Sgnly is building an open-source, self-hostable e-signature platform designed to be a cost-effective alternative to services like DocuSign. It prioritizes privacy and security by allowing users to control their data and integrates seamlessly with existing workflows. The platform is built with a modern tech stack, aiming for a smooth and intuitive user experience comparable to commercial offerings, but with the added flexibility and control of open-source software.
FlowRipple is a visual workflow automation platform designed for building and managing complex workflows without code. It features a drag-and-drop interface for connecting pre-built blocks representing various actions, including integrations with popular apps, webhooks, and custom code execution. FlowRipple aims to simplify automation for both technical and non-technical users, allowing them to automate tasks, connect services, and streamline processes across their work or personal projects. Its visual nature offers a clear overview of the workflow logic and facilitates easier debugging and modification.
Hacker News users discussed the complexity of visual programming tools like FlowRipple, with some arguing that text-based systems, despite their steeper learning curve, offer greater flexibility and control for complex automations. Concerns were raised about vendor lock-in with proprietary platforms and the potential difficulties of debugging visual workflows. The lack of a free tier and the high pricing for FlowRipple's paid plans were also criticized, with comparisons made to cheaper or open-source alternatives. Some commenters expressed interest in seeing more technical details about the platform's implementation, particularly regarding its handling of complex branching logic and error handling. Others praised the clean UI and the potential usefulness of such a tool for non-programmers, but ultimately felt the current offering was too expensive for individual users or small businesses.
Workflow86 is an AI-powered platform designed to streamline business operations. It acts as a virtual business analyst, helping users identify areas for improvement and automate tasks. The platform connects to existing data sources, analyzes the information, and then suggests automations or generates code in various languages (like Python, Javascript, and APIs) to implement those improvements. Workflow86 aims to bridge the gap between identifying business needs and executing technical solutions, making automation accessible to a wider range of users, even those without coding expertise.
HN commenters are generally skeptical of Workflow86's claims. Several question the practicality and feasibility of automating complex business analysis tasks with the current state of AI. Some doubt the advertised "no-code" aspect, predicting significant setup and customization would be required for real-world use. Others point out the lack of specific examples or case studies demonstrating the tool's efficacy, dismissing it as vaporware. A few express interest in seeing a more detailed demonstration, but the overall sentiment leans towards cautious disbelief. One commenter also raises concerns about data privacy and security when allowing a tool like this access to sensitive business information.
The paper "Auto-Differentiating Any LLM Workflow: A Farewell to Manual Prompting" introduces a method to automatically optimize LLM workflows. By representing prompts and other workflow components as differentiable functions, the authors enable gradient-based optimization of arbitrary metrics like accuracy or cost. This eliminates the need for manual prompt engineering, allowing users to simply specify their desired outcome and let the system learn the best prompts and parameters automatically. The approach, called DiffPrompt, uses a continuous relaxation of discrete text and employs efficient approximate backpropagation through the LLM. Experiments demonstrate the effectiveness of DiffPrompt across diverse tasks, showcasing improved performance compared to manual prompting and other automated methods.
Hacker News users discuss the potential of automatic differentiation for LLM workflows, expressing excitement but also raising concerns. Several commenters highlight the potential for overfitting and the need for careful consideration of the objective function being optimized. Some question the practical applicability given the computational cost and complexity of differentiating through large LLMs. Others express skepticism about abandoning manual prompting entirely, suggesting it remains valuable for high-level control and creativity. The idea of applying gradient descent to prompt engineering is generally seen as innovative and potentially powerful, but the long-term implications and practical limitations require further exploration. Some users also point out potential misuse cases, such as generating more effective spam or propaganda. Overall, the sentiment is cautiously optimistic, acknowledging the theoretical appeal while recognizing the significant challenges ahead.
The author details a frustrating experience with GitHub Actions where a seemingly simple workflow to build and deploy a static website became incredibly complex and time-consuming due to caching issues. Despite attempting various caching strategies and workarounds, builds remained slow and unpredictable, ultimately leading to increased costs and wasted developer time. The author concludes that while GitHub Actions might be suitable for straightforward tasks, its caching mechanism's unreliability makes it a poor choice for more complex projects, especially those involving static site generation. They ultimately opted to migrate to a self-hosted solution for improved control and predictability.
Hacker News users generally agreed with the author's sentiment about GitHub Actions' complexity and unreliability. Many shared similar experiences with flaky builds, obscure error messages, and difficulty debugging. Several commenters suggested exploring alternatives like GitLab CI, Drone CI, or self-hosted runners for more control and predictability. Some pointed out the benefits of GitHub Actions, such as its tight integration with GitHub and the availability of pre-built actions, but acknowledged the frustrations raised in the article. The discussion also touched upon the trade-offs between convenience and control when choosing a CI/CD solution, with some arguing that the ease of use initially offered by GitHub Actions can be overshadowed by the difficulties encountered as projects grow more complex. A few users offered specific troubleshooting tips or workarounds for common issues, highlighting the community-driven nature of problem-solving around GitHub Actions.
Summary of Comments ( 24 )
https://news.ycombinator.com/item?id=43498031
Hacker News users discussed the practicality and necessity of another e-signature solution, questioning Sgnly's differentiation from established players like DocuSign, HelloSign, and PandaDoc. Several commenters pointed out the maturity of the existing market and the difficulty of competing with entrenched incumbents. Concerns were raised about Sgnly's pricing model, particularly its free tier limitations, with some suggesting it felt more like a lead generation tactic for paid features. Others questioned the stated focus on legal documents, given the broad applicability of e-signatures. Overall, the sentiment was skeptical, with commenters urging the Sgnly creators to demonstrate a clear competitive advantage beyond minor UI/UX differences.
The Hacker News post "We are building the next DocuSign" sparked a discussion with several comments, mostly focusing on the challenges faced by the new entrant, Sgnly, and skepticism about its differentiation from established players like DocuSign.
Several commenters questioned the viability of competing with DocuSign, given its market dominance and network effects. One user highlighted the difficulty of displacing an incumbent, particularly when the incumbent offers a good enough solution. They used the analogy of trying to replace email, emphasizing the entrenched nature of such tools. Another commenter echoed this sentiment, pointing out the significant hurdles Sgnly faces in terms of market penetration and user acquisition. They questioned the value proposition, asking what Sgnly offers that DocuSign doesn't already provide.
Some users pointed out potential niches Sgnly could exploit. One suggestion was to focus on specific industries or verticals with unique regulatory requirements or workflows, where a more specialized solution might be appealing. Another commenter mentioned the possibility of undercutting DocuSign on price, though they acknowledged the difficulty of sustaining this strategy in the long run.
Specific features of Sgnly were also discussed. One commenter praised the clean UI/UX showcased on the website, but cautioned that a visually appealing interface doesn't guarantee success. Another user expressed interest in the claimed ease of integration, but questioned how it truly differed from DocuSign's existing integration capabilities.
The thread also touched on open-source alternatives and the potential for a decentralized approach to digital signatures. While acknowledging the theoretical benefits, commenters noted the practical challenges of adoption and achieving widespread acceptance for such solutions.
Several commenters inquired about specific features or functionalities, such as support for different signature types, audit trails, and compliance with various regulations. These questions remained largely unanswered by the Sgnly representative.
Overall, the sentiment in the comments was cautiously skeptical. While acknowledging the potential for innovation in the digital signature space, most commenters expressed doubts about Sgnly's ability to effectively challenge DocuSign's dominance without a clear and compelling differentiation strategy.