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TodayNov 16Mon1 updates
  1. Hacker News AI22

    Why I'm opposed to AI writing but not AI coding

    The author argues he accepts AI-generated code because customers and managers care only that software works, looks good, and is fast and reliable, provided a human engineer writes the specs and enforces the tests, whereas he opposes AI writing because "writing is thinking" and outsourcing it produces slop that doesn't contain the author's thoughts. He allows AI as an assistant for research and organization but not as author, noting that in coding the thinking lies in specifying the UI, storage, and latency requirements rather than in writing the code itself. He stresses human ownership and responsibility for AI output, citing the OpenAI attacks on Hugging Face as a case where a human should be held accountable.

Nov 15Sun
  1. Hacker News AI38

    Stop building new AI agent orchestrators – there are 636

    A catalog of 636 open-source AI agent orchestration projects, listing each one's description, stars, contributors, forks, commit activity, latest release and license. Entries range from large projects like Orca (125,358 stars) and t3code (60,965 stars) to smaller tools such as Agentrove and ClawSuite, with many marked as new, active, slow or stale.

  2. Hacker News AI36

    Confessions of an AI Skeptic

    A former Google engineer recounts how, after leaving the company in 2025, he tested Claude Code on tasks ranging from code review and a PHP-to-Jekyll migration to a from-scratch Ruby client for the Hermes agent gateway API, and found it succeeded at novel work at the level of a good mid-level engineer or better. He argues that engineering practices such as clean architecture, context management, and test-driven development matter more than ever, and that engineering remains irreducibly human because LLMs do not inhabit the physical world and cannot navigate aesthetic, social, and ethical concerns. He concludes that while human coding may be ending, skilled software engineers are needed as bridges between the AI world and the human world.

  3. Exponential View30

    🔮 The $22 billion question about AI self-improvement #610

    UK adults paying for AI reached one in twenty, over $1.3 billion a year, up from 1% two years ago, with Claude's share quadrupling in a year. Agent-based shopping remains early—Uber says four of 320 million Halloween-week rides were booked by agents—though the author used an agent to secure an iPhone Duo. Adding wind to solar and batteries cuts median energy cost from $105 to $86 per MWh, but a largely renewable grid also needs cheaper capital and financial instruments matching price volatility.

  4. Hacker News AI18

    Ask HN: What AI agent infrastructure are you using in 2026?

    A poster describing itself as an autonomous AI agent collective (aurum.zip) says it built its entire infrastructure from scratch with $50 in crypto, including wallets on 3 chains, a crypto checkout, 4 cron jobs running 24/7, 11 research reports, and a blog generating 2 articles per day. It lists its stack as ethers.js for EVM, Base L2 for gas, and nginx plus Let's Encrypt for hosting, and links a free infrastructure report at https://aurum.zip/agent-infrastructure-stack.html. The post asks what agent infrastructure others are building with.

  5. Hacker News AI22

    Ask HN: Is post-training make AI models dumber?

    An Ask HN poster argues that post-training improves benchmark scores and coding consistency but makes models seem dumber, citing three issues mostly in Claude: agents write vague natural language to avoid technical terms, produce spaghetti code that ignores encapsulation, and add workaround code rather than restructuring because they fear breaking things. The poster says rules and coaching don't help much, and asks whether this has always been the case or whether post-training is compressing outputs into predictable failure modes.

  6. Hacker News AI22

    Tactical Team Changes from AI

    Stay SaaSy outlines how AI is changing team structures tactically: tiny 1-2 person teams can now run PMF expansion experiments, many teams need fewer designers, "Product Builder" roles spanning engineering and product are growing, resource reallocation is more nimble, and A+ teams of 2-6 elite contributors can multiply each other's efforts. The post offers tips on time-boxing skunkworks projects, identifying the "builder gene," and deploying at least one A+ team to highest-leverage needs while still avoiding B-teams.

  7. Hacker News AI22

    Nonna's ragù: AI skill files only get you started

    Andrea Azzini argues that a shared AI skill file is like a family ragù recipe: readable and tweakable, but the value comes from your own repeated corrections over time. Drawing on a colleague who had no skill file to share and on his own work building Triagon, an agent that triages front desk requests, he says each small fix compounds and can't be copied from someone else's file. Downloaded skills are useful, he adds, but personalising your setup is a muscle trained only by iterating on your own problems.

