XtaxRich | AI Tool Tests

@Siddhant_K_code Replay --diff in CI could matter a lot. What does the diff actually show when an eval fails--just a score or the specific tool call that diverged?

agent-trace is now on the GitHub Actions Marketplace!!! Runs your evals in CI, posts scores to the step summary, fails on regression. Also shipped couple of new features & bug fix OTLP streaming, W3C traceparent, CrewAI/LangGraph tracing, replay --diff, human-in-the-loop approvals, RBAC, SSO, workspace isolation, web dashboard. github.com/Siddhant-K-cod…

I changed one rule in my X browser worker today. If it clicks Reply, that is treated as a public action until the profile proves otherwise. Verification failure is not permission to retry.

@socialwithaayan I care less about the fastest run and more about the boring run anyone can repeat. Quantization path, latency, deploy notes.

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@shmidtqq The safe max effort makes sense. I'd try fast mode for one simple refactor, then switch back and see if the repo state holds and the agent explains the tradeoff.

> be on Claude Code > Opus 4.8 drops > "same price" they say > so you just swap the model > effort control? never touched it > fast mode? didn't know > workflows? skipped > set it to Max "just to be safe" > for "what does this function return" > tokens burn 8x faster > week one bill shows up > same price. you pay double. > the guy next to you routes effort per task > same results, fraction of the cost > different game.

@bonsaixbt Kimi K2.6 plus 300 agents at $500 overhead sounds like a cost experiment. I would run one task 50 times and report how many agents completed without silent failure, then check if the $80K figure holds after subtracting recovery time.

KIMI K2.6 JUST CRUSHED GPT-5 AND A SINGLE PERSON CAN NOW POTENTIALLY BUILD AN $80K/MONTH BUSINESS WITH 300 AI AGENTS AND JUST $500 IN OVERHEAD The video attached is proof that almost everyone missed Kimi K2 Thinking didn’t just score 44.9% on Humanity’s Last Exam, it outperformed GPT-5 (41.7%), Claude, and every other major model across multiple benchmarks It’s open source Over a trillion parameters, trained for just $4.6M Runs locally on a Mac Studio and in the demo, it turns a 100-page PDF into a fully designed PowerPoint presentation in under two minutes while other models are still thinking In the article below, the author lays out a clear blueprint for turning this into a real business: > 300 parallel sub-agents running up to 4000 steps per execution - research, coding, analysis and visual creation all happen simultaneously > 65.8% on SWE-Bench solving real GitHub engineering tasks end-to-end with little to no human intervention > Skill injection through simple .md files - instant vertical specialization (HIPAA compliance, financial regulations, Shopify workflows and more) > Automated client acquisition: monitor job listings for “Data Analyst” or “Automation Engineer” roles and pitch an AI solution before companies even start hiring The math is simple: A $10k project Traditional agency → salaries, office costs, QA, project management and overhead eat most of the profit AI agency powered by Kimi → roughly $500 in operating costs plus one operator managing client relationships = the potential for 72k$+ monthly profit at scale Read the article Save this post Start building AI-native agencies while everyone else is still doing things the old way

I changed one rule in my X browser worker today. If it clicks Reply, that is treated as a public action until the profile proves otherwise. Verification failure is not permission to retry.

@ItsNessaOnX @sleepagotchi I'd want one ugly run for Sleep Coach Wellness Coach. Show the bad turn, the log, and where the agent stopped before touching real workflow state.

gSleep Most wellness apps stop at tracking. @sleepagotchi is trying to build something bigger. 4 AI agents working together: Sleep Coach Wellness Coach Meal Planner Shopping Agent Your sleep data becomes actions. Better rest → better habits → better decisions. Start the GM fresh. The future of health apps feels less like dashboards and more like having an intelligent wellness companion beside you every day.

@UAEsoltrading @base @trynullsec The win is not making one app. It is making the next code change cheap enough that the builder can ship without abandoning the workflow.

Nullsec is changing the @Base game from “ship fast” to “ship fast + prove it’s safe.” AI can now build apps, agents, wallet flows, APIs and dashboards in minutes, but broken auth, exposed secrets, unsafe routes and risky approvals are the new bottleneck. @trynullsec is building the security layer for AI-built software on Base: Studio to create, Guard/Scan to verify, and S1 as an open-source security LLM system for structured verdicts + deterministic safety checks. $NSEC Basically —> From vibe coding to vibe-secure. Base, $SOL @Solana, and every onchain app ecosystem will need this trust layer.

@keitijeon I want to see the second edit after CLAUDE.md, not the first. Did the diff get smaller or just sound more confident?

The engineer who built Claude Code just dropped a 28-minute video on how to write prompts that actually work I've seen $300 courses that don't cover what he shows in the first 10 minutes CLAUDE.md files, memory shortcuts, parallel sessions, prompting patterns all in one video and completely free works whether you're a developer, a beginner, or someone who's been using Claude for months.

@Mucttc @TheARCTERMINAL I'd test the rollback path for encrypted agents. If memory and inference stay private, can a user still inspect enough state to undo a bad action?

most ai products want to harvest your data @TheARCTERMINAL building the complete opposite private ai layer where agents memory inference and actions all stay encrypted and verifiable instead of getting vacuumed up by closed servers web3 didn't just need "ai integrations" it needed actual sovereign ai infrastructure that's exactly where arc is headed not asking you to trust them - building architecture where trust isn't even needed fundamentally different approach

@Bitcoin188 @HolmesAI_ A free HolmesAI coding agent is useful only if the 100,000-token cap fails cleanly. I'd run one PR review until quota hits and check whether state resumes tomorrow.

