MindFort, a Y Combinator (YC X25) company, has launched an AI-powered continuous penetration testing platform. It uses autonomous agents to probe systems for vulnerabilities, mimicking real-world attacker behavior and adapting to changing environments. This approach aims to provide more comprehensive and realistic security testing than traditional methods, helping companies identify and fix weaknesses proactively. The platform offers continuous vulnerability discovery and reporting, allowing security teams to stay ahead of potential threats.
Relace, a YC W23 startup, has launched a code generation service focused on speed and reliability. It uses optimized models fine-tuned on specific programming languages to generate higher quality code faster than general-purpose models. Relace offers a command-line interface and VS Code extension, supporting common tasks like writing documentation, generating tests, refactoring, and translating between languages. Their goal is to boost developer productivity by automating tedious coding tasks, freeing up developers to focus on more creative and complex work. Relace is currently in closed beta.
The Hacker News comments discuss Relace's potential, focusing on its speed and reliability claims for code generation. Some express skepticism about its ability to handle complex real-world scenarios and the long-term viability of relying on AI for code generation. Others are curious about the underlying model and its training data, highlighting concerns about potential bias and the need for careful prompt engineering. A few users draw parallels with GitHub Copilot, questioning Relace's differentiation and competitive advantages. Several commenters express interest in specific use cases, like generating repetitive boilerplate code or migrating legacy codebases. There's also discussion about the closed-source nature of the product and the desire for more transparency regarding its inner workings.
The article "You're a little company, now act like one" advocates for small businesses to leverage their size as a strength. It argues against prematurely adopting the structures and processes of larger corporations, emphasizing the agility and adaptability inherent in being small. Instead of focusing on scaling quickly, small companies should prioritize direct customer interaction, rapid iteration, and personalized service to build strong relationships and a loyal customer base. This approach allows them to experiment, learn quickly from mistakes, and differentiate themselves in a crowded market. Ultimately, the author suggests that embracing the "little" allows companies to be more human, more responsive, and ultimately, more successful in the long run.
HN commenters largely agreed with the article's premise that small companies should focus on speed and flexibility. Several highlighted the importance of recognizing when a company is no longer "little" and adapting strategies accordingly. Some questioned the feasibility of staying small indefinitely, particularly in competitive markets. Others shared personal anecdotes of successfully applying the "little company" mindset, emphasizing quick iteration and direct customer interaction. A few commenters also pointed out the crucial role of company culture in maintaining agility and responsiveness as the team grows. One commenter argued that the core message wasn't solely applicable to small companies, but rather to any team or project aiming for efficient execution.
The author reflects on their time at Carta, highlighting key lessons learned about scaling a company. They emphasize the importance of clear and consistent communication, especially as organizational complexity increases. Building trust and psychological safety within teams, along with fostering a culture of ownership and accountability, are crucial for effective execution. The post also touches on the value of data-driven decision making, acknowledging the potential pitfalls of relying solely on metrics, and the need to balance quantitative analysis with qualitative understanding. Finally, the author underscores the continuous nature of learning and adaptation in a rapidly evolving environment and the significance of individual growth alongside company growth.
HN commenters generally praised the author's transparency and honesty regarding Carta's internal workings, particularly around compensation and performance reviews. Several questioned the effectiveness and fairness of Carta's stack ranking system, with some expressing concerns about its potential to create a toxic work environment and stifle innovation. Others debated the pros and cons of transparency in compensation, with some arguing that it can lead to jealousy and resentment while others believed it fosters fairness and trust. A few commenters also shared their own experiences with similar systems at other companies, offering both positive and negative perspectives. The overall sentiment leaned towards cautious appreciation for the insights, mixed with skepticism about the scalability and long-term viability of Carta's approach.
Jessica Livingston emphasizes the crucial role of finding your "people" – a supportive community – during the challenging journey of starting and running a company. This group, distinct from family or employees, comprises fellow founders who truly understand the unique struggles and anxieties of entrepreneurship. They offer validation, advice from experience, and a safe space to vent without judgment, ultimately helping you stay motivated, persevere through tough times, and maintain your sanity. Livingston encourages founders to actively seek out these kindred spirits through networking events, online communities, and peer groups, stressing that this support system can be instrumental in determining a startup's success or failure.
