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I have been building many many many projects the last 2 years and everytime i faced one problem.

Managing all of my projects

Most of my apps never published because i couldn't keep up with the ideas that i have since i couldn't open so many windows and code across multiple projects

That's why when i installed OpenClaw i had this idea. To build multiple projects in one dashboard without switching apps.

Then i created ClawCode which you can build, manage and plan multiple projects on one dashboard. But not only that, when you open a project, automatically openclaw generates 12 agents:

- 1 Main - 5 Coding - 1 Debugger - 1 Performance - 1 Planner - 1 Security - 1 Tester (opens browser) - 1 Ui Designer

Each projects gets its own agents, which you can run in parallel mode or with queued messages. So you can set up 5 coding agents, switch project set up next 5 switch next 5 etc.

That solved my biggest problem. But not only that, if you are starting a new project you can describe the app, build the actual plan with planner agent, build the workflow and split it into tasks. Then assign tasks to agents by writing # in chat.

My plan is to extend the same logic to have Claude instead of using only OpenClaw and connect your server logs, feature requests and errors reports from your customers, so agents can run them without needing to pay for other apps or switching apps

The article explores three main reasons why being a parent can be rewarding: the joy of watching your child grow and learn, the opportunity to pass on your values and experiences, and the fulfillment of creating a new life and legacy.

I've been building the substrate layer for production AI systems in Rust. This is the index repo for 10 crates I shipped this week. The AI side covers agent memory (episodic, semantic, working with decay and multi-agent bus), cost governance with hard budget enforcement and automatic model downgrade cascade, CRDT state sync for distributed agent fleets, output versioning with full lineage tracking, a knowledge graph on top of agent memory, LLM inference primitives for WASM and edge runtimes, and a complete ReAct loop that runs inside a Cloudflare Worker. The financial side covers market primitives (orderbook, OHLCV, indicators, position, risk) and a streaming ingestion pipeline handling 100K+ ticks/second across 4 exchanges.

Everything is zero-panic enforced at the lint level, typed errors with thiserror throughout, no unnecessary dependencies. The crates are designed to compose, the orchestrator runs the agents, memory stores what they know, the graph understands relationships between what they know, the budget governs what they spend, sync keeps 24 agents consistent without locks.

The orchestration engine that coordinates all of this is tokio-prompt-orchestrator, which I've been running with 24 simultaneous Claude Code agents.

https://github.com/Mattbusel/rust-crates

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Major reinsurers are no longer offering war risk coverage after the U.S. torpedoed an Iranian ship, raising concerns about the availability of insurance for maritime operations in geopolitically volatile regions.

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A fun daily scavenger hunting game where you can find the target anywhere on Earth!

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The article profiles Alex Ray, the co-founder and chief scientist of Anthropic, an artificial intelligence company aiming to develop safe and beneficial AI systems. It examines Ray's background, Anthropic's approach to AI development, and the challenges and potential implications of their work in the rapidly evolving field of AI.

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Old School Realms is a retro-style gaming platform that offers a collection of classic RPG-inspired titles, allowing players to explore various fantasy worlds and engage in engaging gameplay reminiscent of the golden era of gaming.

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An agtech company has moved its headquarters from California to Minnetonka, Minnesota, attracted by the state's strong agricultural and technology sectors. The move is expected to create new jobs and strengthen the company's presence in the Midwest.

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I've been experimenting with analyzing websites from a behavioral perspective instead of just traditional analytics.

One thing that keeps standing out is that most analytics tools tell you what happened (bounce rate, session time, funnels, etc.), but they rarely explain why visitors behaved that way.

For example, a high bounce rate might mean: - confusion about the product - lack of trust - unclear value proposition - hesitation about pricing

But the analytics alone usually don't reveal which one it is.

I'm curious how other builders here approach this problem.

When you look at your own product or landing page metrics, how do you actually determine why users hesitate or leave?

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