... owning an open-source Factory, including models, authentication, storage, sandboxes, and deployment Bringing work in from GitHub, Linear, and Slack, then moving it through investigation, planning, building, and review Configuring stages with specialized agents, skills, rules, and workflows, including alternative coding harnesses

... fixes changed the code under test, and 94% of those fixed a real bug. A flaky test is a bug report with a wider error bar. Skipping it throws the report away. So the fix lives in the harness, not the model. One line for the rules file: on a failing test, rerun it alone and unchanged before editing anything; two identical failures means investigate, one flip means report it as flaky and stop. One line for the task ... ... from Balakrisnan H(@balakrisnan_h): I get why the agent bumped the timeout, but that's feel risky. You might just be covering up the real issue instead. Comment from Jack Mark(@jack_mark8): I'd rather have the harness

... Hello guys, i've seen a lot of movement about the pi harness and how efficient it is, so for the re-launch of Murmell, do you want that harness

... probably saw the comparison: one coding agent harness sends ~33k tokens before your prompt, another sends ~7k. Big thread, lots of outrage about waste. I finally read the whole study instead of the headline, and the actually useful findings are different from what got shared. First, in their realistic-config lane (instruction file + several MCP servers), the "light" harness

... their data, and some orchestration glue to chain prompts together. It's weeks of undifferentiated work before you ship anything a user sees. We are building to be that layer, managed: Tools give your agent capabilities without writing the harness RAG attach a knowledge base, retrieval handled Connectors plug into the systems your agent needs to read and act on Prompt orchestration chain, branch, and route across steps Metering every run is measured, so billing and cost visibility are built ...

... Product Hunt Submission Draft ## Product Name remote-browser.dev ## Tagline A remote headed browser for agentic UI testing ## Short Description Build an agentic UI test harness that lets local coding agents drive a visible remote browser, collect screenshots, judge UI expectations, and produce repeatable test reports. ## Article / Maker Comment ### Building an Agentic UI Test Harness

... Codex (now @ChatGPT by OpenAI )is strong at long-context planning and execution. @Claude Code acts like a supervisor and a second pair of eyes. @OpenClaw is like my daily operations intern. I know there are many other agent harnesses. Many are open-source, including OpenHands, @Pi Coding Agent , and Hermes. I m curious. Which agent harnesses

... this matter? that's shadow mode. you prove the fix on actual code using the one input code review can't simulate: the retry. how are you catching at-least-once bugs today? staging with live webhooks, a replay harness, or do you find out in prod ...

... window and then ask. The phone gets the first stretch of that window and the terminal gets the remainder. The part that surprised me when we measured it is that N is not really ours to choose. The agent harness kills the hook on its own budget, and those budgets differ by agent. Claude Code allows about two minutes, Cursor allows one. We take that number, subtract a guard so we can return a decision rather than get killed ... ... wait, and that is the ceiling. Any policy timeout longer than the harness

... Almost every knowledge-work domain now has a decent tool. Harvey and Legora for legal. Rogo for finance. All decent and all narrow and not accessible to everyone. Coding has something the rest of knowledge work doesn't: harnesses. Cursor CLI, OpenCode, Codex, Claude Code general-purpose agents that turn a model into a real force multiplier. So where's the equivalent for everyone else? Why is there no publicly available harness

... Product Hunt solo builder here. Every multi-agent thing I built ended up with one "manager" object that knew every agent and every step, and an agent harness that was a giant while-loop owning the model call, the tools, the memory, and the approvals. Add a fourth agent and both became the thing that breaks. So I built Cosmonapse , a distributed agent-to-agent protocol where agents are peers on a shared bus. The model is a nervous system ... ... names tell you where logic goes: Neuron thinks (your agent, a pure function), Axon sends, Dendrite reacts, Synapse connects (the bus), Engram remembers. To build harnesses

... delete them, and chased ideas that seemed brilliant until reality proved otherwise. Every failure taught me something that eventually shaped how I build today. By day, I work on AI platform and infrastructure engineering building the systems, orchestration, and harnesses that let AI models and agents run reliably at scale. I've found that the hard part isn't getting an LLM to answer a prompt it's building the infrastructure around it. That led me to create Cosmonapse ...

... honest, you don't get the feedback you want. Again, in 2026, when we have so much data on what makes a good edit for your objective, we shouldn't be limited to that. AI should be harnessed to give you as much tried-and-tested feedback as possible. This is exactly why we've built Review -- a free tool that gets you feedback from your team as well as from AI. Our AI has watched thousands of hours ... ... being able to draw on the frame and select timeline rangesgives it that premium feel without the heavy price tag. Quick question: how does the AI handle different video pacing or retention hooks depending on the platform like YouTube vs

... exactly what the agent did. Setup takes 2 to 5 minutes per environment, then the agent runs unattended until the task is done or it decides a human should take over. You can switch out any part of the harness and use/call whatever you need. Completely modular and transparent with the pricing at the end( Doc ) for every type of call. Docs are at Coasty/Docs . The quickstart gets you to a first running task in a few minutes ...

... they are able to calculate or get the solution to the problem without spending days talking to external suppliers over a broken system. My most pressing issue that I am developing sort of Wisdom & Wellness App portal which harnesses a number of fields to come up with the most constructive solutions to help people move forward in solving multiple life issues such as personal financial management, gaining confidence, developing a money consciousness and understanding how people can related ...