HN commenters largely agree with Jessica Livingston's advice to find your "tribe" of like-minded people, especially when starting a company. Several share personal anecdotes of feeling isolated before finding their group, emphasizing the importance of shared context and understanding. Some suggest practical approaches, like seeking out specific communities online or at events related to one's interests or industry. A few caution against insularity, recommending a balance between finding your tribe and remaining open to diverse perspectives. One commenter highlights the particular relevance of this advice for those outside of the typical Silicon Valley demographic.
The original poster is seeking advice on low-budget promotion strategies for a personal project. They have already explored some common avenues like social media, blog posts, and reaching out to relevant communities, but haven't seen significant traction. They are particularly interested in strategies beyond these basics, acknowledging the inherent difficulty of promotion with limited resources and hoping for unconventional or creative ideas. They are specifically looking for methods to gain initial traction and reach a wider audience without resorting to paid advertising.
The Hacker News comments on this "Ask HN" post offer various low-budget promotional strategies for personal projects. Several suggest focusing on building a community around the project through platforms like Reddit, Discord, and niche forums relevant to the project's target audience. Others recommend content marketing through blog posts, tutorials, and open-sourcing the project. Leveraging free tiers of services like Google Analytics and Search Console for SEO optimization was also mentioned. Some commenters cautioned against spending too much time on promotion early on, emphasizing the importance of a strong, valuable project as the foundation for any marketing efforts. A few suggested exploring free PR options like submitting to product directories or reaching out to relevant journalists and bloggers. Finally, some emphasized the effectiveness of simply sharing the project with friends and family for initial feedback and potential organic spread.
Overlap (YC S24) is seeking a product engineer to build the future of team sync. They're looking for someone with strong frontend skills (React, Typescript) and experience building and shipping user-facing products. This role offers the chance to work on a collaborative scheduling tool aimed at improving how teams manage their time and coordinate meetings, directly impacting user productivity. The ideal candidate thrives in a fast-paced startup environment, enjoys ownership, and is passionate about creating a seamless and delightful user experience.
HN commenters discuss Overlap's YC S24 participation and their product engineer job posting. Several express skepticism about the "impactful" nature of the work, questioning the actual need for a product like schedule syncing across different calendar platforms. Some also find the requested tech stack, particularly the mention of Webflow, unusual for a YC company. Others offer more supportive perspectives, emphasizing the potential market for such a product and the challenges of building reliable syncing solutions. The overall sentiment leans slightly negative, with concerns about the problem Overlap aims to solve and their chosen approach.
Dalus, a YC W25 startup building high-speed, high-precision industrial robots, is seeking a Founding Software Engineer. This engineer will develop software for designing and simulating the robots' complex hardware systems. Responsibilities include creating tools for mechanism design, motion planning, and system analysis, as well as building internal software infrastructure. Ideal candidates have a strong background in robotics, mechanics, and software development, experience with C++ and Python, and a desire to work on challenging technical problems in a fast-paced startup environment.
The Hacker News comments discuss the Dalus job posting, focusing on the unusual combination of FPGA, hardware design, and web technologies. Several commenters express skepticism and confusion about the specific requirements, questioning the need for TypeScript and React experience for a role heavily focused on low-level FPGA and hardware interaction. Some speculate about the potential applications, suggesting possibilities like robotics or control systems, while others wonder if the web technologies are intended for a control/monitoring interface rather than core functionality. There's a general sense of intrigue about the project but also concern that the required skillset is too broad, potentially leading to a diluted focus and difficulty finding suitable candidates. The high salary is also noted, with speculation that it reflects the demanding nature of the role and the niche expertise required.
Tinfoil, a YC-backed startup, has launched a platform offering verifiable privacy for cloud AI. It enables users to run AI inferences on encrypted data without decrypting it, preserving data confidentiality. This is achieved through homomorphic encryption and zero-knowledge proofs, allowing users to verify the integrity of the computation without revealing the data or model. Tinfoil aims to provide a secure and trustworthy way to leverage the power of cloud AI while maintaining full control and privacy over sensitive data. The platform currently supports image classification and stable diffusion tasks, with plans to expand to other AI models.
