people think about this layer. Comment from Jackson Liu(@jacksonliu_): @eric_nodeops  Yeah that s a fair question and honestly, this is where ... ... redefining them keeping a typed env schema (e.g. Zod validation) so missing/misaligned vars fail fast and avoiding per-env divergence unless absolutely necessary So I wouldn t say it eliminates drift but it reduces it to something manageable with guardrails

... tools out there? They let you do it. Pine Script doesn't stop you from overfitting. Python backtesting libraries don't warn you about data snooping. QuantConnect gives you 16 hours of compute per experiment and zero guardrails on methodology. So we built Varrd. It's not a backtesting tool. It's a system that an LLM gets placed into where it is physically impossible to test wrong. The AI runs inside a framework with hard guardrails

... explain how and why it happened and how you'll ensure it won't happen again. That's 10x worse than when you eat it yourself. Comment from Daniel Foster(@dpfoster): @ddu   @jake_friedberg  unlimited with guardrails, 100% yes. Our ToS include an abuse clause. For us at this stage, policy is enough, along with occasional analytics review to look for extreme outliers or patterns of abuse. And thanks for using Camtasia and Snagit, @jake_friedberg ...I hope ... ... customer again. Comment from Daniel Foster(@dpfoster): We recently introduced generative voice and video into our Camtasia bundled subscription plans while retaining a traditional SaaS pricing model. Why? Sticking with the SaaS model helps us differentiate from competitors

... sparked an interesting thought experiment: how likely is it that we ll see AGI (AI that thinks and learns like a human) within the next five years? The report highlights a fascinating divergence: the view from money vs. the view from science. Money : the probability inferred from trillions poured into data centers, Nvidia chips, and servers. Investors seem to be betting that AGI is inevitable. Science : the probability inferred from research papers and AI development models. Experts are far more ... ... might be ahead of reality. Expect volatility, overpromised outcomes, and valuable lessons along the way. Meanwhile, AI continues reshaping work, attention, and human behavior. I d love to hear the community s perspective: Are you seeing this money vs

... Project X Incident Runbook while composing. * Scoped & read-only: Chips are TTL (time-to-live) bound, no auto write-back; your current project s memory stays clean. * Inline provenance: Replies show which chip informed which part. * Admin guardrails: Allow/deny lists, approvals, label-based redaction (PII/secrets), and audit logs. Why it helps * Cut repeat explanations across repos/teams. * Reuse proven auth/logging/CI/CD patterns instead of reinventing. * Faster onboarding by bridging Architecture + Conventions. * Safer incident response: pull the right runbook just for this ... ... into a new hire s first week. Open questions (feedback welcome!) * Security model: Is read-only + TTL + provenance enough? What else is mandatory? * UX: Where should chips live in the composer to avoid friction? * Policy defaults: Org opt-in vs

... started testing Watchflow s rule engine across some of the most active GitHub repositories: vscode langchain react pytorch kubernetes Only vscode