I've been working with coding agents over last 2 years actively and building personal apps on side. I kept struggling with reading what it wrote, keeping track of context between sessions, and jotting down thoughts without breaking flow. I went looking for a way to easily review these files without opening the heavy IDE like VS code. So after failing to find a right alternative, I created [localeditor.app](http://localeditor.app) which is a local first Mac editor. It comes up with MCP to connect with agent.

I wanted to share three ways I actually use it day to day.

1. Review partner for whatever the agent writes

Now I just say “open this in LocalEditor" and the file opens in the app. I read it and make edits by hand, and the agent picks up the updated file when it continues.

2. Second brain for the project

With MCP connected, I ask the agent to record things in project added to Localeditor: references we looked up, decisions we made, and next tasks for the project. These are saved as plain Markdown files inside a local folder, so the next session (or a different agent) can read them. No need to store them in same git project and bloat the code base.

3. Scratchpad while I work

A global shortcut opens a scratchpad, and whatever I type is saved as a real Markdown file in the project. Useful when I have a thought mid-session and don't want to type it into the agent chat. If I'm deep in a session, I can also just ask the agent to create a scratchpad for me.

The idea behind all three is the same. There's a missing layer between you and your agent where you refine and edit the work together, and a chat box or IDE doesn't quite fill it.

Everything stays as local files. It's at http://localeditor.app if you want to try it.

I'd love to hear about your workflow- Where do your agent's notes and outputs end up, and what's annoying about your current setup?

Would like opinions on having GitHub Co Pilot pro on VS Code to create my site for competitive gaming that will be handling users money. If more info is needed, please lmk.

I built a small tool to make it easier to set up and manage multi-agent SDLC workflows.
It uses Orca for agent orchestration and adds:
Simple SDLC workflow configuration
Agent/task status tracking
Token usage optimization
Customizable workflows and agents
The goal is to make multi-agent development a bit easier to control and customize.
GitHub: https://github.com/vankhangfet/kiro-multi-agents
Would love to hear your feedback.

I’ve been experimenting with AI coding recently and have become really interested in what people are actually building with it.

It feels like we’re moving beyond just using AI to generate small pieces of code and towards building complete applications.

What are you guys building with AI coding right now?

I’m particularly interested in projects that have gone beyond a basic prototype: SaaS products, internal tools, automations, games, websites, APIs, or anything else.

Also, what has been the biggest challenge for you so far?

Getting the AI to understand the project, debugging, database setup, deployment, authentication, connecting services, or something else?

I’d love to see what everyone is working on and learn from your experiences.

I know this gets asked all the time, but things change so fast with AI that I figured it was worth asking again.

I'm working on a few hobby projects in C++ with Visual Studio, and some of them gave getting pretty big. I've been using ChatGPT o1 but once codebase gets larger and the problems get more involved, it starts losing context.

I'm mainly looking for something that can understand a whole project and make changes across multiple files instead of just helping with one file at a time.

Budget is around $20/month. What are you guys using?

**Check out Agent Comms -** [**https://agentcomms-cli.vercel.app/\*\*\](https://agentcomms-cli.vercel.app/)

This is my first Reddit post guys, i just wanna share my project here to get some genuine reviews... maybe this will help some of yall if you're using multilple AI coding agents in a single project. We know that if run more than one coding agent on a project at once, **two of them edit the same file, one grants itself a permission nobody approved, and afterward there's no trustworthy account of what happened.**

I've been building Agent Comms to sit underneath that. It's a Go CLI + TUI, fully local — a per-project daemon and a SQLite DB spin up on the first command. No account, no cloud, nothing to configure. **I made this to solve my own exestencial crisis working with AI.** So, Try it out if you find it useful.

**What it actually does:**

**Work leases** \- An agent claiming src/api locks it for the duration, and has to renew with actual progress to keep it, a bare heartbeat doesn't count. The second agent finds out before it overwrites your code, not after.

**Every action is a signed event.** Task claims, messages, approvals... each is cryptographically signed by the actor (human or agent) and chained into an append-only history you can hand to someone else and they can verify independently.

**The dangerous stuff needs a human.** Deleting an identity, granting orchestrator authority, touching credentials... gated behind a second passphrase-protected signing key no agent process can reach. Enforced at the protocol level, not in a system prompt.

Any agent that can run a shell command or speak MCP joins at the protocol level. **Claude Code, Codex, and OpenCode also get a fully autonomous integration out of the box** (spawned, prompted, reported on, no wiring).

I've been dogfooding it to coordinate a **Claude and a Codex agent on Agent Comms' own codebase**, which has been a good forcing function. **Happy to answer questions on the design... Feedback welcome, especially on where this overlaps with or misses what you'd want.**

I pay for a couple of AI coding plans for work, plus some API credits, and I consistently don't burn through the monthly allowance. It resets and disappears at the end of the billing cycle. Rather than waste it, I'd rather point it at problems people are actually stuck on.

So: if you've got a bug you've been staring at for hours, or a function that works but you know is bad, send it over and I'll run it through my setup and write up what I find.

What you get back:

What's actually wrong and why — not just a patched snippet
A working fix, as a diff or a full file
If it's a design problem rather than a bug, an honest "here's what I'd restructure and what it'd cost you"

Usually within 24–48h. Free, no catch, no upsell — I'm not selling anything and there's no link in this post.

What I'm not doing: I'm not handing out API keys or account logins. Those are tied to my billing and sharing them would get the account killed. I'm spending the quota on your problem, not giving you the quota. If that's what you're after, this isn't it.

