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ExternalSoftware Engineering
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An AI Coding Cost Tracker Needs a Measurement Contract

The most dangerous number in an AI coding dashboard is the one labeled cost without a definition. A local tool can reconstruct token activity from Claude Code and Codex session records. It can apply a dated model-price table. That produces an estimate with a clear use: comparing periods and understanding the shape of local activity. It does not produce an invoice. Claude Code and Codex do not write identical usage records. Claude can expose input, output, cache creation, and cache-read fields on

opensourceaiprogramming
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ExternalSoftware Engineering
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The number that lied: rebuilding a usage meter that actually helps

Short version first, for anyone who just wants the outcome: I run Claude Code on a flat monthly subscription, not pay-as-you-go. For months that plan never gave me a reason to look closely at it, so I stopped looking. Then an overnight automation burned through a week's worth of it in two days, the account locked with four days still to go, and I bought my way out at list price. That cost enough to make me build a small usage meter that now tells me, in plain language, whether I can spend more o

aiseomarketing
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ExternalSoftware Engineering
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Creating a Live Status Page for Your Python Bot

Building a Live Status Dashboard for Your Python Bot A JSON health check is enough for a hosting platform, but it's not much use to you when you want a quick, human-readable view of whether your bot is actually doing its job. This guide covers building a real python bot status dashboard — with proper HTML, CSS, and a bit of JS — using nothing more than StayPresent's web.html() and the HTTP server it already runs. Why a Dashboard Beats a JSON Blob How web.html() Works Serving Static Assets Alon

htmlpythontutorial
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ExternalSoftware Engineering
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¿Cómo revertir una migración promovida a Aurora sin perder los datos nuevos?

Migraste una base de datos MySQL de Amazon RDS a Amazon Aurora. La read replica de Aurora se puso al día, la promoviste, cambiaste el endpoint de la app, y ahora los writes aterrizan en Aurora. Diez minutos después, o quizá tres horas después, algo anda mal y quieres regresar a la vieja instancia de RDS. Aquí está la trampa. La vieja instancia de RDS está congelada en el momento en que hiciste el corte. Cada pedido, registro y edición que pegó en Aurora desde entonces no existe en RDS. "Reverti

awsclouddatabase
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ExternalSoftware Engineering
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AgentATC

Track 3: AI & Agent Observability — "Agents of SigNoz" Hackathon (WeMakeDevs × SigNoz, July 2026) Every team at a hackathon like this is going to show you an agent that's slow, or an agent that errors. We're showing you something worse—and far more common. A multi-agent system where nothing ever fails. No exception. No page. No red dashboard. And yet the system is still stuck. Tasks bounce endlessly between an Executor and a Critic. Work is quietly repeated even after it's completed. Sometimes a

agentsaimonitoring
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ExternalSoftware Engineering
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Extracting video frames in Rust, in-process — no CLI, no hand-written decode loop

Here is a task that comes up constantly. You are doing inference in Rust — candle, burn, ort — and you want to feed a video to a model. Step one is always the same: get the frames. And in Rust today, getting frames means one of two things. Either you shell out to Command::new("ffmpeg"), write PNGs to disk or parse -f rawvideo off a pipe, and read them back; or you reach for the low-level bindings and hand-write the send_packet / receive_frame decode loop — forty lines before the first pixel, and

rustffmpegframe
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ExternalSoftware Engineering
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I replicated the vision-only Pokémon run Anthropic showcased on the Fable 5 launch page — then I read its thinking chains

Anthropic says Fable 5 can play Pokémon from vision alone. I verified that claim independently: 1,785 decisions and $65.40 to the first gym badge — then I read its thinking chains in the logs, and the result stopped looking so simple. In short — Anthropic's Fable 5 launch page claims the model beat Pokémon FireRed "with a minimal, vision-only harness." No protocol, no step count, no cost, no code was published. So I built my own harness — matching or undercutting every constraint in their descri

aipythonmachinelearning
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