zoomzoom

There are designs for untethered structures in orbit that could function with current technology, e.g. https://en.wikipedia.org/wiki/Skyhook_(structure)

As opposed to multiple-choice forms, conversational surveys drive true insight. AI-powered conversations enable this insight to scale.

Writing a blog post and would love HN's input on this question!

Is the high level instruction compiled to a flowchart under the hood? If so maybe a conversational interface is another layer on a flowchart and not an alternative? Overall it makes sense that flowcharts are limiting when they get big, yes. Product looks cool congrats on the launch.

At Coherence, we're building the infrastructure layer that enables customers to make sense of the data in your product using AI agents. Our product enables you to get a chat interface live in your existing application, with access to all your current backend endpoints and APIs, in less than an hour.

This correlates (in a scary way) with some interesting hypothesizing I've seen about possible cataclysims from earth's core changing within human history: https://theethicalskeptic.com/2024/05/23/master-exothermic-c...

We've built a data generation studio that creates robust test datasets for testing their LLM applications in just minutes. While working with hundreds of engineering teams on DevOps automation, we discovered a critical gap: everyone wants to build AI products, but acquiring, labelling, and organizing test data for tasks is a massive challenge.

The current approaches to creating "golden datasets" for LLM testing are either infrastructure-heavy (observability-based) or time-consuming (manual creation). Many teams end up relying on intuition-based development, which leaves crucial questions unanswered about model selection, edge cases, and performance optimization.

Our solution generates comprehensive, realistic test datasets tailored to your specific use cases. You provide context (existing examples, domain information, or system prompts), and it creates robust test data that helps you:

- Balance distribution across your test suite including edge cases - Evaluate prompt effectiveness across various scenarios - Compare and optimize model selection - Identify and handle edge cases systematically - Assess performance across diverse use cases - Support rapid R&D experimentation with different data shapes

We're launching this as the first data studio focused on giving AI engineers both speed and precision in their development workflow. If you're building AI products, we'd love your feedback on our approach to making LLM testing more reliable and efficient.

Check out what we’re building at https://www.withcoherence.com/

If interested in a similar product with GCP support, check out https://cncframework.com.

Appreciate the POV, and agree that Coolify has a much better community around it! A lot we can learn from. Not sure we agree on the license front since we do allow commercial use.

Coolify and cnc are very different technical solutions. Coolify is a server you deploy to a VM that then can schedule workloads onto that VM, managing features like ingress and updates. cnc is a client-side CLI that schedules workloads into managed cloud services like lambda, cloud run, ECS, or Kubernetes. It orchestrates public cloud provided services instead of providing them itself (e.g. RDS vs. MySQL in a docker container on a VM). The trade-offs here are too big for a comment and both are a great fit for different use cases. We dive in a bit deeper with our POV here: https://www.withcoherence.com/post/the-2024-web-hosting-repo...

We wrote up this guide (withcoherence.com, we're somewhere in the PaaS space and I'm a cofounder) https://www.withcoherence.com/post/the-2024-web-hosting-repo.... Hope it's helpful!

At Coherence (withcoherence.com - I'm a cofounder) we are delivering the open-source benefits of Coolify (less vendor lock-in, cheap hosting costs) via our open-source CNC framework (cncframework.com) while still keeping a hosted SaaS control plane that eliminates the "few hours of fiddling with setup" that the blog author minimizes here. Maintenance and configuration complexity over time (as you customize and use click-ops to configure) are endless, especially as you get more usage or host more projects.

Coolify is awesome software, and alongside similar tools like Caprover, Dokku, and Cloud66, it has its role. But for business use-cases I believe that giving up managed cloud services is too big a leap to make sense, and that a middle-ground approach will win in the long term.

Hey HN, Zach here, cofounder of Coherence (withcoherence.com). We’re excited to announce the launch of AWS Lmabda support for our open-source CNC framework. Let us know what we can do to make it better!

Hey HN, Zach here, cofounder of Coherence (withcoherence.com). We’re excited to announce the launch of free-tier compatible serverless deployment options for both AWS and Google Cloud Platform (GCP). This new functionality enables developers to deploy applications directly to AWS Lambda and GCP Cloud Run, leveraging the power of serverless architectures without intermediary platforms. We hope that these provide a way to use Coherence for low-volume or R&D type projects, and open up some interesting new use cases!

You can learn more in our docs:

AWS Lambda - https://docs.withcoherence.com/reference-architectures/aws/l... GCP Run Lite - https://docs.withcoherence.com/reference-architectures/gcp/r...

Appreciate this feedback, thanks so much for sharing!

The tagline clearly doesn't say what we want here, but the idea is that we are a framework that sits on top of IaC tools like the ones listed above, and makes them easier to use. Under the hood, cnc uses terraform/opentofu to actually manage infra, the cnc layer adds new concepts like environments onto those tools as well as providing a much simpler, higher level configuration with cnc.yml, while still enabling you to edit the templates directly so you're not limited in the infra you can deploy for your app. In this way, we're the first tool of that kind, sort of like a "PaaS in your own cloud" but we expose the plumbing as a CLI.

Thanks again!

In the ever-evolving software development landscape, one of the most influential ideas of the past decade has been the "git flow" working style, thanks to the iconic blog post "A Successful Git Branching Model." Here, we suggest an updated workflow with less long-lived branching.

Developer experience is hard to quantify, and is not a simple as correlating with subjective input of "how devs feel." SPACE and DORA are attempts to get objective about engineering productivity. Some teams prefer to use a more subjective approach here as well. There aren't any great answers for equivalents in developer experience, yet.

