... backend service. It resulted in a live habit tracker that currently has twenty-three beta users, and I would like to talk about what actually worked and what did not work for me. First of all, Cursor's autocomplete functionality really helped me save some time when I had to write boilerplate code. I simply described in English what I needed to get, and in most cases (about eighty percent), I got the fully functional React components. The rest twenty ...

... tool called Code Tracker AI , built around a simple question: Why is understanding code still the hardest part of software engineering? Debugging, onboarding, reading unfamiliar files, tracing logic these are the moments where engineers lose hours. IDEs give us autocomplete and refactors, but not understanding . So I m building something that acts like a code intelligence layer inside JetBrains IDEs: Understands code context Explains logic and flow Helps with debugging Tracks reasoning across files Reduces onboarding time Works directly inside ...

... right and is more useful than either, and the revised version went up this month, so it's worth twenty minutes before you write your Q4 plan. It's NBER working paper 35275, Demirer, Musolff and Yang - "Writing Code vs. Shipping Code." More than 500,000 GitHub developers, matched against their actual AI usage telemetry rather than a survey, in a matched event study design. The headline numbers are large and I have no interest in arguing with them. Cumulative ... ... effects on commits: 30% for autocomplete

... around it and a tool that stuck a chat box on top because it was trendy. From the listing alone, those two look identical. Curious if anyone else feels this. What's an AI feature you actually use regularly, versus one you tried once and forgot about? And does a listing mentioning AI make you more likely to try something, or less at this point? Comment from Raneen Alawamleh(@raneenalawamleh05): The funniest part is when I forget the app even ... ... someone helping you answer questions and keep up with a meeting. My perspective is good AI, like good technology, does what it does without being loud. I look at how Google integrated gemini into their natural search experience, autocomplete

... Nobody questions someone's competence for using a calculator, a spellchecker, a design template, or an IDE autocomplete. Using a tool to help execute an idea is normal everywhere else. But the second writing involves AI even when the person had the actual idea and used AI just to help draft or refine it there's an instant judgment that doesn't apply anywhere else. Genuinely curious what people think: is this really about output quality, or is it more ...

... inbox. Shortcuts for triage, reply, and mark as done mean i rarely touch the mouse. That's most of an hour back on a heavy day. 2. Cursor If you tried Cursor in 2024 and decided it was fancy autocomplete, that opinion is out of date. You describe what you want, it edits across files, runs the tests, reads the errors, and tries again before it shows you anything. Founders and engineers i know run two or three of these ...

... Genuinely curious how others here draw this line. I've been letting an AI coding agent (Claude Code) handle a growing share of day-to-day engineering on a side project not autocomplete, actual multi-step changes across the codebase, including schema migrations on a live production database. What made that feel safe enough to actually do: - It states what it's about to touch before touching it, so a bad plan gets caught before execution, not after. - Rules written ...

... About a week ago, I built a free YouTube Keyword Tool to make keyword research faster and more practical for creators. Most keyword tools mix data from Google Search or show generic suggestions. This tool focuses specifically on YouTube autocomplete , helping creators discover phrases people are actively searching for on YouTube. It currently includes: Short-tail and long-tail keyword filters Popularity-based sorting Hundreds of keyword suggestions from one topic Instant CSV export Keyword selection for YouTube ...

... nothing, the reviewer's normal experience becomes an empty screen, and empty screens train people to expect empty. Whether the one that is not empty gets read properly on day forty is an open question. It still beats the alternative, because a difference against a background of silence is about as salient as anything gets. And yes to the small pile. Most of what gets called judgement is work nobody has bothered to make mechanical yet. Comment from Raffay Sajjad ... ... there's no shared webhooks folder they both sit under. so the glob fix doesn't even apply to the three i have today, they were never colocated in the first place. which proves your enumeration vs

... July 14. Today's release is a direct result of that: 1.0.12 ships the tagging system several of you asked about in the comments, plus two other things people kept running into. What's in 1.0.12: Tags: free-form, autocomplete-first note tags with color coding and a filter popover in the library (multi-select, so you can narrow by more than one tag at once). Tables: paste one in and it's preserved instead of turning into plain text ...

... they relate to a business or product. A lot of this can only be learned through exposure. It creates an interesting dynamic for creating products that scale. Comment from Kseniia Shevchenko(@kseniia_shevchenko2): The craft hasn t disappeared autocomplete just developed opinions Writing code may be faster now, but knowing what to build, recognizing confidently generated nonsense, and keeping production alive at 2 a.m. are still very much engineering. Comment from Azouzi(@azouzidesign): Product designer here. I can't speak ... ... watched this play out with our own engineering team too. The syntax-level stuff got faster. What got harder, and honestly more valuable, is knowing when an agent-generated architecture will hold up under real production load vs

... solo founder behind TxDesk. I built it around one idea: in crypto, a confident wrong answer costs you your wallet. A general AI model answers from training data with no live view of the chain, so it autocompletes something fluent and possibly wrong. When the cost of being wrong is your money, the model cannot be the source of truth. The chain has to be. So TxDesk reads first, then talks. It fetches your real transaction and decodes the actual ...