The Hacker News comments on Tinfoil's launch generally express skepticism and concern around the feasibility of their verifiable privacy claims. Several commenters question how Tinfoil can guarantee privacy given the inherent complexities of AI models and potential data leakage. There's discussion about the difficulty of auditing encrypted computation and whether the claimed "zero-knowledge" properties can truly be achieved in practice. Some users point out the lack of technical details and open-sourcing, hindering proper scrutiny. Others doubt the market demand for such a service, citing the costs and performance overhead associated with privacy-preserving techniques. Finally, there's a recurring theme of distrust towards YC companies making bold claims about privacy.
Artie, a Y Combinator-backed startup building generative AI tools for businesses, is seeking a Senior Product Marketing Manager in San Francisco. This role will be responsible for developing and executing go-to-market strategies, crafting compelling messaging and positioning, conducting market research, and enabling the sales team. The ideal candidate possesses a strong understanding of the generative AI landscape, excellent communication skills, and a proven track record of successful product launches. Experience with B2B SaaS and developer tools is highly desired.
Hacker News users discuss the apparent disconnect between Artie's stated mission of "AI-powered tools for creativity" and the job description's emphasis on traditional product marketing tasks like competitive analysis and go-to-market strategy. Several commenters question whether a strong product marketing focus so early indicates a pivot away from the initial creative AI vision, or perhaps a struggle to find product-market fit within that niche. The lack of specific mention of AI in the job description's responsibilities fuels this speculation. Some users also express skepticism about the value of a senior marketing role at such an early stage, suggesting a focus on product development might be more prudent. There's a brief exchange regarding Artie's potential market, with some suggesting education as a possibility. Overall, the comments reflect a cautious curiosity about Artie's direction and whether the marketing role signals a shift in priorities.
Jazzberry, a Y Combinator-backed startup, has launched an AI-powered agent designed to automatically find and reproduce bugs in software. It integrates with existing testing workflows and claims to reduce debugging time significantly by autonomously exploring different application states and pinpointing the steps leading to a failure. Jazzberry then provides a detailed report with reproduction steps, stack traces, and contextual information, allowing developers to quickly understand and fix the issue.
The Hacker News comments on Jazzberry, an AI bug-finding agent, express skepticism and raise practical concerns. Several commenters question the value proposition, particularly for complex or nuanced bugs that require deep code understanding. Some doubt the AI's ability to surpass existing static analysis tools or experienced human developers. Others highlight the potential for false positives and the challenge of integrating such a tool into existing workflows. A few express interest in seeing concrete examples or a public beta to assess its real-world capabilities. The lack of readily available information about Jazzberry's underlying technology and methodology further fuels the skepticism. Overall, the comments reflect a cautious wait-and-see attitude towards this new tool.
Miyagi, a YC W25 startup, transforms existing YouTube videos into interactive online courses. It allows creators to add quizzes, flashcards, and other learning resources directly within or alongside a YouTube video. This aims to make learning from YouTube more structured and engaging, while offering creators a new revenue stream beyond traditional advertising. The platform handles payment processing and content hosting, providing a seamless experience for both learners and educators.
HN commenters generally expressed interest in Miyagi's approach to creating interactive courses from YouTube videos. Several questioned the long-term viability of relying on YouTube's platform, citing potential copyright issues and YouTube's own educational initiatives. Some suggested focusing on specific niches or partnering directly with creators. The pricing model also drew scrutiny, with some finding it expensive for individual users. Positive comments focused on the potential for educational accessibility and the convenience of leveraging existing YouTube content. The ability to integrate quizzes and interactive elements was seen as a valuable addition. A few commenters offered specific suggestions for improvement, such as incorporating spaced repetition and different learning modalities.
Legion Health (YC S21) is seeking founding engineers to build an AI-powered mental healthcare platform. They're aiming to create a personalized, data-driven approach to diagnosis and treatment, combining the best aspects of human therapists and AI. The ideal candidates are experienced full-stack or backend engineers proficient in Python/TypeScript and interested in tackling the mental health crisis. They offer competitive equity and the opportunity to shape the future of mental healthcare.
