... loop from scratch no LangChain, no AutoGen. Mainly because debugging tool-routing failures through someone else's abstraction layer was more painful than writing my own. Curious how many of you building AI products have made the same call, vs leaning on existing frameworks and whether you regret either direction. 2. Made the task scheduler survive the app closing entirely. Instead of an in-process scheduler that dies the moment you close the app, I integrated directly with Windows Task ... ... with how fast it runs. If you've tackled local voice pipelines, I'd love to compare notes on what held up and what didn't. The product itself (Sidus-Agent autonomous, voice-enabled, tools/plugins/connectors/scheduler, spawns sub-agents for parallel

... them costs you in control and compliance, and how to sequence the work so your product team is not waiting on the pipeline. Four parts, sixteen sections, 24 pages, free: How wearable data reaches your backend: cloud OAuth vs mobile SDK, and why most production products run both Build, buy, or self-host, with the compliance implications of each Running it in production: observability, security, consent, CGM, health scoring, and the AI layer A realistic timeline built around three parallel

... instead of sprints Show the team a clickable, living interface instead of a static image Shorten the distance between an idea and real user feedback I've been working this way myself for the past year: designing and, in parallel, taking things far enough that a developer isn't left interpreting a mockup, they're refining something that's already close to functional. It changes the role itself, from "the person who draws things" to "the person who brings ... ... real edge: their decisions reach users faster, and their value to startups, especially early-stage ones, goes up significantly. Has anyone else been exploring this? Curious what tools you're using and what's actually speeding things up versus

... keep seeing tools talk about how many agents they can run in parallel or how much of the backlog they can take on. But every additional agent also creates more work to review, more decisions to make and more places where something can quietly go wrong. At some point, the person supervising them is no longer properly checking the work. They are just trying to keep up with it. So I m starting to think agent count is the wrong ... ... measure. What matters is how much verified work gets completed without creating another pile of work for the human overseeing it. Has anyone found where that tipping point is? Comment from Rabnoor Singh(@rabnoor_s): i ran four in parallel

... leap forward? I see true evolution in qualitative shifts approaches that deliver fundamentally better outcomes. An AI agent is essentially the same underlying LLM with the exact same core constraints. What actually changes if multiple models write code in parallel? At best, we get raw speed by splitting a project into subsystems where each agent operates in its own narrow vector space. But in real-world production, subsystems are never truly isolated. Agents, just like base models, cannot hold ...

... KriptaCorp a Brazilian tech company building software around one principle: your data belongs to you, not to the platform. We're a small team building an ecosystem of tools: Kripta-Timer a time structuring instrument with 16 independent parallel timers. No urgency logic, no streaks, no pressure. Live at kripta-timer.kriptacorp.com Kripta-Organizer a local-first knowledge organizer. Think second brain, but your data stays on your machine. ARK Docs intelligent document management for businesses and law offices. Base ... ... backend infrastructure platform (BaaS), built as an alternative

... canonical passage, compare classical and modern translations, ask narrow questions about specific terms, and verify generated explanations against the text and trusted references. I built RuShiWoWen ( ) around that source-first approach. It includes 4,515 CBETA texts, parallel reading, contextual AI explanations, Buddhist Q&A, and Chinese, English, and Japanese interfaces. https://rushiwowen.co/ I would especially appreciate feedback on whether the parallel

... version you're pinned to, the thing your teammate said in standup all invisible unless the delegation prompt spells them out. Which is why fan-out works great for reading and searching, and keeps failing for parallel writing: two clones writing code make small conflicting decisions about naming, style, and edge cases, nobody wrote the assumptions down, and the merge is where it dies. Cost reality check, since this is the part nobody quotes: Anthropic's engineering blog put agents ... ... roughly 4x the tokens of a chat session, and multi-agent systems at roughly 15x. Parallel

... really underestimated how hard it would be to pick one. Before launch, I was considering things like: Will users trust something that processes their messages with a model they have never heard of? What is the real uptime record, versus the claimed one? Do I go cheap/free , or pay more for something that will last longer? Self-hosted? Or just ride on someone else s frontier model and take their roadmap? I took a solution and moved ... ... realizing the model itself was the problem. It turns out it was being decommissioned that October, and apparently a silent outage is how that gets communicated. I re-engineered the architecture to always have a backup model running in parallel

... keep going on the harder problem underneath it. We've been building ClawTeams, an IM-native platform where you describe an outcome to a "team lead" agent and it splits the work across specialist agents that run in parallel, inside the chat tools you already use (Slack, Telegram, WeCom, DingTalk, Lark). I wanted to share what we're working on and get this community's take, because the deeper we get the more convinced I am that the hard problem ... ... each time. Money and anything touching production are the other two, but the byline one is the one I'd never soften, because a bad deploy is revertible and a bad sentence in my voice isn't. On manager vs

... most of the fun is in that phase before things start feeling like work. Keep building the worthless ones, that's how the good instincts show up. Comment from Kidder(@hellokidder01): @omri_ben_shoham1  Yeah, the "thinking vs blocked on approval" distinction is the hard part. A bell that fires on every pause becomes noise fast; one that only fires on real blocks needs to actually understand what the agent is doing. That's basically why I ended ... ... question then becomes: when one of those does fire, how fast can the human re-enter? Standing authorization reduces the volume; a good re-entry path handles what's left. Curious what categories your operator ended up pre-authorizing vs