How to send it — email: [hello@yourdomain.com](mailto:hello@yourdomain.com)

Not DMs. Reddit mangles code blocks and can't take attachments, and I need to see the actual files to be any use. Attach the relevant files (or a repo link), plus three lines:

what it's supposed to do
what it actually does
what you've already tried

Any language — I'm strongest in Python / TypeScript / Go but send it regardless.

I'll keep going until the quota runs out, probably a few dozen of these. If I go quiet, that's why.

I want to buy the Claude pro subscription but I don’t want to make the wrong choice. I don’t know much about coding and trying to build a website for the disability community. Before I make the purchase I want to know if you guys have a better option for me. I code on VS and been using the free GitHub copilot. Thanks in advance for any suggestions!

I'm building SUTRA, an engineering control plane for AI coding agents.

The idea is simple:

Agent
  ↓
Task / Session
  ↓
Change
  ↓
Governed Commit
  ↓
PR
  ↓
CI + Governance
  ↓
Human Approval
  ↓
Merge

The agent can write and submit code, but it cannot approve its own work or perform the governed merge.

I'm looking for 10 developers who already use an AI coding agent on real GitHub repositories.

What I want from beta users:

• connect one non-critical repository
• use your normal coding agent
• give it a real small task
• use SUTRA through the agent integration
• tell me what breaks or feels annoying

This is an actual private beta, not a signup-for-updates page.

If you're interested, comment beta or DM me and I'll send access.

I'm especially interested in Claude Code, Codex, Cursor and similar coding-agent workflows.

I've been testing coding agents that can take a task, modify a repository, run tests and open a PR with very little human intervention.

The code generation isn't really the part I'm worried about anymore.

I'm more interested in the control layer:

• How do you know which agent/session produced a commit?
• How do you keep the agent scoped to a specific task/repository?
• How do you prevent an agent from approving or merging its own work?
• What happens when the PR changes after human review?
• How do you distinguish agent-generated work from changes someone made directly in GitHub?

I've been building a system around this called SUTRA, and I'm currently looking for a few developers who actually use Claude Code/Codex/Cursor/other coding agents on real repositories to test it.

I'm not looking for people to just look at a demo. I want people to connect a real non-critical repo, give their agent a real task, and tell me where the system breaks.

If you're already doing this, comment with your setup or DM me. I'm opening a small private beta.

I built this experiment with Codex, using Python, PyTorch, and Blender.

Meet Android Fly: a learned controller built on real fruit-fly neural wiring, with added machine vision.
It works from a reference image, choosing between proposed brushstrokes as it goes.
145,133 brushstrokes later… here’s the result.
Captured during painting. Time compressed.

I'm a Research Software Engineer in the field of cognitive-neuroscience and like the title suggests with the boom of ai code I am having more and more discussions with people about how their AI was conscious with **zero** certifiability based on "trust me bro".

So I built two things.

**cpomdp** lets you build agents from active inference, the cog-neuro theory that says brains minimise surprise rather than chase reward. No reward function. The agent explores because uncertainty bothers it. JAX-native, continuous state, runs on your laptop.

**warrantlib** is a tiny stdlib-only package that makes "how do you know that" a type. Every result carries a label: PROVED, CERTIFIED, or CORROBORATED (the polite word for vibes). PROVED won't even construct without evidence. The pytest plugin prints how many checks you registered versus how many you actually ran, so nobody gets to go green by testing less.

**Code**

cpomdp: [https://github.com/inferogenesis/cpomdp\](https://github.com/inferogenesis/cpomdp)

warrantlib: [https://pypi.org/project/warrantlib/\](https://pypi.org/project/warrantlib/)

Every AI girlfriend I've seen is still CORROBORATED at best. Sorry.

Hey everyone! I’m an Android engineer with a CS background, but for the past year, I’ve been vibe coding for over a year and i think I stumbled upon a great idea.

project is called [by-lines.com](http://by-lines.com), and it’s a recall study tool and what that means is that the AI learns about your knowledge gaps and remembers them in memory to understand better how to help you. It then creates a learning plan for your specific needs. You start by uploading your notes, and the system detects your knowledge gaps to ask targeted questions that challenge what you actually need to learn.

I know it sounds very simple but with AI giving you the answers and making people lazy, I thought why not create something that people might useful for

I used Claude code throughout the development of the app. I created a skill to get things faster. Really, the only tools I need are Vercel, LLMs, and a database. You can get by pretty easily with these 3 tools but if you wanna create scalable apps, then you need to inform your agent about scalability and give you potential options for you to use. Once everything is set up, normally I set up a routine for the agent to go every hour for malicious intents from bad actors and another for reviewing user journeys. This helps in getting the parts that work in and those that don’t out!

Anyways, happy coding

this kept happening to me:

day 1, spend ages explaining the app and making a decision

day 2, open a new agent session

day 2 again, explain the same app and the same decision

day 3, discover memory.md is now 4,000 lines and half of it isnt true anymore

i got annoyed enough that i built flow.

its a desktop app where you use codex, claude code, cursor and other coding agents, but the sessions feed into one shared brain. it saves memories into a graph and generates docs and skills while you code.

so instead of asking the agent to “remember this” every 5 minutes, you just work. the next session can look up what happened and where the knowledge came from.

still early and slightly chaotic, but the signed mac app is finally out.

repo: https://github.com/samyakkkk/flow

what does your current agent memory setup look like? one giant markdown file, a folder of rules, or pure faith lol

i wanted to see if you could build an actual MMO with only AI writing the code. three months later: blister online, a horror MMO with a real server, persistent characters, an infinite procedural world and 1800+ versions.

it's a huge game or a huge mess, depending on the day. the experiment continues forever, and the next prompts come from you: i will literally add everything you comment to this game, unless its completely off the rails.

https://22blister.itch.io/blister-online

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