Several Hacker News commenters express skepticism about using AI to "fix" mental health, questioning whether it's the right tool for such complex and nuanced issues. Some worry about the potential for misdiagnosis and the ethical implications of relying on AI for mental health support. Others point out the difficulty of collecting accurate and representative data for training such AI models, particularly given the subjective nature of mental health experiences. There's also discussion around the potential for bias in these systems and the importance of human oversight. A few commenters offer alternative perspectives, suggesting AI could be useful for specific tasks like scheduling or administrative work, freeing up human clinicians to focus on patient care. The potential for misuse and the need for careful regulation are also highlighted. Several users questioned the high salary advertised given the company's early stage, while others shared personal anecdotes related to mental healthcare access and affordability.
ParaQuery, a YC S25 startup, launched a GPU-accelerated data processing engine designed to significantly speed up Spark and SQL workloads. Leveraging the parallel processing power of GPUs, ParaQuery offers a drop-in replacement for SparkSQL and PySpark, aiming to reduce query execution times by up to 100x without requiring code changes. The project is open-source and integrates with popular data lakehouses like Apache Iceberg and Delta Lake. It supports various data formats like Parquet and ORC and enables interactive analytics on massive datasets.
The Hacker News comments express cautious optimism and interest in ParaQuery's potential. Several users question the performance claims, especially regarding GPU acceleration for all operations, not just specific ones. They highlight the complexity of query optimization and the challenges of effectively utilizing GPUs for everything in Spark/SQL. Some express interest in specific use cases, like vector databases and large language models (LLMs). Concerns about vendor lock-in with a closed-source solution and curiosity about pricing are also raised. A few commenters share their experiences with similar technologies, mentioning the difficulties of achieving promised performance gains and the importance of transparency in benchmarks.
Synder, a Y Combinator-backed (S21) fintech company specializing in accounting automation for e-commerce businesses, is hiring a Business Development Representative. This role focuses on outbound sales, generating leads, qualifying prospects, and scheduling demos for the sales team. Ideal candidates possess strong communication and sales skills, are comfortable working in a fast-paced startup environment, and have a genuine interest in the SaaS and fintech industries. This is a remote position offering an opportunity to contribute to a rapidly growing company.
Hacker News users discussed the listed salary ($60k-$80k) for the Business Development Representative role at Synder, with many finding it too low, especially for a YC-backed company located in the Bay Area. Several commenters pointed out the high cost of living in the region, arguing that the offered range is insufficient for a comfortable lifestyle, even for an entry-level position. Some suggested the low salary might reflect a commission-heavy compensation structure, while others speculated it might indicate issues with the company's funding or business model. The overall sentiment was negative, with many users expressing skepticism about the job posting and advising potential applicants to carefully consider the compensation before applying.
Google is investing in three advanced nuclear energy projects through its Google.org philanthropic arm. These projects, developed by TerraPower, X-energy, and Core Power, focus on different next-generation reactor designs, including molten salt, high-temperature gas-cooled, and molten chloride salt reactors. The investment aims to accelerate the development and deployment of these technologies, which offer potential advantages in safety, scalability, and waste reduction compared to traditional nuclear power. Google's contribution will support advanced modeling and simulation capabilities to help bring these designs to market faster and demonstrate their viability as clean energy sources.
Hacker News commenters discuss Google's investment in advanced nuclear projects with a mix of cautious optimism and skepticism. Some express hope that these smaller, modular reactors will prove safer and more efficient than traditional nuclear power. Concerns are raised about the timeline and feasibility of these projects, with some pointing to the history of cost overruns and delays in nuclear energy development. Others question Google's motivations, suggesting it's a PR move or a hedge against future energy needs rather than a genuine belief in the technology. There's also a discussion about the role of government regulation and the need for public acceptance for these projects to succeed. Several comments highlight the potential benefits of nuclear energy for climate change mitigation, while others argue that renewable energy sources offer a faster and more cost-effective solution.
Artifact, a YC W25 startup building a personalized news feed, is hiring a Forward Deployed Software Engineer. This role involves working directly with users, rapidly iterating on product features based on feedback, and collaborating closely with the founding team. Ideal candidates are highly adaptable, enjoy a fast-paced environment, possess strong communication skills, and are proficient in full-stack development with a preference for React and Node.js. The position offers the opportunity to significantly impact the product's direction and grow alongside a small, ambitious team.
