Engineer

github

Deepraj Bera  • Peerlist

Building smarter software with ML and Cloud | CSE undergrad at KIIT

<a target="_blank" rel="noopener noreferrer" class="break-all link-break text-gray-500 hover:underline" href="https://runstack.buildlab.in/">Runstack</a> is a middleware layer for AI agents that eliminates context bloat and enables scalable tool usage.Instead of exposing hundreds of tools directly to an LLM (which increases token usage, slows responses, and hits context limits), Runstack introduces a meta-tool architecture - where the model interacts with just four intelligent interfaces: search, authenticate, connect, and execute.Behind the scenes, a dynamic tool registry manages all domain tools (GitHub, math, APIs, etc.), allowing agents to discover and invoke tools on-demand rather than carrying their definitions in every prompt.This results in:<ul><li>Massive token reduction (fixed context size regardless of tool count)</li><li>Better reasoning (LLM focuses only on relevant tools)</li><li>Infinite scalability (connect thousands of tools seamlessly)</li><li>Built-in auth orchestration (OAuth handled via meta layer)</li><li>Zero-code extensibility — add or remove tools without changing agent logic</li><li>Zero downtime updates — new tools become instantly available without redeploys</li></ul>Runstack transforms how AI agents interact with external systems fundamentally decoupling tool management from agent logic - making them faster, smarter, and production-ready at scale.

Runstack

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When we launched Architech a few months ago, the goal was simple: make system design less painful and more collaborative. The feedback we got from the community has been incredible, and it pushed us to take things a lot further. This launch brings some of the biggest updates yet: <ul><li>AI-driven design capabilities → Allowing for rapid prototyping and system architecture development.</li><li>Codebase integrations → visualize your GitHub, GitLab &amp; Bitbucket repos instantly. </li><li>GitHub sync → push diagrams right into your project’s README. </li><li>Expanded templates → SaaS, AI/ML pipelines, LLM apps, mobile backends, and more.</li><li>In-house AI models (arch-base &amp; arch-apex) → trained on real architectures and engineering knowledge. </li><li>Themes &amp; customization → make the canvas yours.</li><li>Community sharing → create and share templates with others. </li></ul>Our vision is to make Architech the go-to place for turning messy ideas or complex repos into clear, production-ready architecture blueprints. We’d love your feedback — what works, what doesn’t, and what you’d love to see next. And of course, if you’re building something cool, we’d be excited to hear how Architech fits into your workflow.