Hello Hacker News! We're Filip, Stavros, and Vivek from Terminal Use (https://www.terminaluse.com/). We built Terminal Use to make it easier to deploy agents that work in a sandboxed environment and need filesystems to do work. This includes coding agents, research agents, document processing agents, and internal tools that read and write files.Here's a demo: https://www.youtube.com/watch?v=ttMl96l9xPA.Our biggest pain point with hosting agents was that you'd need to stitch together multiple pieces: packaging your agent, running it in a sandbox, streaming messages back to users, persisting state across turns, and managing getting files to and from the agent workspace.We wanted something like Cog from Replicate, but for agents: a simple way to package agent code from a repo and serve it behind a clean API/SDK. We wanted to provide a protocol to communicate with your agent, but not constraint the agent logic or harness itself.On Terminal Use, you package your agent from a repo with a config.yaml and Dockerfile, then deploy it with our CLI. You define the logic of three endpoints (on_create, on_event, and on_cancel) which track the lifecycle of a task (conversation). The config.yaml contains details about resources, build context, etc.Out of the box, we support Claude Agent SDK and Codex SDK agents. By support, we mean that we have an adapter that converts from the SDK message types to ours. If you'd like to use your own custom harness, you can convert and send messages with our types (Vercel AI SDK v6 compatible). For the frontend, we have a Vercel AI SDK provider that lets you use your agent with Vercel's AI SDK, and have a messages module so that you don't have to manage streaming and persistence yourself.The part we think is most different is storage.We treat filesystems as first-class primitives, separate from the lifecycle of a task. That means you can persist a workspace across turns, share it betw
FL score
out of 100
Verdict
high confidence
Competition
23
competitors found, emerging market, funded players
Trend
6 community mentions
A Vercel-like platform for deploying stateful, filesystem-based AI agents, targeting a niche but growing developer pain point.
The pain
The gap
Build angle
Strengths
Questions about this idea?
FlyBot reads the scoring and gives you a second opinion on “Terminal Use (YC W26) – Vercel for filesystem-based agents”.
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 for developers deploying stateful, filesystem-based AI agents, with clear signals for willingness to pay. However, the solution space is competitive, and the complexity makes it challenging for a solo builder to achieve rapid time-to-market.
Value Equation
Dream outcome and how likely it feels, against the time and effort it costs.
Good market opportunity in a growing space, but high complexity and strong competition challenge value delivery and feasibility for a solo builder.
One-Person Business
Curiosity pull, identity fit, and a path from free value to paid for a solo creator.
Clear problem and good monetization potential, but challenging simplicity, reach, and leverage for a solo builder in a competitive space.
Viral Frameworks
Hook strength, shareability, and how cheaply it can be tested.
Clear target audience and value prop with a proven business model, but distribution and market size assumptions need further validation.
Builder Lens
Evidence the problem exists, timing, defensibility, and a model that fits on a napkin.
Strong demand for solving agent deployment pains, but the narrowest wedge and early surprises need more focus for rapid traction.
Why this verdict
Five lenses, one composite. How scoring works
The angle
This weekend
Who is already there, emerging market
Provides cloud-hosted development environments integrated with GitHub, ideal for professional developers.
Pricing: Offers a free tier; advanced capabilities require a subscription.
An AI-powered desktop IDE built on VS Code, focusing on developer control and precision coding in local environments.
Pricing: Free 2-week trial, then $25/month.
A development platform tailored for fast, scalable, and secure sandbox environments, especially for frontend prototyping and testing AI agents.
Pricing: Offers generous free tiers or community editions.
Enables visual full-stack web app creation using only Python code, featuring a browser-based drag-and-drop UI builder and one-click deployment.
Pricing: Offers a free plan. Paid plans start from $15/month for individual plans.
A collaborative in-browser IDE that allows users to write, run, and share code in many programming languages.
Pricing: Offers a free tier; advanced features require a subscription.
A PaaS provider that developers use to deploy web and SaaS applications without managing underlying infrastructure, offering automatic scalability and Git-native deployments.
Pricing: Hobby plan is $0 (compute costs billed separately). Professional is $19/user/month. Organization is $29/user/month.
A frontend cloud platform to streamline modern web application development, scaling, and security, with serverless functions for backend logic.
Pricing: Offers a free developer plan. Pro plan is $20/member/month. Enterprise pricing available upon request.
A PaaS built on a managed container system with integrated data services, known for its simplicity in deployment.
Pricing: Fully paid, no longer offers a free tier.
A developer-centric platform that allows applications to run close to users by deploying them on a global network of servers, emphasizing edge computing.
Pricing: Offers a free tier for small applications. Paid plans are usage-based.
A modern PaaS that allows developers to deploy applications with ease, offering Git-based deployments and a focus on developer experience.
Pricing: Usage-based pricing; offers a free trial.
A PaaS that simplifies app deployment and management, built on the Cloud Native Buildpack model, supporting smart autoscaling and various programming languages.
Pricing: Offers a free tier for up to three static sites. Paid plans are usage-based.
An open-source, self-hostable PaaS that simplifies deploying applications, databases, and services, offering a dashboard similar to Vercel or Render.
Pricing: Free (self-hosted), requires managing your own VPS.
What they charge
What people say, 6 mentions
How to Build Apps & Software Without Code (UPDATED JULY 2025 GUIDE)
r/Entrepreneur
I built and launched a SaaS-style product as a one-person team using AI for almost everything
r/SaaS
What am I doing wrong, or is the product wrong or we are too early?
r/SaaS
Ramp just released March 2026 SaaS spending data. Here are the 5 most interesting patterns.
r/SaaS
2026 AI Coding Agent Dev Tool Market Map
r/SaaS
I sold 75 Bitcoin at $300 each to start a business. Lost everything. Ended up alone in Bahrain with no plan. Then I typed "create me a chatbot" as a laugh.
r/SaaS
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Market signals
The market for deploying agents in sandboxed environments is growing, driven by the increasing demand for AI applications and the need for secure, scalable development and deployment platforms. Recent funding rounds indicate strong investor interest in platforms that offer simplified deployment, AI integrations, and flexible infrastructure options. There's a clear trend towards platforms that provide managed services, automated CI/CD, and support for various programming languages and frameworks, particularly those catering to AI/ML workloads.
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