The Hacker News comments express skepticism and concern about Artifact's "Forward Deployed Software Engineer" job posting. Several commenters question the meaning of "forward deployed," interpreting it as potentially euphemistic for dangerous or unstable work environments, possibly involving military or conflict zones. Others speculate it might refer to embedded systems or working directly with clients. The lack of clarity in the job description is criticized, with some suggesting it's a red flag and a sign of poor communication from the company. A few commenters note the high salary offered, but this is largely overshadowed by the ambiguity surrounding the role's actual responsibilities. The overall sentiment is one of caution and a desire for more information before considering the position.
Tabular, a YC S24 startup, is seeking a founding engineer to help build a collaborative spreadsheet tool designed for complex data analysis. They're looking for someone passionate about developer tools and spreadsheets with a strong understanding of front-end technologies like React, Typescript, and potentially Rust/WebAssembly. The ideal candidate enjoys fast-paced environments and collaborating closely within a small team to shape the product's direction. Experience with data visualization, collaborative editing, or spreadsheet software is a plus.
The Hacker News comments on the Tabular (YC S24) job posting are largely focused on the requested tech stack (TypeScript, React, and Node.js) and its perceived suitability for a data-intensive application. Several commenters question the choice of JavaScript for performance-critical backend tasks, expressing concern about potential bottlenecks and advocating for languages like Rust, Go, or Python with optimized data science libraries. Others defend the choice, citing the large existing ecosystem and ease of rapid prototyping. A few commenters also note the broadness of the "founding engineer" role and discuss the potential challenges and rewards of joining an early-stage startup. Several commenters express interest in the remote work aspect and the focus on tabular data interfaces. Finally, there's some skepticism about the actual innovation being pursued, with one commenter questioning whether the problem being addressed is truly significant.
Exa is a new tool that lets you query the web like a database. Using a familiar SQL-like syntax, you can extract structured data from websites, combine it with other datasets, and analyze it all in one place. Exa handles the complexities of web scraping, including navigating pagination, handling different data formats, and managing rate limits. It aims to simplify data collection from the web, making it accessible to anyone comfortable with basic SQL queries, and eliminates the need to write custom scraping scripts.
The Hacker News comments express skepticism and curiosity about Exa's approach to treating the web as a database. Several users question the practicality and efficiency of relying on web scraping, citing issues with rate limiting, data consistency, and the dynamic nature of websites. Some raise concerns about the legality and ethics of accessing data without explicit permission. Others express interest in the potential applications, particularly for market research and competitive analysis, but remain cautious about the claimed scalability. There's a discussion around existing solutions and whether Exa offers significant advantages over current web scraping tools and APIs. Some users suggest potential improvements, such as focusing on specific data types or partnering with websites directly. Overall, the comments reflect a wait-and-see attitude, acknowledging the novelty of the concept while highlighting significant hurdles to widespread adoption.
OpenAI has agreed to acquire AI startup Windsurf for $3 billion. This marks OpenAI's largest acquisition to date and aims to bolster its development of next-generation AI models. Windsurf specializes in building AI models capable of understanding and generating complex code, which OpenAI intends to integrate into its existing offerings. The acquisition is expected to accelerate OpenAI's progress in areas like code generation, code completion, and software development automation.
Hacker News commenters discuss OpenAI's acquisition of Windsurf AI for $3B, expressing skepticism about the high valuation given Windsurf's apparent lack of public presence or readily available information. Some speculate about Windsurf's potential value proposition, suggesting expertise in areas like vector databases, efficient model training, or perhaps even a revolutionary new AI training paradigm. Others question OpenAI's strategy, wondering if this is a defensive move to prevent competitors from acquiring Windsurf's technology or talent. A few commenters note the increasing consolidation in the AI space and the potential implications for competition and innovation. Overall, the sentiment reflects a mixture of curiosity, doubt, and concern about the long-term effects of such acquisitions.