... finished 30 minutes ago and I wasted the half hour. Or it sat waiting on a yes/no I never saw. Or the fun one, it happily ran something I would never have approved. The more agents I run in parallel, the worse this gets. Babysitting three terminals is impossible. Trusting three terminals blindly is worse. So I want to know where everyone else draws the line: - Which camp are you in, babysit or let it rip? - Do you have ... ... where "let it run" should end and "ask me first" should begin. Genuinely curious how you all handle it. Comment from Stacy Wycoff(@stacywycof83995): @aadilghani  I don't run coding agents but I have the same read-only vs

... rankings, and links. You optimized pages for a search engine, you built backlinks, you climbed the SERPs. That was the job . That job still exists. But it's no longer the only one. Generative AI has introduced a second, parallel layer of discovery. One where answers are synthesized, not retrieved. Where visibility depends not on ranking, but on whether an AI system understands, trusts, and cites your expertise . Traditional SEO is now about maintaining technical health and training signals. Generative ... ... that's still being invented. We need to be honest. We need to learn. We need to experiment. And slowly, we will evolve. From SEOs to whatever shiny new title this world gives us . The future isn't human versus

... Cursor just dropped " Origin ," a GitHub competitor. Cursor is moving way beyond "VS

... breed faster horses, how to make the cabin lighter? But they were on the completely wrong thing. Henry Ford built a motorzed vehicle and took over everything. It wasn't just a faster transportation; it was a completely different parallel. We aim to recreate this difference with Dirac vs

... both content and   product work.   2. Google Search Console I basically live in it. For anything SEO, it's the only honest source of truth   about what's actually happening vs. what I assume is happening.   3. Ahrefs keyword and competitor

... endless. In the near future, professionals will fall into just two categories: those buried under communication friction, and those who cloned themselves via Talkmie . Talkmie lets high-impact executives, subject matter experts, academics, lawyers, and doctors train a sophisticated Parallel Persona in under 10 minutes. How it works: Instant Training: Upload your knowledge base, publications, or organizational frameworks into the cloud 24/7 Connectivity: Stay deeply connected with your students, clients, or audience in your exact voice and professional style. Ironclad ...

... actual insight, and it's bigger than it looks: making the notification say why it's waiting is what turns a ping into a triage. "Done" makes you tab back to find out what "done" means. "Needs approval vs finished vs

... Something I built led to a design decision I want to get feedback on. LineageLens is a free VS Code extension that captures every AI code insertion and scores it for risk on a 0 100 scale. Works with Cursor, Copilot, ClaudeCode, Gemini CLI. Zero config on install just start using your AI tools and your insertions start showing up in the sidebar. The scoring is deterministic rules: +28 for credential-like material, +24 for eval/exec patterns, +22 for subprocess ... ... operationally. Right now the score intentionally mixes both because incomplete capture weakens auditability, but I agree there s a conceptual difference between this code appears dangerous and we cannot fully explain how this code was generated. Exposing those as parallel

... breaks in prod the next day because the agent did what I asked literally, but the feature doesn't REALLY work CI passing doesn't tell you whether clicking the button does anything. The more agents I run in parallel, the more PRs I'm merging without verifying. How are people handling this? - Click through every preview manually? (took 2-3 hours of my mornings) - Some kind of QA agent that drives the preview deploy? - Pre-merge integration tests covering ... ... founding it). What it does: Generates e2e test cases based on a feature spec or on a branch. You review and edit them before they run. Spins up isolated sandboxes and runs the test cases in parallel

... saves it as a workflow it can repeat any time. No setup. No explaining. Just do it once. Voice Mode : Talk to NeuralAgent. It talks back. Start tasks with your voice, get responses spoken aloud. No typing required. Parallel Agents : NeuralAgent now spawns multiple agents working simultaneously. Research 30 competitors

... Repos drill-in: ASCII blocks over 52 weekly buckets, with empty weeks rendered as muted ticks so the timeline stays continuous even on young repos. Footer reads +N in last 12mo last star Xd ago. Fetched in parallel with the rest of the drill-in no extra wait when you open a repo. Latest release column A new Release column on the Repos tab shows the most recent release tag plus its age (v1.2.3 3d). The s sort cycle gains ... ... release" entry. No extra round-trip piggybacked onto the existing parallel

... trip Linux's inotify limits on big monorepos. The terminal now adapts its renderer to your GPU, so machines without acceleration stay smooth. Free, all three platforms hiveterm.com Full changelog hiveterm.com/changelog Curious how others here run parallel agents today tabs? tmux? worktrees? What would make a split-grid actually replace your setup? Comment from Andrii Krugliak(@theuniverseson): Four agents in split panes fixes a real annoyance, the alt-tab roulette is exactly the friction I hit. What ... ... communicate through the Hive MCP. Comment from Tehreem Fatima(@tehreem_fatima5): @ebrahimpleite The 'Not Responding' freeze fix on Windows and fixing the Linux inotify limits show you guys are really listening to dev pain points! Right now, managing parallel

... with key material in your profile (often integrated with the  OS keychain  on macOS and Windows where supported). You can also set a  Primary Password  for an extra unlock step. We didn t invent a parallel Oasis password cloud. If it s a saved login from import or autofill, it s in the  same on-device vault  as Firefox. Is the vault walled off from the assistant? For vault contents: yes, by architecture ... ... feed your imported password vault into assistant training or semantic memory.  If you voluntarily put secrets into chat, or a page visibly shows them, that s a different path and we think you should know that. Onboarding copy vs

... updated shadcn UI components and UI polish Coming next: multi-agent collaboration mode. I am working on several collaboration patterns: - Team Mode: sub-agents work together as a coordinated team - Round Table: multiple agents discuss, critique, and brainstorm together - Parallel Exec: agents run in parallel