There are some obvious "tooling" considerations that impact developer experience. For the most part, these are related to how much devs can "self-service" the various parts of the SDLC, and how good the user experience of that service flow is. For teams that want to get a great experience without reinventing the wheel, internal developer platforms like what we're building at Coherence (withcoherence.com) are a great answer.

We've also got a free 1-minute PR velocity scorecard that you can try: https://www.withcoherence.com/post/measure-your-pr-efficienc...

Fixing our highest drop-off step with an integrated AI agent

Migrate your app from Vercel to GCP in just a few clicks

Now any software development team can measure their PR efficiency with Coherence's new Velocity Scorecard

Check your PR size, review time, and pace against industry benchmarks for free using Coherence's new velocity tool!

Discover the evolution and cutting-edge practices in measuring engineering velocity! For software teams, mastering this metric isn't just about numbers—it's a journey towards consistent value delivery, process enhancement, and turning velocity into a catalyst for continuous growth, not just a measure of judgment.

My view is that there are areas where GCP is better and areas where AWS is better. AWS has a much bigger community, and better business continuity story. GCP has a better developer experience and more uniquely-amazing best-in-class products (e.g. Spanner, Cloud Run, BigQuery). In the end, I don't believe Google will shut down GCP.

At Coherence (withcoherence.com) - I'm a cofounder - we deliver a developer platform that lets use use either cloud in a developer-friendly way. It also gives you some protection against lock-in to either cloud.

At Coherence (withcoherence.com) we are building a slightly different twist on this where one configuration can drive different environments across the SDLC - Cloud IDE for dev, full-stack branch previews, CI/CD, staging/qa/UAT, production - with deployments in your own AWS/GCP account.

We generally see a ton of velocity increase in dev from teams that adopt the Cloud IDE alongside the rest, as exhibited by lots of comments. Internally, we dogfood them 100% and the team would never go back to the old "local-first" ways. So we are using them and love them. The key qualities we love are ephemerality, parallelism, and accessibility. But in general there is a lot of resistance for various reasons, as seen in many comments here.

We wrote up some of our POV in our docs here: https://docs.withcoherence.com/docs/explanations/remote-deve...

[I'm a cofounder of Coherence]

If interested in using Neon for ephemeral environments, Coherence (I’m a cofounder) recently launched a first-class integration with Neon for just this purpose: https://docs.withcoherence.com/docs/reference/integrations#n...

Would be cool to try using this extension on top of RDS or Cloud SQL to offer the same experience without the overhead of another SaaS tool!

The best answer to keeping your workstation clean & secure is, in my view, a thin-client paired with ephemeral remote environments:

Immutable or chain-of-trust based host OS (e.g. nix or iOS)

Minimal software installed (including docker, which itself is heavy and full of vulns or opens the door to them)

Do everything on ephemeral remote environments where the configuration is stored in reviewable tools (e.g. GitHub) and the state can be wiped at will. This means you reduce your surface area for persistent malware to supply chain and network attacks, which require careful practices to avoid but which are well-understood

Remote envs are preferred to local virtualization (e.g. quebes) because they lend themselves to team use and sharing more, and so are more likely to be widely adopted and collectively improved. Also easier to create different hardware configurations as needed (when you need a bigger GPU temporarily), as well as different environment types - e.g. always-on previews for QA testing. Also eliminates persistent paths in the local OS for malware storage

(I'm the cofounder of Coherence)

I consider the "best-in-breed" tools with this shape to break into the following categories:

"Infra Abstractions": DuploCloud, Massdriver, Stacktape "PaaS in your own cloud": Nullstone, Zeet, Quovery, Porter, Architect.io, FlightControl "SDLC Platform for Teams": Coherence (withcoherence.com) - the key difference here is in how CI/CD (incl integration tests) are handled, how development environments are configured alongside other environments, and how production is segregated from other environments.

This a somehow both a crowded space and an emerging one. But we believe that even with the diversity of choice that there are clear reasons that most teams will by (vs. build) their internal dev platform in the future: namely the cost to buy vs. to build/maintain, and the productivity from better tools.

If you're building a Refine app and want to deploy it to AWS or GCP in your own account, I just posted a setup video of using Refine on Coherence (withcoherence.com): https://youtu.be/gFCXXU72Nec. We're happy to get you set up the same way if you get in touch (disclosure - I'm a cofounder).

As the CEO and cofounder of Coherence (withcoherence.com) - it's cool to see this project launch. At Coherence, we've been working fully in the cloud for the last 2 years - and it's better than I thought it would be. But it's hard to get more conservative teams to jump into a new workflow. While we've done a lot to support integration with local tools and development, I'm looking forward to seeing more innovation, and am curious to see Google invest here more directly. For us, all of this innovation is about delivering the best developer experience for end users that we can, let's see what direct IDX goes as well.

Other products to check out: codesphere, stackblitz, Replit

We are excited to introduce our latest project, The Cloud Whitepaper Index, which leverages generative AI to give you an AI-powered Cloud Architecture expert with access to almost 1,000 expert-written whitepapers from AWS, GCP, CloudFlare, Azure, and the CNCF.

If you want a similar in-cloud VSCode experience, but tied more tightly to your SDLC (e.g. CI/CD, branch previews, deployments) for each project and requiring less configuration to get a dev server running alongside it (this just lets you edit code, not run it) we offer “Workspaces” at withcoherence.com.