Databricks is in advanced discussions to acquire data startup Neon, a company that offers a serverless PostgreSQL database as a service, for approximately $1 billion. This potential acquisition would significantly bolster Databricks' existing data lakehouse platform by adding a powerful and scalable transactional database component. The deal, while not yet finalized, signals Databricks' ambition to expand its offerings and become a more comprehensive data platform provider.
Hacker News commenters discuss the potential Databricks acquisition of Neon, expressing skepticism about the rumored $1 billion price tag. Some question Neon's valuation, citing its open-source nature and the availability of similar PostgreSQL offerings. Others suggest Databricks might be more interested in acquiring talent or specific technology than the entire company. The perceived overlap between Databricks' existing services and Neon's offerings also fuels speculation that Databricks might integrate Neon's tech into their platform and potentially sunset the standalone product. Some commenters see the potential for synergy, with Databricks leveraging Neon's serverless PostgreSQL offering to enhance its data lakehouse capabilities and compete more directly with Snowflake. A few highlight the potential benefits for users, such as simplified data management and improved performance.
InstantDB, a Y Combinator (S22) startup building a serverless, relational database designed for web developers, is seeking a founding TypeScript engineer. This role will be instrumental in shaping the product's future, requiring expertise in TypeScript, Node.js, and ideally, experience with databases like PostgreSQL. The engineer will contribute heavily to the core platform, API design, and overall developer experience. This is a fully remote, equity-heavy position offering the opportunity to join a small, passionate team at the ground floor and build something impactful.
Hacker News users discuss Instant's TypeScript engineer job posting, expressing skepticism about the "founding engineer" title for a role seemingly focused on building a dashboard. Several commenters question the startup's direction, suggesting the description sounds more like standard frontend work than a foundational technical role. Others debate the meaning and value of the "founding engineer" title itself, with some arguing it's overused and others pointing out the potential equity and impact associated with early-stage roles. A few commenters also discuss InstantDB's YC association and express mild interest in the role, though the majority seem unconvinced by the framing of the position.
Helpcare AI, a Y Combinator Fall 2024 company, is hiring for various roles including software engineers, machine learning engineers, product designers, and medical professionals. They're building an AI-powered platform to assist healthcare professionals in diagnosing and treating patients more effectively. They seek individuals passionate about improving healthcare with AI and offer competitive salaries and equity. Experience with large language models (LLMs), healthcare data, and fast-paced startup environments is a plus.
The Hacker News comments are sparse and primarily focus on the hiring aspect of the post, rather than the Helpcare AI product itself. One commenter questions the wisdom of advertising engineering roles with such a broad range of required experience (from junior to staff). Another expresses skepticism about the prevalence of AI/ML startups in the current YC batch and suggests the hype around AI may be influencing founders' choices. A third comment simply notes the use of a Google Form for applications, a practice generally considered less professional than dedicated application portals. Overall, the comments offer little substantive discussion of Helpcare AI's mission or technology.
To speed up perceived Office app launch times, Microsoft is implementing a change where core parts of the suite will load in the background during Windows startup. This pre-loading aims to make opening Word, Excel, PowerPoint, and Outlook feel significantly faster, addressing user complaints about sluggishness. The feature, currently rolling out to Microsoft 365 subscribers, can be disabled in settings if desired.
Hacker News users largely criticized Microsoft's decision to pre-load Office applications at startup to improve perceived performance. Many argued this was a poor solution, consuming resources and potentially slowing boot times for a marginal speed improvement. Some suggested alternative approaches like optimizing the Office suite itself or allowing users to opt-in to pre-loading rather than forcing it on everyone. The sentiment was that this move prioritized superficial performance gains over actual system efficiency, echoing past criticisms of Microsoft's bloatware tendencies. A few commenters offered potential benefits, like faster access for frequent Office users, but this was overshadowed by the prevailing negative reaction.
Forty years ago, in 1982, the author joined Sun Microsystems, a startup at the time with only about 40 employees. Initially hired as a technical writer, the author quickly transitioned into a marketing role focused on the Sun-1 workstation, learning about the technology alongside the engineers. This involved creating marketing materials like brochures and presentations, attending trade shows, and generally spreading the word about Sun's innovative workstation. The author reflects fondly on this exciting period of growth and innovation at Sun, emphasizing the close-knit and collaborative atmosphere of a small company making a big impact in the burgeoning computer industry.