... unlimited access to the best models with Fable and sol, what's the most ambitious thing you'd build? Also, where would you use these models to build things? In Claude, some other harness? Comment from Alper Tayfur(@alpertayfurr): @praneethpike  I'm currently using Claude Code. Comment from Praneeth Pike(@praneethpike): @alpertayfurr  How do you do all these currently? Comment from Praneeth Pike(@praneethpike): @thenameisarian  that idea has real potential! The best thing is that ... ... this quarter for performance reviews + investor updates. half of an engineer's real work never lands on a resume because nobody writes it down at the time. an agent with persistent context across these surfaces would be the unlock. harness

... Srinivasan(@aakash_srinivasan): Here's my everyday 5: Google Docs - User friendly and easier to save my content drafts. Canva - For quick creatives, decks and one pagers. ChatGPT/Claude - For ideation, content tweaking, image generations. Notion - to track and save competitor information. Buffer + Linkedin - For scheduling, sharing ideas, building a community. Comment from Mayur(@mayur17): @mustafa_najoom   Try this Android app KeepSafe: Offline Secure Vault For your personal passwords and important Creds, it will store in your device only ... ... Cursor: coding Supabase: backend and auth Vercel: hosting GitHub: version control Google Search Console: SEO Campix: my own project, camp software, yes I'm biased Comment from Hans Desjarlais(@ismaelyws): Gmail Calendly Claude Code Google Docs & Sheets VS

... against your model and hardware, oneinfer-edge evaluates all five simultaneously and tells you exactly which one to use, for local, cloud, or both. Hours of trial and error eliminated before a single deployment. - Traffic control panel for agentic harnesses. Zero code changes. You can now leverage locally deployed models through the existing agentic copilots like codex, kilocode, opencode and openclaw and more upcoming. -Model, serving library and hardware compatibility. Before you deploy. Wrong serving library for your hardware. Wrong ...

... small, but justifying the rollout took more work. The risk cut the other way too: a too-tolerant liveness probe could mask a genuinely stuck pod and delay a restart that would actually help. We wrote a small reproduction harness that runs against real kubelet in minikube. It installs 2 identically-built pods, each running the production /health handler and the production memory watchdog. Both get the same self-induced event-loop freezes on a schedule. The only difference ... ... liveness probe. DEPLOYMENT LIVENESS PROBE RESTARTS IN 2.5 MINUTES victim-oldprobe 1s default timeout, threshold 3 2 (crash-looping) victim-newprobe 5s timeout, threshold 6 0 (stable) That was enough to ship, and the harness

... Feature Update: You can now route your coding copilot or any agentic harness' traffic to self hosted models either in local or cloud in oneinfer-edge (fully open-sourced) Currently we have given support to OpenCode, KiloCode, OpenClaw, and Codex, most of you already have used at some point. No plugin. No config file. No IDE restart. You click ONEINFER, a local proxy intercepts your copilot's requests, translates the format, routes to your self hosted model, and returns ... ... expects an OpenAI messages format and your local model returns something else. Switch back to original models in one click, mid-session, no restart. For when you actually need it. This is just the start. Support for more agentic harnesses

... 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

... appears -> agent freezes File name typo -> agent gives up App not in foreground -> click misses I know I could write more robust skills, but that defeats the voice and forget promise. Is anyone working on a harness layer specifically for desktop reliability? Something that retries, asks clarifying questions, and logs everything? Feels like the model part is solved, the engineering part ...

... According to the 2025 @Stack Overflow Developer Survey (49,000+ participants), @VS Code still is the most-used dev environment, maintaining the top spot thanks to its marketplace. @Kilo Code , @Github Copilot , @Ultracite ... What are the extensions that significantly improve your coding workflow? Comment from John Abiola(@jonabiola): @fmerian The agentic feature is quite very helpful. I practically use it to code, troubleshoot, etc. Basically, I use it as far as using it to troubleshoot my server, inclusive security audits ... ... reading big files. Comment from fmerian(@fmerian): @viorelmocanu  great list! Comment from Viorel Mocanu(@viorelmocanu): I've been tweaking this setup for about 6 months now, it's getting better by the day as the agentic harness

... engineering" mode better prompts, longer templates, more examples you're leaving most of the value on the table. Frontier models (Claude Opus 4.7, GPT-5.4, etc.) can now run autonomous workflows end-to-end if you build the right harness around them. Four parts: a loop, a verifiable goal, a tool set, a secure environment. I wrote a full breakdown the practice, the 4 components, the most common failure modes, and why "verifiable" is the most important word in this ...

... reporting it does proofs on systems code before starting work. Hex says it flags missing data instead of making up plausible-but-wrong fallbacks. Genspark measured loop rates on hard queries and 4.7 basically stopped looping. different teams, different harnesses, same pattern. the numbers are nuts too: - CursorBench: 58% on 4.6 70% on 4.7 - Rakuten SWE-Bench: 3x more production tasks resolved - XBOW visual-acuity: 54.5% 98.5% - Notion: tool errors cut to 1/3 - same $5 / $25 pricing as 4.6 also ... ... Swift(@splitpostio): On task budgets, I'm not sizing them yet. Pinned to 4.6 through a launch in a few weeks and the tokenizer change alone means I want to benchmark before migrating anything. The point about task shape vs