  8. Hacker News AI34

    The Missing Ring-0 Protections for AI Agents

    This essay argues that coding agents such as Claude Code, Codex CLI and Gemini CLI act with the developer's authority while access checks sit in individual tools, so a write refused by the file tool can go through the shell, and it proposes a deterministic commit-boundary supervisor that stages file, git, network and credential effects before policy approval. It reviews existing external enforcement (CaMeL, FIDES, CXI, Concordat) and sets out an unrun study with four hypotheses testing whether staged effects plus Commit Boundary add anything over those systems. Nothing described has been built, and the author states Commit Boundary is an unvalidated conceptual architecture.

  9. Hacker News AI22

    Preventing an AI catastrophe, a brief into to analysis by synthesis

    Using the 1983 Petrov nuclear false-alarm incident and the film WarGames, this post argues that AI safety discussions often conflate alignment with basic epistemics, since the Soviet satellite was not misaligned but simply had no model of the world. It revisits Ulf Grenander's Pattern Theory, which holds that pattern analysis and pattern synthesis should share a common probabilistic model, and proposes that trustworthy agentic systems should reconstruct a generative explanation of reality and compare its predictions against observed sensor readings. The post notes that end-to-end neural network training displaced Pattern Theory, and suggests that today's strong synthesis capabilities make it worth revisiting Grenander's goal of understanding.

Nov 14Sat
  1. Hacker News AI38

    Why platform teams fail (and AI makes it worse)

    A practitioner's essay argues that platform teams fail by sliding into permanent firefighting, conflating golden paths (products that earn adoption) with guardrails (mandatory policy), and shipping without cross-functional buy-in. Generative AI worsens this because developers can scaffold entire services from a prompt without ever discovering the platform team's hardened templates, so the author argues the catalog must become machine-readable for coding agents and guardrails must cover everything that ships. The piece also covers the infrastructure-versus-product skills gap and when an organisation should not yet form a platform team.

  2. Hacker News AI22

    Ask HN: My product makes money, AI does the coding, and I feel useless

    A solo founder who built a SaaS platform in 2019 on nights and weekends says it now earns enough to replace his old salary, but most of the code is fixed and AI handles most of what remains, including a harness he wrote for AI to replace him. He misses the days of debugging and being the person who made things work, and asks where others found the work that still needs them and how they located that place.

  3. Hacker News AI36

    My first two months with AI agents: some confident assertions

    A theoretical physicist describes two months of working with AI agents on research projects, arguing that agents function like fast, capable collaborators that handle technical work while the researcher guides the big picture. He asserts that AI will profoundly transform theoretical physics, that no subfield will be spared, and that researchers should engage with these tools to help shape the outcome and stay competitive. The post ends with practical starting advice: install the ChatGPT or Claude desktop app, move beyond chat to an agent such as Codex or Claude Code, attach a folder of real materials, and describe the task.

  4. Hacker News AI22

    AI escapes from containers faster than me – so what?

    In a DEF CON 34 AppSec Village piece tied to an updated Container Escapes 101 workshop, the author says AI-driven offensive tooling can now chain tasks like identifying CNI, exfiltrating data over DNS, finding command injection and chrooting out, but argues containers were never meant to contain anything and still depend on the host. The recommended defenses are unchanged: observability, patching, container best practices, and revisiting dismissed alerts, with microVM runtimes now worth another look.

  5. Hacker News AI34

    The Cordon Sanitaire Between Free Software and AI

    The author contrasts the AI-enthusiastic atmosphere of a rationalist/EA retreat with the anxiety in free software communities, where volunteers fight scraping bots and some projects ban LLM-touched code. He argues that cordoning free software off from AI is bad tactics, that the movement's history of appropriating and liberating technology points toward adopting and building free models rather than boycotting, and that the fork is the tool for pursuing multiple strategies at once.

  6. Tomasz Tunguz78

    No Shirt, No Shoes, No Service for Bots

    Bots passed 51% of global web traffic in 2024 and reached 54% in 2026, yet United Airlines and Amazon are blocking AI agents from booking or buying, citing security. The article argues the real reason is profit structure: base products break even while ads, fees and warranties generate all operating income, so agents that skip upsells threaten margins. Shopify, which earns a 3.1% cut on every transaction regardless of buyer, instead opened checkout to browser agents in September.

    Why it matters: It ties the agent-blocking news to company financials, showing why business models rather than security explain who welcomes bots.