HN commenters discuss the author's apparent naiveté about Sun's business practices, particularly regarding customer lock-in through proprietary hardware and software. Some recall Sun's early open-source friendliness contrasting with their later embrace of closed systems. Several commenters share anecdotes about their own experiences with Sun hardware and software, both positive and negative, highlighting the high cost and complexity, but also the power and innovation of their workstations. The thread also touches on the cultural shift in the tech industry since the 80s, noting the different expectations and pace of work. Finally, some express nostalgia for the era and the excitement surrounding Sun Microsystems.
This April 2025 "Ask HN" thread on Hacker News features developers, entrepreneurs, and hobbyists sharing their current projects. Many are focused on AI-related tools and applications, including AI-powered code generation, music creation, and data analysis. Others are working on more traditional software projects like mobile apps, SaaS products, and developer tools. Several posters mention exploring new technologies like augmented reality and decentralized systems. Personal projects, open-source contributions, and learning new programming languages are also common themes. The thread offers a snapshot of the diverse range of projects being pursued by the HN community at that time.
The Hacker News comments on the "Ask HN: What are you working on? (April 2025)" thread primarily consist of humorous and speculative future projects. Several users joke about AI taking over their jobs or becoming sentient, with one imagining an AI therapist for AIs. Others predict advancements in areas like personalized medicine, AR/VR integration with daily life, and space colonization. A few express skepticism or cynicism about technological progress, wondering if things will truly be that different in two years. There are also meta-comments about the nature of these "Ask HN" threads and how predictable the responses tend to be. A couple of users share actual projects they are working on, ranging from software development tools to sustainable agriculture.
Freshpaint, a Y Combinator S19 company specializing in customer data infrastructure, is hiring remote backend and frontend engineers based in the US. They are building a product that helps companies collect, manage, and activate their customer data, aiming to simplify the complex process of data integration. Experience with data-intensive applications and distributed systems is desired for backend roles, while frontend positions require proficiency in modern Javascript frameworks like React. The company emphasizes a fast-paced, collaborative environment and the opportunity to contribute significantly to a rapidly growing startup.
The comments on this Hacker News post are sparse and primarily focus on the "US only" hiring restriction. Several commenters express frustration or disappointment with this limitation, questioning the reasoning behind it and suggesting it unnecessarily limits the talent pool. One commenter speculates it might be due to legal or tax complexities. Another simply points out the lost opportunity to hire globally. There's no discussion of the company itself or the specific roles.
A developer created Clever Coloring Book, a service that generates personalized coloring pages using OpenAI's DALL-E image API. Users input a text prompt describing a scene or character, and the service produces a unique, black-and-white image ready for coloring. The website offers simple prompt entry and image generation, and allows users to download their creations as PDFs. This provides a quick and easy way to create custom coloring pages tailored to individual interests.
Hacker News users generally expressed skepticism about the coloring book's value proposition and execution. Several commenters questioned the need for AI generation, suggesting traditional clip art or stock photos would be cheaper and faster. Others critiqued the image quality, citing issues with distorted figures and strange artifacts. The high cost ($20) relative to the perceived quality was also a recurring concern. While some appreciated the novelty, the overall sentiment leaned towards finding the project interesting technically but lacking practical appeal. A few suggested alternative applications of the image generation technology that could be more compelling.
"Tarpit" startup ideas are deceptively attractive yet ultimately unproductive, consuming significant time and resources without yielding meaningful results. They often involve complex technical challenges with unclear market demand or readily available, superior existing solutions. The YC video advises avoiding tarpits by focusing on simpler initial products addressing proven customer needs, prioritizing execution speed over elaborate features, and validating market interest early and often through user feedback. It emphasizes that elegantly engineered solutions for non-problems are a waste, while even clunky solutions for real problems can be successful. Thorough market research and ruthless prioritization are key to escaping the allure of the tarpit.
