Hey HN! We're Ashwin and Akshay from Spine AI (https://www.getspine.ai). Spine Swarm is a multi-agent system that works on an infinite visual canvas to complete complex non-coding projects: competitive analysis, financial modeling, SEO audits, pitch decks, interactive prototypes, and more. Here's a video of it in action: https://www.youtube.com/watch?v=R_2-ggpZz0Q.We've been friends for over 13 years. We took our first ML course together at NTU, in a part of campus called North Spine, which is where the name comes from. We went through YC in S23 and have spent about 3 years building Spine across many product iterations.The core idea: chat is the wrong interface for complex AI work. It's a linear thread, and real projects aren't linear. Sure, you can ask a chatbot to reference the financial model from earlier in the thread, or run research and market sizing together, but you're trusting the model to juggle that context implicitly. There's no way to see how it's connecting the pieces, no way to correct one step without rerunning everything, and no way to branch off and explore two strategies side by side. ChatGPT was a demo that blew up, and chat stuck around as the default interface, not because it's the right abstraction. We thought humans and agents needed a real workspace where the structure of the work is explicit and user-controllable, not hidden inside a context window.So we built an infinite visual canvas where you think in blocks instead of threads. Each block is our abstraction on top of AI models. There are dedicated block types for LLM calls, image generation, web browsing, apps, slides, spreadsheets, and more. Think of them as Lego bricks for AI workflows: each one does something specific, but they can be snapped together and composed in many different ways. You can connect any block to any other block, and that connection guarantees the passing of context regardless of block type. The
FL score
out of 100
Verdict
high confidence
Competition
10
competitors found, emerging market, funded players
Trend
No signal yet
A visual canvas with collaborating AI agents designed for complex, non-coding projects, challenging the linear chat interface for AI.
The pain
The gap
Build angle
Strengths
Questions about this idea?
FlyBot reads the scoring and gives you a second opinion on “Spine Swarm (YC S23) – AI agents that collaborate on a visual canvas”.
Risks
Next steps
Fly Labs Method
Is the pain real, is there a gap, is it the right time, can one person build it.
The idea addresses a real and specific pain point in AI-assisted project work with a novel visual, block-based approach. While the pain is clear and payment signals exist, the complexity of building and the presence of strong, albeit indirect, incumbents make it a high-effort endeavor for a solo builder.
Value Equation
Dream outcome and how likely it feels, against the time and effort it costs.
Strong market pain and growth, with a differentiated product offering clear value, but high build complexity and resource requirements.
One-Person Business
Curiosity pull, identity fit, and a path from free value to paid for a solo creator.
Addresses a clear and impactful problem but is far too complex and resource-intensive for a solo builder, lacking simplicity and leverage.
Viral Frameworks
Hook strength, shareability, and how cheaply it can be tested.
Offers a clear value proposition to a specific audience with a viable business model, but its advanced stage means validation readiness is not applicable for a new solo builder.
Builder Lens
Evidence the problem exists, timing, defensibility, and a model that fits on a napkin.
Addresses a critical, growing need with an innovative interface but could benefit from a more focused initial wedge.
Why this verdict
Five lenses, one composite. How scoring works
The angle
This weekend
Who is already there, emerging market
An online collaborative whiteboard platform for team collaboration and visual thinking.
Pricing: Free plan available. Paid plans start at $8 per user/month (billed annually) for Team, $16 per user/month (billed annually) for Business, and custom pricing for Enterprise.
A digital workspace for visual collaboration, particularly useful for design thinking and agile methodologies.
Pricing: Free plan available. Team+ plan is $12 per member/month (billed annually), Business plan is $17.99 per member/month (billed annually), and Enterprise is custom pricing.
An AI-powered platform for creating multimedia stories and presentations quickly and easily.
Pricing: Free plan with limited presentations and no AI features. Pro plan is $20 per user/month, or $16 per user/month when billed annually.
An AI-powered platform for creating presentations, documents, and webpages from text prompts.
Pricing: Free plan with 400 credits per month. Plus plan is $8 per user/month, Pro plan is $15 per user/month.
An AI-powered presentation platform that helps teams create polished, on-brand slides with automated design.
Pricing: Pro plan is $45 per month (billed annually), Team plan is $180 per month (billed annually). Custom pricing for Enterprise. A free trial is available.
An AI slide maker that works as an add-on inside Google Slides and PowerPoint.
Pricing: Free trial available. Pro plan at $10/month, Business at $20/month, and Enterprise with custom pricing.
An AI-native presentation tool that leverages AI to create high-quality, on-brand slides effortlessly.
Pricing: Free plan for 5 AI-generated presentations. Pro plan starts at $8 per month for US customers, custom pricing for Enterprise.
An AI-powered tool that quickly generates high-quality presentations from text or documents.
Pricing: Offers a free trial, then paid plans to download presentations (specific numbers not found).
Legal AI agents that automate and manage every part of a legal case on a visual canvas.
Pricing: Pricing not publicly available (requires demo).
A technology that maps a company's or individual's extended network to reveal strong introduction paths.
Pricing: Pricing not publicly available (requires demo).
