... 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

... Memory systems for products like Claude Code and Codex might not be as reliable as they seem because they're heavily dependent on the harness, how the LLM is guided to retrieve and use them. More customizable agents like OpenClaw and Hermes solve some of this with plugins and custom memory systems. But then you need memory that works across devices, local sessions and cloud agents. So I'm wondering : is AI memory actually a product, or just infrastructure agents ...

... most guardrail tooling I looked at only reports how it does against a static, round-one test set, which doesn't tell you much about what happens once an attacker actually adapts. So I built an adaptive red-teaming harness alongside the defense layer itself, and published the honest result even though it wasn't flattering. Launching on Product Hunt this Tuesday. Mostly here to learn from others working on similar problems what's everyone else building or running into ...

... 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 ...

... founded a consulting shop, Blast Off Apps, back in 2014, and later managed a big banking client relationship at Naehas). Since late 2023, I've gone independent and been building AI products full-time: RAG pipelines, agent workflows and harnesses, and generally the whole stack. Right now I'm heads-down on AI Oracle , a Chrome extension and web app that saves what you've already thought through (notes, decisions, videos, articles) and hands it back the moment ...

... that fails the build if that ever collapses into an auto-approve. Not because waiting is good. Because for that class every automatic resolution is worse than the others, so we declined to pick one. Which means the agent harness budget is what ends the wait, and that is an unattributed denial with a timer on it. Somebody further up this thread called that out and was right. On meeting people where they are, agreed, with one limit. Push only ... ... been compiling some practical approaches to this nothing magic, just real-world patterns for managing agent behavior at the intersection of reach and responsibility. Comment from Aria(@ariajinling): I agree: degradation has to be an explicit, author-authored alternative

... 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

... work we must do... something that shallow chatbots and aimless agents just couldn't keep up with. We've been systematically building this for over a year and currently in open beta, with a pretty cool (patent-pending) AI harness that I genuinely believes is unlike anything else. I've admired PH for a long time but never brought myself to post or launch here before... hoping to connect with like-minded folks who think a lot about where entrepreneurship ...

... 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 Mustafa Arian(@thenameisarian): if i got unlimited Fable for a month, i'd build the thing i've been backlog-shelfing for 18 months: a private agent that watches my git history, slack threads, and PR review comments, and writes the receipts of what ... ... 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

... 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 Code Comment from Bill Davis(@billspaced): @nolan_vu  Slack, not because I love it but because everything dies without it. YESSSSSSSSSSSSS Comment from Bill Davis(@billspaced): @riya_pariyar   @benfleming   @asapx  same question... never heard ... ... solo founder, these are the five tools I use almost every day: ChatGPT 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 ...

... muted rule. The choice is written back to ~/.config/octoscope/config.toml automatically your pins survive restarts. Sort cycle, filter and public-only mode all respect the partition. pinned_repos = [ "gfazioli/octoscope", "gfazioli/Mantine-Hint", ] Quiet but important There's also a vhs smoke harness under tapes/ that scripts the canonical user flows same scenarios I used to walk through manually before every release, now reproducible with make tapes . And a CI workflow runs build / test / lint on every push, so regressions don't sneak through ...

... 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 ... ... case is just endless. Comment from John Abiola(@jonabiola): Combining GitHub Copilot with VS

... everyone, I m Sarvesh, a product designer and builder interested in the space between product design, creative tooling, AI agents, and emerging tech. Lately I ve been exploring how AI changes the design workflow, especially around agent harnesses, durable project memory, design systems, prototyping, and how designers can move faster without losing taste or context. I m especially interested in tools that help builders go from idea to usable product more fluidly. I come from a product design, advertising ...