Show HN: rari, the rust-powered react framework https://ift.tt/txjAUQN

Show HN: rari, the rust-powered react framework https://rari.build/ February 12, 2026 at 11:15PM

Show HN: Agent framework that generates its own topology and evolves at runtime https://ift.tt/31itnaG

Show HN: Agent framework that generates its own topology and evolves at runtime Hi HN, I’m Vincent from Aden. We spent 4 years building ERP automation for construction (PO/invoice reconciliation). We had real enterprise customers but hit a technical wall: Chatbots aren't for real work. Accountants don't want to chat; they want the ledger reconciled while they sleep. They want services, not tools. Existing agent frameworks (LangChain, AutoGPT) failed in production - brittle, looping, and unable to handle messy data. General Computer Use (GCU) frameworks were even worse. My reflections: 1. The "Toy App" Ceiling & GCU Trap Most frameworks assume synchronous sessions. If the tab closes, state is lost. You can't fit 2 weeks of asynchronous business state into an ephemeral chat session. The GCU hype (agents "looking" at screens) is skeuomorphic. It’s slow (screenshots), expensive (tokens), and fragile (UI changes = crash). It mimics human constraints rather than leveraging machine speed. Real automation should be headless. 2. Inversion of Control: OODA > DAGs Traditional DAGs are deterministic; if a step fails, the program crashes. In the AI era, the Goal is the law, not the Code. We use an OODA loop to manage stochastic behavior: - Observe: Exceptions are observations (FileNotFound = new state), not crashes. - Orient: Adjust strategy based on Memory and - Traits. - Decide: Generate new code at runtime. - Act: Execute. The topology shouldn't be hardcoded; it should emerge from the task's entropy. 3. Reliability: The "Synthetic" SLA You can't guarantee one inference ($k=1$) is correct, but you can guarantee a System of Inference ($k=n$) converges on correctness. Reliability is now a function of compute budget. By wrapping an 80% accurate model in a "Best-of-3" verification loop, we mathematically force the error rate down—trading Latency/Tokens for Certainty. 4. Biology & Psychology in Code "Hard Logic" can't solve "Soft Problems." We map cognition to architectural primitives: Homeostasis: Solving "Perseveration" (infinite loops) via a "Stress" metric. If an action fails 3x, "neuroplasticity" drops, forcing a strategy shift. Traits: Personality as a constraint. "High Conscientiousness" increases verification; "High Risk" executes DROP TABLE without asking. For the industry, we need engineers interested in the intersection of biology, psychology, and distributed systems to help us move beyond brittle scripts. It'd be great to have you roasting my codes and sharing feedback. Repo: https://ift.tt/u3UEjTJ https://ift.tt/GoPg0EV February 11, 2026 at 11:39PM

Show HN: Unpack – a lightweight way to steer Codex/Claude with phased docs https://ift.tt/5iyBeIG

Show HN: Unpack – a lightweight way to steer Codex/Claude with phased docs I've been using LLMs for long discovery and research chats (papers, repos, best practices), then distilling that into phased markdown (build plan + tests), then handing those phases to Codex/Claude to implement and test phase by phase. The annoying part was always the distillation and keeping docs and architecture current, so I built Unpack: a lightweight GitHub template plus docs structure and a few commands that turns conversations into phases/specs and keeps project docs up to date as the agent builds. It can also generate Mintlify-friendly end-user docs. There are other spec-driven workflows and tools out there. I wanted something conversation-first and repo-native: plain markdown phases, minimal ceremony, easy to adapt per stack. Example generated with Unpack (tiny pokedex plus random monsters): Demo: https://apresmoi.github.io/pokesvg-codex/ Phases index: https://ift.tt/gq3MRws... I’d love feedback on what the “minimum good” phase/spec format should be, and what would make this actually usable in your workflow. -------- Repo: https://ift.tt/BA3g5ue https://ift.tt/BA3g5ue February 11, 2026 at 11:47PM

Show HN: Goxe 19k Logs/S on an I5 https://ift.tt/IbyaLgC

Show HN: Goxe 19k Logs/S on an I5 https://ift.tt/T0qbRyk February 8, 2026 at 01:43PM

Show HN: Clawe – open-source Trello for agent teams https://ift.tt/vmG9Bke

Show HN: Clawe – open-source Trello for agent teams We recently started to use agents to update some documentation across our codebase on a weekly basis, and everything quickly turned into cron jobs, logs, and terminal output. it worked, but was hard to tell what agents were doing, why something failed, or whether a workflow was actually progressing. We thought it would be more interesting to treat agents as long-lived workers with state and responsibilities and explicit handoffs. Something you can actually see and reason about, instead of just tailing logs. So we built Clawe, a small coordination layer on top of OpenClaw that lets agent workflows run, pause, retry, and hand control back to a human at specific points. This started as an experiment in how agent systems might feel to operate, but we're starting to see real potential for it, especially for content review and maintenance workflows in marketing. Curious what abstractions make sense, what feels unnecessary, and what breaks first. Repo: https://ift.tt/FT6mCpU https://ift.tt/FT6mCpU February 11, 2026 at 12:17AM

Show HN: Deadlog – almost drop-in mutex for debugging Go deadlocks https://ift.tt/TqGdBut

Show HN: Deadlog – almost drop-in mutex for debugging Go deadlocks I've done this same println debugging thing so many times, along with some sed/awk stuff to figure out which call was causing the issue. Now it's a small Go package. With some `runtime.Callers` I can usually find the spot by just swapping the existing Mutex or RWMutex for this one. Sometimes I switch the mu.Lock() defer mu.Unlock() with the LockFunc/RLockFunc to get more detail defer mu.LockFunc()() I almost always initialize it with `deadlog.New(deadlog.WithTrace(1))` and that's plenty. Not the most polished library, but it's not supposed to land in any commit, just a temporary debugging aid. I find it useful. https://ift.tt/aVmAJ3M February 10, 2026 at 09:44PM

Show HN: I built a cloud hosting for OpenClaw https://ift.tt/qTFx0vg

Show HN: I built a cloud hosting for OpenClaw Yet another OpenClaw wrapper. But I really enjoyed the techy part of this project. Especially server provisionings in the background. https://ift.tt/5H9jmfZ February 10, 2026 at 02:39AM