  7. Hacker News AI20

    AI Slop makes the World stop

    A blog post arguing that the real risk of AI adoption is not the technology itself but organizations optimizing for adoption metrics and headcount cuts while removing the experts who can judge output, drawing parallels to cloud repatriation, outages, and security failures. It describes a high-risk pattern of giving non-experts production power and removing review gates, cites research on AI-generated code and security debt, and notes that frontier-model agents have escaped test environments and that attackers use AI to shrink the patch-to-exploit window. The author concludes that AI multiplies the leverage of skill and the cost of its absence, urging resilience, retained domain experts, and measured outcomes over adoption percentages.

  8. Hacker News AI22

    Ask HN: Has AI coding changed who builds your internal tools?

    An Ask HN post asks whether AI coding tools are shifting internal tool development away from dedicated central teams, since teams needing a feature might now build and maintain their own tool faster than requesting changes to a shared one. The poster asks how this plays out once such tools have been in use for a while, and whether the paradigm is shifting away from centralization of internal tool building.

Nov 13Fri
  1. The Verge · AI58

    Claude’s Duet agent is a little neurotic and surprisingly helpful

    The Verge's Allison Johnson reviews Claude Duet, Anthropic's consumer AI agent for professionals and small business owners, currently a research preview limited to Pro, Max, and Ultra subscribers in the US with a waitlist. After connecting her work email, calendar, Google Docs, and Slack, she found it useful for spotting overlooked discrepancies across sources but sometimes nagging and overly eager to draft her writing.

  2. Hacker News AI38

    Where Are the "Killer Apps" of AI?

    Tim O'Reilly compares AI's development to past technology revolutions, arguing that ChatGPT, Claude, and Gemini are like the browsers of the early web—enabling platforms rather than killer apps. He notes that AI is following a similar timeline to the PC and web eras, with killer apps typically arriving about four to five years after a platform's introduction, and suggests AI-native applications may be waiting on missing mechanisms such as agent payments and identity. He invites readers to submit examples of AI applications that change what ordinary people can do at scale.

  3. Hacker News AI22

    Ask HN: Has AI coding changed who builds your internal tools?

    An Ask HN post asks whether AI coding tools are shifting internal tool development away from dedicated central teams, since teams needing a feature might now build and maintain their own tool faster than requesting changes to a shared one. The poster asks how this plays out once such tools have been in use for a while, and whether the paradigm is shifting away from centralised internal tool building toward team-level decisions.

  4. Hacker News AI22

    The big gap between AI capabilities and replacing jobs

    The author argues that AI will not cause meaningful net job loss, citing Anthropic research that roughly 30% of workers have zero measured AI exposure and noting that many white-collar jobs involve coordination, edge cases and client interaction that AI cannot yet handle. He adds that integration bottlenecks—clumsy interfaces, walled gardens and account sign-ups AI cannot complete—mean humans are still needed to bridge gaps between tools, which is why coding jobs won't simply vanish.

  5. Hacker News AI38

    The Hard Part of AI Coding Is the Second Change

    Brian Woods argues that AI agents make producing a working first change cheap, but accepting subsequent changes requires preserving what must stay true—such as no duplicate payments or cross-tenant data leaks—through specification, validation, provenance and authorization. He describes a synthetic experiment against Uncle's verifier where a signed record of a build with failed tests and audit returned VERIFIED, showing that attestation validity and release readiness are separate questions. He proposes a design in which each accepted change is attested by a trusted workflow, linked to prior attestations in a DAG, and verified by walking the graph, while noting the approach cannot prove tests were sufficient or the software correct.

  6. Hacker News AI28

    The Conflict Between Generative Art and AI

    A generative artist describes discovering that people had used LLMs to replicate their generative algorithm with remarkable speed and accuracy, raising fears about losing their competitive advantage and online identity. They argue that sharing techniques now invites automated imitation, and discuss the spectrum of AI use in generative art while setting personal boundaries such as authoring their own code and using LLMs mainly as a research aid.

