Alternatives
Products that do what Model Boss does
Delegate code to cheaper models. Keep frontier judgment.
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2025 · github.com
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We built a model router that plugs into coding agents (e.g. Claude Code, Codex, Cursor, etc.) and intelligently sends requests to the best model to serve them. Here's a quick demo of running it locally: https://www.youtube.com/watch?v=isKhAyivtfM. At Weave, we write most of our code with AI, and it's been getting more expensive. This came to a head when Opus 4.7 was released and, thanks to its tokenizer changes, our costs shot up. We knew we didn't need Opus for everything but we didn't want to lose out on the intelligence for the cases where you really need it. So we decided…
Jun 2026 · github.com
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I built a lightweight project management workflow to keep AI-driven development organized. The problem was that context kept disappearing between tasks. With multiple Claude agents running in parallel, I’d lose track of specs, dependencies, and history. External PM tools didn’t help because syncing them with repos always created friction. The solution was to treat GitHub Issues as the database. The "system" is ~50 bash scripts and markdown configs that: - Brainstorm with you to create a markdown PRD, spins up an epic, and decomposes it into tasks and syncs them with GitHub issues - Track…
2025 · github.com
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KingCoding▲91Run Claude, Codex & Cursor in parallel from one dashboard
Mar 2026 · kingcode.shingoirie.com
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Single-agent LLMs suck at long-running complex tasks. We’ve open-sourced a multi-agent orchestrator that we’ve been using to handle long-running LLM tasks. We found that single LLM agents tend to stall, loop, or generate non-compiling code, so we built a harness for agents to coordinate over shared context while work is in progress. How it works: 1. Orchestrator agent that manages task decomposition 2. Sub-agents for parallel work 3. Subscriptions to task state and progress 4. Real-time sharing of intermediate discoveries between agents We tested this on a Putnam-level math problem, but the…
Feb 2026 · github.com
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Warning: this whole post is a blatant plug for my Open Source project https://github.com/etiennesillon/ModelRunner There is lot of discussion around no code platforms and why developers don’t like them. My view is that they can be very useful to quickly get through the boring parts of a project, like creating master data management screens for example. So I’ve built my own version which interprets models at run time and, it turns out, understands natural language queries too! Hi, my name is Etienne, I love coding and I’ve been doing it for a few decades now so I’d rather…
2022 · modelrunner.org
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ive spent the past few months designing a framework for orchestrating multiple large language models in parallel — not to choose the “best,” but to let them argue, mix their outputs, and preserve dissent structurally. It’s called Maestro heres the whitepaper https://github.com/d3fq0n1/maestro-orchestrator (Narrative version here: https://defqon1.substack.com/p/maestro-a-framework-for-coher...) Core ideas: Prompts are dispatched to multiple LLMs (e.g., GPT-4, Claude, open-source models) The system compares their outputs and synthesizes them It never…
2025
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1 Orchestrator. 18 AI Agents. 6 PM Workflows. In Claude Code
Mar 2026 · github.com
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A bunch of companies that I spoke to had their own claude & codex OTel dashboards that showed spend + seats per month. However, none of the dashboards actually analyzed how the engineers worked with the tools and if there were any areas for improvement! That's why I created https://www.promptster.ai. Managers get aggregate level view of code quality and how that ties with team workflows (nothing on a per-engineer level). While engineers get personalized coaching on how they can save tokens while keeping output high. We also have a tool built for individuals to test their local…
Jul 2026
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