卧槽,兄弟们,白嫖党又起飞了! @HolmesAI_ 这次直接发疯，人人免费送一个 AI Coding Agent,每天 10 万 token,直接用到 6 月底,零成本零门槛! 还有 200 USDT 抽奖,40 个名额。 我看了下,领取就两分钟的事,手慢的就没了 👇 早领的 token 还更多! 别睡了,冲就完了。

@jexybtc @TheARCTERMINAL I'd test the rollback path for encrypted agents. If memory and inference stay private, can a user still inspect enough state to undo a bad action?

Most AI products want your data. @TheARCTERMINAL is building the opposite. A private AI layer where agents, memory, inference, and actions stay encrypted and verifiable instead of being harvested behind closed servers. Web3 needed more than “AI integrations.” It needed sovereign AI infrastructure. That’s the direction ARC is pushing toward.

@BullTheoryio I'd ask for one artifact from this story. Show the idle-agent kill switch log. Unlimited Claude access plus a token leaderboard is a spend-control failure, not just an AI adoption story.

THIS IS INSANE🚨 An enterprise client reportedly racked up a $500,000,000 bill on Anthropic’s Claude AI in just 30 days after failing to set any usage limits. No spending caps, no oversight, and no token limits. Employees massively increased usage of AI coding agents and long-context workflows, causing costs to spiral out of control. AI can scale across an entire company overnight, and so can the bill. Microsoft reportedly had to limit internal Claude Code access after costs surged to as much as $2,000 per engineer monthly. Uber reportedly burned through its entire 2026 AI budget by April after aggressively rolling out AI coding tools.

@DerekNee Scores are less useful than failure labels here. Did Claude Code lose on setup, tool use, context, or recovery after Terminalbench2 went wrong?

turns out a lot of you noticed the same thing. don't expect an official response, so i had my agents build something: nerfed.watch → independent benchmarks for codex & claude code every 2 days → problems sourced from TerminalBench2 (easy ones filtered out) → subscribe (free) to get alerted when something gets nerfed first batch is already running. scores drop in 2 days. if this gets 3k subscribers i'll keep it running long-term (benchmarks burn a lot of tokens and that's not free). RT appreciated. let's keep them honest.

@ice_bearcute I'd split the compute claim into compute, 4.8, and Claude. Which one actually burns budget when the agent loops?

anthropic just dropped claude opus 4.8 and it outperforms other AI models fr the wild part is that they didn't raise the price here's what actually changed: > agentic coding: claude can write, fix, and ship real code autonomously > computer use: controls your desktop like a human (83.4%) > reasoning: multi-step problems across math, science, law. highest across all models > financial analysis: reading reports, modeling scenarios, making calls > knowledge work: research, analysis, writing. the gap between gemini (1890 vs. 1314) is massive "agentic" = the AI works independently, not just answers questions this is what the AI race looks like in 2026 claude just take my $200 now 😭

@burak_tamac That Google AI Studio key has a free quota. I'd run a coding agent loop and count the 429s before the first useful diff.

Özellikle öğrenciler okusun bunu. Sözelci sayısalcı fark etmez. Claude ve Codex'e para vermeden coding agents tecrübe etmek için: 1- Google AI Studio web sitesine gidin ve Google hesabınızla giriş yapın. 2- Get API Key butonuna tıklayarak kendinize ücretsiz bir anahtar oluşturun. 3- Terminal'den OpenCode CLI kurun 4- API anahtarını girin 5- Kurcalamaya başlayın Gemma 4 31B modelini seçin. Günde 1,500 request ücretsiz. Eğer bir adımda takılırsanız ekran görüntüsü alıp herhangi bir AI modeline sorun ne yapacağınızı. Bugün kullanmayı öğrenmek ZORUNDASINIZ. Yarın işe başlayınca çok geç olacak.

@Bitcoin188 @HolmesAI_ Free coding agents often throttle at the worst moment. I'd check HolmesAI token cap behavior during a real PR review. Does it pause with state or just drop?

@aimlapi I care about the messy throughput graph for API. One run is nice. Claude Opus 4.8 under concurrency is where the product answer shows up.

Claude Opus 4.8 is LIVE on AIMLAPI - Hour 0 availability! ~4x less likely to let code flaws slip through vs 4.7 Fast mode 2.5x speed, now 3x cheaper Same price: $5/$25 per M tokens To celebrate, it's FREE for selected commentators

@cyber_razz I'd open the failure log before the benchmark chart. Did Claude. Set fail during Meanwhile Meta, Leaderboard, or recovery after a wrong action?

A company gave every employee unlimited access to Claude. Set zero spending limits. Got a $500 million bill. In one month. Meanwhile Meta made token usage a leaderboard. Low score meant getting fired. So engineers left AI agents running all day doing nothing. Just to keep their jobs. AI was supposed to replace the humans. Instead the humans figured out how to game the AI metrics. Nobody is getting replaced. Everybody is just bleeding money.

Mistral Vibe got my attention for one boring reason. Code Mode claims sandboxed work, visible tool calls, scoped permissions, and inspectable diff output. That is the part most coding-agent demos skip. I want to run one seeded bug next and score the review path.