You can, however, continually monitor and steer the agent by refining its instruction set / memory to improve it over time so that it makes better decisions itself.

I have claude connected to the Cronloop MCP and occasionally ask it to analyze the previous N runs of my agent to see if its instructions should be adjusted.

Cronloop is more of a control plane that makes it nicer & more scalable once you have many agents and need to monitor / refine them over time.

Create & manage unlimited agents in one place, they all run in the cloud - no machine to manage and keep online yourself, easily monitor and analyze runs (agent runs stream in real-time), tune the agent with run duration constraints, give it the ability to self-improve with the built-in durable memory system without having to invent your own, connecting tools is very simple (200+ supported in the connector library).

It also runs codex, not just claude code.

I currently have ~25 cronloop agents running on various models between codex/claude.

Running them all on /loop would be painful and hard to maintain without cronloop or a similar control plane.

Just create an agent, set a schedule, connect your existing claude code/codex subscription, give your agent instructions + tools, and boom - you have an autonomous agent running in a loop, working while you sleep.

Every agent has a simple, durable markdown-based memory system. Your agents can self-improve over time - you can include instructions to record learnings with each run for other agents to benefit from.

Some ways I'm using it:

- I built a self-driving events website (aievents.now) and have a cronloop agent for each city that autonomously curates events every morning. - I have a few websites autonomously SEO-optimizing every day based on search console data + keyword research.

Free to try - you can create up to three agents for free to get started.

Comments URL: https://news.ycombinator.com/item?id=49348220

Points: 1

# Comments: 5

Just click "New agent", set a schedule, connect your existing claude code/codex subscription, give your agent instructions, connect the tools it needs, and boom - you have an autonomous agent running in a loop, working while you sleep.

Some ways I'm using it:

- I built a self-driving events website (aievents.now) and have a cronloop agent for each city that autonomously curates events every morning. - I have a few websites autonomously SEO-optimizing every day based on search console data + keyword research.

Some features:

- Every agent runs in an ephemeral, isolated sandbox - You can monitor runs in real-time (the agent logs stream into the app) - Every agent has a simple, durable markdown-based memory system. Your agents can self-improve over time - you can include instructions to record learnings with each run for other agents to benefit from. - You can leverage your existing claude code/codex subscriptions or bring your own API key. - 200+ connectors are ready-to-go - connect your agents to any tool that has an MCP, CLI, SDK, API, etc. - You can configure the agent's environment with a setup shell script if needed for greater flexibility

Free to try - you can create up to three agents for free to get started.

You bring your own inference, so cronloop is very generous with usage, the pro plan offers unlimited agents with up to a 5 min interval on runs for $25/mo (or $20/mo annual).

I'm a huge Cronloop user and get a lot of value from it, so I'm excited to share it. Let me know your thoughts!

*Hand-written comment, no AI

Comments URL: https://news.ycombinator.com/item?id=49336157

Points: 2

# Comments: 1

Comments URL: https://news.ycombinator.com/item?id=48721003

Points: 1

# Comments: 0

Comments URL: https://news.ycombinator.com/item?id=48720653

Points: 3

# Comments: 0

The idea is simple: issues should live with your code. They show up in diffs, travel with branches, and don't require accounts, databases, or external services. They're just markdown files with YAML frontmatter.

It's built for AI coding assistants. You can tell Cursor/Claude/Codex (or any AI agent) things like "create a bug for the login redirect issue, high priority" and it handles the rest — creating, searching, updating, and closing issues through natural language. There's a Cursor skill you can install with `npx skills add miketromba/issy`.

It also comes with a CLI for filtering/searching and a local web UI at localhost:1554 for when you want a visual overview.

Key points: - Zero infrastructure — no DB, no accounts, no SaaS - Issues are git-native — visible in PRs, blame-able, branch-able - Fuzzy search with typo tolerance - Monorepo-aware (walks up the directory tree to find .issues/) - Works offline

Blog Post: https://mike.gg/issy

GitHub: https://github.com/miketromba/issy

Comments URL: https://news.ycombinator.com/item?id=47008034

Points: 1

# Comments: 0

Tweakcn also charges $ users to be able to share and save themes which I think is silly for a tool like this, should be 100% free and open source.

I also prefer the simple UX of ShadcnThemer better but I'm biased of course.

The goal was to make it easy to visually design shadcn color themes, preview them live across various example UIs, and export them straight into your projects (as CSS or via the shadcn CLI registry command).

I had a bit of experience going into this because I built the Theme Studio for VS Code in the past, but it was fun using a modern stack and leveraging Cursor to help me along the way this time.

GitHub: https://github.com/miketromba/shadcn-themer

Comments URL: https://news.ycombinator.com/item?id=45706487

Points: 136

# Comments: 41

Comments URL: https://news.ycombinator.com/item?id=44380784

Points: 1

# Comments: 0

The fundamental issue is that agents / LLMs at present are not engineers or system architects. You cannot sit back and play product manager yet. If you go in with this expectation, you will certainly have a poor experience.

LLM-powered coding agents are not comparable to any existing human role or tool and therefore cannot be used interchangeably. They are a fundamentally new and novel type of tool that enable incredible productivity IF and only if you use them effectively. The tool is not the problem, the user is.

I’m also building a non-trivial SaaS platform and the cursor agent has written 90%+ of the code in the codebase. It has architected ~0% of the codebase. It has modeled ~0% of the data layer in the codebase. It has enabled me to move at least 10x the speed of implementation and debugging (yes, it is incredible at debugging if you use the right techniques).

I use the word implementation because that is almost exclusively what I use it for. I do the planning, design, architecture, engineering. Then, I communicate those specifications to it in digestible chunks, and it implements them incredibly fast. It makes mistakes sometimes, comes up with poor naming conventions, fails to reuse existing modules in the codebase, etc. But that’s fine - I simply give it feedback, point it in the right direction, and within seconds it’s back on course.

I own the codebase, it’s just my super fast implementation minion. If it gets something wrong - that’s my fault. I failed to communicate my expectations clearly. I’m heavily using my brain while working with the LLM - I’m just reserving those mental cycles for higher-level decision making than the actual tokens to type into the editor.

The power is in your ability to steer it and communicate in clear terms what you want, and maintain the right level of abstraction in your instructions. Too specific and you lose some of the benefit beyond just writing the code by hand, too vague / high-level and it will over-engineer something totally different than what you intended.

You’re the engineer, it’s just a really smart semantic code generator. That might change in the future, but for now, if you use it in this way, the productivity benefit is very clear.

I’ve been using cursor with 3.7 sonnet max (now sonnet 4) and I already can’t imagine a world without coding agents - it is so deeply rooted into my workflow.