What they charge
Recent news
Launch HN: Spine Swarm (YC S23) – AI Agents Collaborating on a Visual Canvas
Hacker News, March 15 2026
Spine Swarm just launched on Product Hunt
Reddit (r/ProductHunters), March 10 2026
Spine - 2026 Company Profile, Team, Funding & Competitors
Tracxn, March 08 2026
Spines raises $16 million Series A to transform the publishing industry with AI
Ctech, November 19 2024
Pens at the ready! Spines secures $16M to revolutionize publishing with AI
Refresh Miami, November 19 2024
Market signals
The market for AI agents collaborating on visual canvases for non-coding projects is a growing niche. Recent funding rounds, such as The Swarm raising $8M and Spine AI (Spine Swarm) receiving seed funding from Y Combinator, indicate increasing investor interest. The trend is moving towards more intuitive human-AI collaboration beyond traditional chat interfaces, leveraging visual workspaces for structured and auditable task execution.
What frustrates people
Last summer we faced a conundrum at my company, Tiger Data, a Postgres cloud vendor whose main business is in timeseries data. We were trying to grow our business towards emerging AI-centric workloads and wanted to provide a state-of-the-art hybrid search stack in Postgres. We'd already built pgvectorscale in house with the goal of scaling semantic search beyond pgvector's main memory limitations. We just needed a scalable ranked keyword search solution too.The problem: core Postgres doesn't provide this; the leading Postgres BM25 extension, ParadeDB, is guarded behind AGPL; developing our own extension appeared daunting. We'd need a small team of sharp engineers and 6-12 months, I figured. And we'd probably still fall short of the performance of a mature system like Parade/Tantivy.Or would we? I'd be experimenting long enough with AI-boosted development at that point to realize that with the latest tools (Claude Code + Opus) and an experienced hand (I've been working in database systems internals for 25 years now), the old time estimates pretty much go out the window.I told our CTO I thought I could solo the project in one quarter. This raised some eyebrows.It did take a little more time than that (two quarters), and we got some real help from the community (amazing!) after open-sourcing the pre-release. But I'm thrilled/exhausted today to share that pg_textsearch v1.0 is freely available via open source (Postgres license), on Tiger Data cloud, and hopefully soon, a hyperscalar near you:https://github.com/timescale/pg_textsearchIn the blog post accompanying the release, I overview the architecture and present benchmark results using MS-MARCO. To my surprise, we were not only able to meet Parade/Tantivy's query performance, but exceed it substantially, measuring a 4.7x advantage on query throughput at scale:https://www.tigerdata.com/blog/pg-textsearch-bm25-fu
AI
Hi HN!I recently switched from a Fedora/GNOME laptop to a MacBook Air. My old setup served me well as a portable workstation, but I’ve started traveling more while working remotely and needed something with similar performance but better battery life. The main thing I missed was a simple taskbar that shows the windows in the current workspace instead of a Dock that mixes everything together.I built boringBar so I would not have to use the Dock. It shows only the windows in the current Space, lets you switch Spaces by scrolling on the bar, and adds a desktop switcher so you can jump directly to any Space. You can also hide the system Dock, pin apps, preview windows with thumbnails, and launch apps from a searchable menu (I keep Spotlight disabled because for some reason it uses a lot of system resources on my machine).I’ve been dogfooding it for a few months now, and it finally felt polished enough to share.It’s for people who like macOS but want window management to feel a bit more like GNOME, Windows, or a traditional taskbar. It’s also for people like me who wanted an easier transition to macOS, especially now that Windows feels increasingly user-hostile.I’d love feedback on the UX, bugs, and whether this solves the same Dock/Spaces pain for anyone else.P.S. It might also appeal to people who feel nostalgic for the GNOME 2 desktop of yore. I started my Linux journey with it, and boringBar brings back some of that feeling for me.
AI
### Describe the project you are working on Godot C# bindings ### Describe the problem or limitation you are having in your project For the past weeks, I've been discussing with several Unity users intending to move to Godot C# regarding dealing with the C# garbage collector. The most common complaint I hear from users is that, in Unity, allocations can trigger unexpected GC spikes into the game. In Godot, we target to make all of the high performance APIs (those that intended to be called every frame) not allocate any memory, so theoretically the GC should not be a problem. Additionally, Godot starting from 4.0, uses the Microsoft CoreCLR version of .net, which also supposedly has a better garbage collector than Unity. But in all, after several discussions with Unity users, neither is enough reassurance for them, and they would really feel safer if Godot exposed a zero allocation API. ### Describe the feature / enhancement and how it helps to overcome the problem or limitation The idea of this proposal is that Godot exposes zero allocation versions of many functions in the C# API, that users can use if they desire. Technically, this could be done from the binding generator itself, without breaking compatibility, and without doing any modification to Godot itself. ### Describe how your proposal will work, with code, pseudo-code, mock-ups, and/or diagrams **WARNING** I am not familiar with C#, so take this as pseudocode. Imagine you have two functions exposed as to C#: ```C# void MyClass.SetArray( Vector2[] array); Vector2[] MyClass.GetArray(); ``` This works and is pretty and intuitive. However, it has two problems: * GC is allocated on return * Memory is copied to Godot native formats every time there is a call. The idea is to add NoAlloc versions, which can be generated directly by the binder automatically when required: ```C# void MyClass.SetArrayNoAlloc( Godot.Collections.PackedVector2Array array); void MyCl
AI