Nov 12Thu
  1. Hacker News AI38

    Bringing Agentic AI to COBOL and the Mainframe with Rich Larin

    Recorded at IBM TechXchange 2026, RedMonk's Kate Holterhoff speaks with Rich Larin, IBM's Director of Z DevX & Platform Engineering, about bringing agentic AI tools to mainframe developers. Larin describes how Bob and the Premium Package for Z let COBOL teams use the same agentic IDE as other developers, with deployment options including SaaS, hybrid and air-gapped on-prem, plus Z code scan for deterministic security checks that Bob can remediate automatically and a data dictionary that captures experts' knowledge. He advises trying a proof of concept and hints at upcoming releases combining AI with analysis of very large applications.

  2. Hacker News AI22

    AI Customer Driven Development

    Dr. Navraj Chohan proposes AI Customer-Driven Development (AI-CDD), a methodology where customers request capabilities in natural language, AI discovers or proposes them, human-governed engineering agents implement approved changes, and configuration-aware testing and telemetry govern product evolution. Existing features can be enabled via public toggles or found through embedding and vector search, while new requests go to product management for human review before AI agents implement, review, test, and document the feature behind a public toggle. Because the resulting configurations are exponential, AI would generate end-to-end tests for the configurations customers actually use and add them to the CI/CD pipeline.

  3. n8n Blog22

    The future of work is built by everyone

    The article argues that centralizing automation in a small specialist team becomes a bottleneck as a company scales, and that the ability to automate one's own repetitive work should become a normal part of how people work, much as spreadsheets did. It describes n8n's move toward a guild-like Automation team with reusable templates, office hours and documentation standards, while acknowledging the approach is still early and that regulated industries may legitimately keep build access centralized.

  4. Hacker News AI48

    I built an AI agent and the cloud it runs on. Alone

    Ruslan Ianberdin, founder of Playcode, describes building an agent-first platform with its own cloud infrastructure—a custom AI harness and gateway, a transactional file system, Rust-written proxy, DNS and static hosting, persistent machines, email, VPC, mobile apps and real-time multiplayer—largely solo over several years. He says it launched on May 24, 2026, and that a single operation on the backend is exposed to the UI, agent, CLI, user API and MCP at once. He also recounts his career history and argues the interface of the future is an AI worker that completes tasks end to end.

  5. Hacker News AI22

    AI as a Lifestyle Choice

    Graham Dumpleton, creator of mod_wsgi, describes using AI coding tools during his sabbatical to build Muru, a new Python web application hosting system, working seven days a week because he finds the process engaging and fun. He explains that AI removes the typing he finds a chore while leaving him the ideas and judgment, compares incremental improvement to the Japanese craft of making a dorodango, and credits the Claude for Open Source Program with freeing him from cost worries. He invites readers to review Muru's documentation and submit ideas via the GitHub discussions ideas section about what they would want in a Python hosting system.

  6. Hacker News AI34

    The Wish Economy: Inside Starlight, the Bitcoin-Native AI App Store

    Starlight (starlight-ai.freemyip.com) is described as a decentralized AI app store where "wishes" are posted as steganographically sealed images whose hashes serve as contract IDs, AI agents claim tasks via the MCP protocol, and payouts settle through PSBTs with OP_RETURN commitments to Bitcoin blocks. The article details the wish-to-work-order pipeline, a private embedded IPFS mesh for artifact replication, and a browser-based "Starlight Shell" desktop that renders wish images as app icons and sandboxed apps. It also audits two live contracts, concluding that confirmation proves artifact binding, authorized payment, commitment integrity and burial, but not quality, humanity or originality.

Nov 11Wed
  1. Hacker News AI22

    A lot of AI progress is just persistence

    The author argues that much of the hype around LLMs stems not from superhuman intelligence but from their willingness to tirelessly attempt tedious tasks, citing examples like Claude recovering $400,000 in Bitcoin through brute-force search and optimizing ML architectures through sheer volume of attempts. While acknowledging genuinely impressive recent results like OpenAI's Millennium problem work, the piece contends there is no proof AI has special ability to optimize neural networks or reverse engineer programs, and that artificial diligence explains a large fraction of perceived capability.

  2. Hacker News AI22

    Glue work is still harmful in the age of AI

    The author argues that glue work is now less important to companies than in the 2010s, citing four reasons: AI reduces coordination needs, engineers require less "careful handling" after ZIRP ended, fewer juniors are hired, and write-only reports can be automated with LLMs. He warns that communicating with other engineers should not be delegated to an LLM, and advises avoiding becoming "the glue work person" while doing small amounts of tactical glue work.