Hacker News users discussed the concept of "tarpit ideas" as presented in the linked video. Several commenters shared personal experiences with such projects, highlighting the deceptive allure of seemingly simple ideas that become increasingly complex and time-consuming. Some debated the distinction between tarpit ideas and genuinely challenging but worthwhile projects, suggesting that passion and a clear understanding of the potential pitfalls can mitigate the risks. The idea of "scope creep" was mentioned as a key factor in turning a promising project into a tarpit. One commenter suggested that maintaining a "kill list" of abandoned projects can be a healthy way to acknowledge sunk costs and move on. Others pointed out the importance of recognizing when an idea has become a tarpit and the courage to abandon it. A few users found the video's advice somewhat obvious, while others appreciated the clear articulation of a common problem.
Recover, a YC W21 startup, is hiring a Head of Finance. This role will be responsible for building and managing all finance functions, including accounting, financial planning & analysis (FP&A), fundraising, investor relations, and strategic finance. The ideal candidate has a strong background in finance, preferably within a high-growth startup environment, and is comfortable working in a fast-paced and dynamic setting. They will report directly to the CEO and play a critical role in shaping the company's financial strategy and driving its growth.
Several commenters on Hacker News expressed skepticism about the Head of Finance position at Recover, questioning the relatively low salary ($140k-$180k) for the Bay Area, especially given the expectation of managing a Series B/C fundraising round. Some compared it unfavorably to similar roles at larger, more established companies. Others pointed out the potential for significant equity, given Recover's YC backing and growth stage, arguing that this could offset the lower base salary for the right candidate. A few commenters also discussed the pros and cons of working at a mission-driven company like Recover, which focuses on textile recycling, versus a more traditional for-profit enterprise.
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https://news.ycombinator.com/item?id=44117465
Hacker News users discussed MindFort's approach to continuous penetration testing, expressing both interest and skepticism. Some questioned the efficacy of AI-driven pentesting, highlighting the importance of human intuition and creativity in finding vulnerabilities. Others were concerned about the potential for false positives and the difficulty of interpreting results generated by AI. Conversely, several commenters saw the value in automating repetitive tasks and increasing the frequency of testing, allowing human pentesters to focus on more complex issues. The discussion also touched upon the ethical implications and potential for misuse of such a tool, and the need for responsible disclosure practices. Some users inquired about pricing and specific capabilities, demonstrating a practical interest in the product. Finally, a few comments suggested alternative approaches and open-source tools for penetration testing.
The Hacker News post for Launch HN: MindFort (YC X25) – AI agents for continuous pentesting has generated several comments, offering a mix of skepticism, curiosity, and practical considerations about the application of AI in penetration testing.
A recurring theme is the questioning of how "AI agents" are practically employed in pentesting beyond simply automating existing tools. Commenters express doubt that current AI capabilities can genuinely discover novel vulnerabilities or navigate complex attack scenarios requiring human intuition and adaptability. Some suggest the AI's role is likely limited to handling repetitive tasks like vulnerability scanning or fuzzing, which are already automated by existing tools. They are eager to see concrete examples of the AI agent finding vulnerabilities that traditional methods would miss.
Several commenters raise concerns about the potential for misuse of such a tool. They point out the risk of malicious actors leveraging similar AI agents for offensive purposes, making the overall security landscape more precarious. The discussion touches on the ethical implications and the need for responsible development and deployment of AI-powered pentesting tools.
Some comments delve into the technical aspects, questioning the ability of AI agents to handle the dynamic nature of modern web applications, especially those incorporating complex JavaScript frameworks and anti-automation measures. The challenge of mimicking real-world user behavior and understanding the nuances of different application contexts is highlighted.
There's also a thread discussing the legal gray areas surrounding automated pentesting, particularly regarding the potential for unintentional damage or unauthorized access. Commenters raise the need for clear guidelines and regulations to govern the use of AI-driven pentesting tools.
A few comments express interest in specific features, such as integrations with existing security workflows, reporting capabilities, and the ability to customize the AI agent's behavior.
Finally, some users share their personal experiences with other automated pentesting tools, offering comparisons and highlighting the limitations they've encountered. They emphasize the importance of human oversight and the need for AI agents to augment, rather than replace, human expertise in penetration testing. Overall, the comments reflect a cautious optimism tempered by realistic concerns about the current capabilities and potential implications of AI in the field of cybersecurity.