tilde.run
Bridging the data Infrastructure gap for AI. Ensure AI data governance, make AI training and agent runs reproducible, reduce access friction.
tilde.run launched on May 7, 2026 with 11 votes, #1,153 of 20,538 launches that month and more than 90% of that year's launches.
What it does
Let AI agents loose on production. Without the risk. Tilde turns every agent run into a transaction you can roll back. Code from GitHub, data from S3, and documents from Drive show up as a single versioned filesystem. Every outbound call is checked and logged. Autonomous code, finally safe to use against real data.
Tilde started from a simple observation: AI agents are only as useful as the environment they can work in. Giving an agent a prompt is easy. Giving it the right files, credentials, tools, context, and execution environment, safely and repeatably, is much harder. Over the past year, we learned a lot from teams trying to […]
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Tilde.run – Agent sandbox with a transactional, versioned filesystemMay 2026 · tilde.run · ▲205Tilde started from a simple observation: AI agents are only as useful as the environment they can work in. Giving an agent a prompt is easy. Giving it the right files, credentials, tools, context, and execution environment, safely and repeatably, is much harder. Over the past year, we learned a lot
Tines Feb 2026 · tines.com · ▲557Hey HN! This is Yannick from Tines, really excited to share what we’re launching today. Tines 3B is a new product we’ve built for teams building agents, apps, and automations with AI, on top of the assumption that people are already doing this, whether or not IT or security knows about it. Finance, marketing, and more are building dashboards in Claude Code or Codex. None of it is malicious, people are doing exactly what they were asked to do. The issue is there's no easy way for that work to run securely: it ends up on a laptop or personal account, with a credential pasted directly into the…
PylarDec 2025 · pylar.ai · ▲502Hey HN! We're Hoshang & Vishal, the team behind Pylar - a governed access layer between databases and LLMs. We previously led data and AI and we kept seeing the same problem across teams using LLMs internally: agents are great with unstructured data, but the moment you want them touching your actual systems of record — Snowflake, Postgres, CRMs, product DBs — everything becomes fragile, risky, or outright unsafe. Two issues show up every single time: 1. Agents over-querying They don’t understand cost. They’ll happily generate queries that blow up your warehouse bill. 2. Accidental data…
How to build and self-host a code review agentJul 2026 · trytilde.ai · ▲29Hey HN, I've had a side-project that I've slowly ticked away at over the last year called Tilde. Tilde is a harness SDK platform - I've tried to take the best things of OpenClaw, Hermes & other harnesses and decompose them and make them available as cloud API building blocks. You can use Tilde to create AI agents for your use case, fast and self-host the agent's yourself. The documentation (and attached blog post) leave a lot to be desired in terms of technical documentation but hopefully the attached git repo does a good job of showcasing the API.…
ReplicasJun 2026 · replicas.dev · ▲239Hey HN! I'm Connor, creator of Replicas. I'm a heavy Codex/Claude Code user, and I wanted to hand off tasks to agents like I would to an engineer - kick something off before work, let it scaffold while I'm at lunch, even come back to a ready PR. The problem: existing alternatives use workspace VMs that are black boxes. I have no access to any of them - they can't run tests, read logs, or use tools like the Playwright MCP (which I use to verify agents actually fixed what they claim to fix). Replicas gives agents real cloud workspaces where they can: - Run your test suite and read the…
AgenMar 2026 · agenhq.com · ▲138AI changed the way we code, but we're still using the old processes, and we've become the bottleneck, the AI is waiting for us - to reply, to open our laptops, to review the code, and so on. We're building the future of AI software development. The agents are autonomous, they run in sandboxes, automatically fix the pipelines, and deliver you the final, working code. You can use live preview to see the changes they made. Working across multiple repositories, all within the same session. This is the future - you don't need an IDE, and you don't have to run anything locally.
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