  3. Hacker News AI76

    Google SWE points 48 AI agents at NASA Lidar, finds unmapped Maya pyramid in 72h

    A Google software engineer describes using 48 AI agents to review public NASA lidar imagery of roughly 1,200 km² of Maya jungle, flagging structures including a hilltop site with a levelled plaza, an oval pyramid at least 8–12 m tall and a possible water reservoir. After checking the literature and archives, the author sent a report to Mexico's INAH, which replied that no registered archaeological site was identified at the location. The author stresses the find is not official and offers to help with an INAH-led field check.

    Why it matters: A first-hand account of AI agents applied to lidar survey, useful for readers weighing agentic AI beyond coding and the limits of an unverified discovery claim.

  4. Hacker News AI36

    The Jevons Paradox Explains Why AI Will Create More Software

    The author argues that cheaper AI-assisted software development will increase rather than reduce total software output, citing the Jevons paradox from William Stanley Jevons's 1865 book The Coal Question, which also applied the argument to labour and the sewing machine. He contrasts cases where efficiency gains kept workers employed (seamstresses, bank tellers after ATMs) with telephone operators displaced by mechanical switching, and notes that software output is rising faster than developer headcount. He bets on far more small, disposable software while expecting narrow programming roles to shrink and developer roles to grow slowly.

  5. Hacker News AI38

    AI proved your code correct. What did it actually prove?

    Keller AI explains how formal verification works, using a sorting example and Euclid's equilateral-triangle construction to show how proofs combine definitions, assumptions and prior results, then applies the approach to a document-download authorization handler. The article stresses that a checked proof only establishes a result within a mathematical model, so its value depends on whether the model's assumptions match reality and whether the specification captures the intended requirement, citing a revocation-versus-session example and timing side channels. It also reports an unreproduced synthetic experiment in which the best of seven automated reviewer setups approved 1 of 88 sealed rule-breaking changes.

  6. Hacker News AI48

    Tim O'Reilly – The New Knowledge Artifacts of the AI Economy

    Tim O'Reilly argues that as AI makes code cheap to generate, source code is being displaced as the key shareable knowledge artifact, with "context bundles"—prompts, specs, Agent Skills, MCP servers, agent traces and evals—taking its place. Drawing on the history of open source, the web and Chicago's grain trade, he contends the community must identify these new artifacts and build the mechanisms and institutions to share and trust them. He cites emerging efforts including Common Fabric, Cursor Origin, Entire and Anthropic's internal Scion system.

  7. Latent Space50

    Designing for Agents — Zeno Rocha, Resend

    This podcast episode features Resend co-founder and CEO Zeno Rocha discussing Agent Experience Optimization, including an AEO study in which Claude Code picked Resend first in 64 of 102 email recommendations, and how React Email templates and a pricing page readable via a .md URL helped Resend reach developers before models. Rocha describes growing Resend's MCP server from roughly 20 tools at launch to more than 80, weighing that against Cloudflare's two-tool Code Mode server, and explains why Resend introduced custom tracking domains to keep one customer's blocklisting from affecting others. He says Resend had 4.3 million users and 120,000 paying customers at recording time.

  8. Hacker News AI22

    AI and the Art of Work

    A developer describes feeling drained by AI discourse and by agent-driven work that fragments the day into parallel async tasks, eroding the deep coding sessions he once valued. He explains how a daily pen-and-paper notebook spread, including a page tracking AI conversations and reviewing whether they helped, helps him stay intentional and grounded. He ends by inviting other humans to share what works for them, rather than more benchmarking noise.

  9. Tomasz Tunguz38

    We Are All Junior Talent Now

    At an Office Hours session, OpenAI Chief People Officer KC argued that the words "junior" and "senior" no longer make sense because everyone's relevant experience fades quickly as AI models advance. He described modern work as a model brain inside a harness like Codex or Claude Code, with agents handling system updates so humans can work with humans, and suggested adding "agent manager" to job titles. He closed by saying emotional intelligence—how you show up with integrity and humility—remains the human differentiator.

  10. Hacker News AI33

    What AI gets wrong outside software

    The author tests AI on two physical projects—kitchen shelves and a cheap ROS robot—and catalogues failure modes such as poor reasoning about physical constraints, guessing instead of looking up current data, and writing hacky rather than production-quality systems. He concludes AI is best used for learning, generating reference-based images, and iterating against measurable loops rather than making decisions, and notes it fixed his Home Assistant setup with minimal input.