... breaking, and so on. - Vaizle - I work with Vaizle, but it has very easily emerged as my fav platform. Not even lying. I can keep track of ad performance, check what competitors are posting on social. And best part is that I can feed it my own website + competitors

... first time in decades It now expands to handle longer, more complex queries and accepts text, images, files, videos, and open Chrome tabs from a single entry point . It also includes AI-powered suggestions that go far beyond traditional autocomplete . For SEOs, this signals something important: optimizing for short keyword queries is increasingly beside the point 3. Generative UI means Google builds the experience on the fly Instead of returning a list of ten blue links, Search can now generate ... ... factual, structured, and authoritative enough to be cited inside those generated experiences. 3. Your brand's entity footprint now matters across personalized contexts. The same search for "accounting software" will yield different results for a solo founder versus

... paying for usage if it saves meaningful engineering time, but it definitely changes how casually people will use agents. Comment from fmerian(@fmerian): curious what are your preferred models? @MiniMax ? @Qwen ? else? Comment from fmerian(@fmerian): @bullterriertime  what alternative to @Github Copilot would you recommend? Comment from fmerian(@fmerian): no longer using @VS

... something I've been building for 6 months. AUREM CTO Dev auremcto.com The problem: every AI coding tool stops at "here's your code." You still copy, paste, test, commit, push. That's not an AI engineer. That's autocomplete. What AUREM does differently: Reads your actual repo files (not hallucinated code) Writes the fix Runs 25-pattern security scan Commits directly to your GitHub branch Returns commit SHA in chat No VS

... have actually diverged in outcome in the ledger so far and if it's inferred, what's your cold-start before a single divergence has been observed? Comment from Alexander Bering(@alexanderbering): @aadilghani  The reason "edit vs. tell-it-to-revise vs

... Keypad (46 upvotes) sits next to your keyboard with Claude integration. Video calls: Mina Meeting Assistant (47 upvotes). Text threads: folk (51 upvotes). Chat windows: Databox MCP (39 upvotes) plugs business data into Claude via Model Context Protocol. Mac autocomplete: Typeahead (22 upvotes). The pattern is clear: shipping AI as a new app is the slow path. The fast path is grafting onto a surface the user already touches. The cost of building a standalone AI app dropped ...

... Morning Pages point tracks. I tried it for a while and kept catching myself slowing down mid-sentence to reword things. Kind of defeats the whole thing. Comment from Nolan Vu(@nolan_vu): @hayleyapp  Yeah, the hearing vs writing split tracks. I'm definitely in the "write it down and it just sits there" camp. I've tried Morning Pages, Notion journals, the works. None of it really clicked until I started just talking through problems out loud, even ... ... than writing them, reading it back is just never going to hit the same way. The "layering AI on top of a journal" thing was the trap I was most trying to avoid. Most of those apps are just autocomplete

... prefer to review the output of agents, rather than individual actions, and run one or more sessions in parallel. What type of developer are you when working with AI coding agents? For context, when @Kilo Code launched their new @VS Code extension last week , with parallel agents, inline diff reviewer, and multi-model comparisons, some users actually wanted more control back. While the team is working on multiple improvements , like better diffs before you approve and permission flow fixes ... ... from MD Amirul Islam(@1mirul): Nice prompt this is exactly the kind of question shaping how we ll work in the next few years. For me, the best way to use AI coding agents is as collaborative engineers, not autocomplete

... specific ways: Agent-Level Interception: LineageLens sits at the proxy layer and intercepts API tool calls (like Anthropic's tool_use or OpenAI's apply_patch). It inherently captures larger, intent-driven agent workflows rather than keystroke-level IDE autocompletes. State Machine Filtering: Because we track the final outcome of every edit, the dashboard defaults to hiding "Rejected" or "Errored" proposals. The database logs the hallucinations if you ever want to analyze them, but the primary review UI only surfaces ...

... near future that integrates 350+ tools into a single system, including 24/7 monitoring tools for business/company risk and management, as well as tools to integrate AI into laboratory machines and other medical devices. The main focus is: - Advanced autocomplete for coding (faster, more context-aware than traditional AI coding assistants) - Medical intelligence support (helping analyze data, summarize cases, and assist decision workflows) What makes this AI different: Deep tool integration Instead of just chatting, the AI can directly use hundreds ... ... tools to execute tasks in real workflows. Smarter coding autocomplete

... edit labels inline. Better organization, better visibility. Fixes & Improvements We've also focused on stability and polish this release: File Explorer bottom row clipping resolved Cross-window copy behavior corrected LSP recovery process improved for better session resumption Autocomplete context refined for more accurate suggestions Editor tab strip UI polished View menu reorganized for better navigation on Windows and Linux Download v0.10.21 now and experience the improvements firsthand. https://invoke.yugin.co/downlaod Comment from Ghost Kitty(@ghost-kitty-9637647): Comment ...

... nika  Agents are fast and useful but speed isn't understanding. Using the calculator analogy again it solves equations faster than any human but it doesn't know what a number is. Current agents chain together hundreds of autocomplete steps very quickly and the output looks like thinking, but there's no comprehension behind it remove the prompt and the system does nothing because it has no intent. Whether that gap closes with AGI is genuinely unknown the problem ... ... understand human intelligence well enough to measure the gap. So the question "will AI work without us" has a boring answer the technology we have now literally can't because it's architecturally incapable of independent action. It's autocomplete

... Last month, I did something that felt slightly insane. I took our product description, fed it into ChatGPT, and asked it to build a competitor. Not a parody. A real competitor