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The New Stack | DevOps, Open Source, and Cloud Native News

Agentic development hinges on verification. For cloud-native software, that is a runtime problem. AI agents need infrastructure: Why Europe’s regional cloud strategy matters Transform your AI coding agent into a deterministic Java Spring expert WeAreDevelopers is coming to the US to give unsung developers a bigger voice Cleaner AI training data, fewer bugs: Sonar’s SonarSweep explained Observability overload is drowning engineers Google’s DiffusionGemma is 4x faster than its other Gemma models Fable 5: Guardrails and burn rate are annoying users, who say it’s still better than Opus 4.8 The Anthropic leader who built Claude Code says he ditched prompting — now he just writes loops. AWS can now mathematically prove your VMs are isolated Microsoft pulled 73 GitHub repos after malware attack — but still won’t say who’s compromised Databricks wants to kill the “email me a file” problem for AI agent skills Ramp bets forward deployed engineers can do what off-the-shelf finance AI can’t Git real: AI agents aren’t just for solo developers anymore Anthropic launches Claude Mythos/Fable 5, but you better try it soon Spring is 23 years old. AI just made it a security emergency. This AI agent startup ditched Anthropic for DeepSeek — and says it’s saving millions When your data model is the bottleneck: lessons from Medium’s feature store How long before we stop reading the code? The tokenmaxxing party is over, and Revenium is mopping up How AI is solving the memory crunch it created Microsoft’s pitch to enterprises: Ditch Azure Repos for GitHub, despite its rocky reliability record Claude Code’s biggest upgrade yet ran 5 agents at once — here’s what happened Why Anthropic just doubled Claude Cowork limits at no charge For years, Apache Cassandra handed this work to your team — 6.0 takes it back “A dangerous combination”: The 2 factors that can “corrupt” AI agent workflows With Foundry, Microsoft bets the enterprise AI battle is about reliability, not capability Microsoft unlocks Visual Studio for developers left behind by its own AI AI teams now deploy 1,000 times a month. Your pipeline wasn’t built for that. Microsoft just made the agent runtime free — and kept everything around it “Whoever builds the most joyous product wins”: The agent war begins Netlify CTO Dana Lawson: Writing code is no longer the job From Jupyter Notebook to production: How to ship AI systems that actually work OpenClaw used Gavriel Cohen’s code and exposed the AI Agent accountability problem Replit shows how vibe coding is getting its own financial stack — and a path to profit Cloudflare aqui-hires VoidZero: Did a piece of the open web just stabilize, or become more brittle? Cursor cuts prices and adds enterprise spend controls amid “tokenomics” reckoning Google Gemma 4 12B nearly matches 26B benchmarks — and runs on your laptop Snowflake thinks it knows what’s really slowing developers down Autonomous agents have met their biggest challenge yet: The database. Why agentic AI makes the ops platform the most important layer in the enterprise How to dramatically improve enterprise security alert tuning to battle cyberattacks Why the need for humans won’t disappear in the age of autonomous databases How to secure Kubernetes in the age of AI workloads Asana says its new AI “chief of staff” turns your Slack chaos into trackable work Nvidia’s best model is now live Mate Security’s Asaf Wiener made every backend engineer a model router. He’s right to. The AI cost crisis finally has a watchdog — just not the companies causing it How to get operational data off the factory floor without creating an IT breach Why CPUs still matter in the age of AI agents Rayfin: Microsoft’s answer to the gap between vibe coding and enterprise production Microsoft bets the enterprise AI race will be won on data context, not model power “A successful attack could be catastrophic”: Anthropic gives more groups access to Claude Mythos How GitHub plans to win developers back Microsoft really, really, really wants developers to love Windows again With Intelligent Terminal, Microsoft is reinventing the Windows terminal Microsoft debuts “Scout” at Build, a new personal agent for work OpenAI’s Codex adds new tools — Sites, Annotations, more plugins — for knowledge workers GitHub Copilot’s usage-based billing is live: Here’s what you need to know OpenAI, Anthropic, Google, Amazon, and xAI all fail on type of attack, study finds JetBrains open-sources Mellum2 to go where Claude Code can’t Claude Code vs. Cursor vs. Codex vs. Antigravity — six months in This coding agent doesn’t want your feedback — it ships without it “Blowing things up”: The one move vendors got wrong on AI agents At Sapphire, SAP makes the case that enterprise AI is a context problem Gavriel Cohen found his own code inside OpenClaw, so he walked away AI retrieval at scale is becoming a systems problem, not a tooling problem The DIY platform trap that’s burning out engineering teams I tested Cursor’s new Jira integration and it’s 5 stars, no notes. Here’s why. Why GPT-5.4, Claude, and Gemini can’t agree on basic, real-world facts Replit’s vibe coding platform just got a Visa-backed identity layer for AI agents — and it changes how agents spend money Opus 4.8 Made Claude Smarter. Token Discipline Got Urgent. Why Linux creator Linus Torvalds gets angry hearing “99% of code is AI” Vendor neutrality isn’t magic: A hard look at the OpenTelemetry ecosystem “The AI did it” won’t save you when EU regulators come knocking The fix for soaring AI cloud bills exists — so why won’t we trust it? AI is shipping code faster than security was built to handle Why AWS scrapped OpenSearch’s architecture to chase agent workloads Percona celebrates 20th birthday with new foundation — and a goat cake Why OpenAI and Anthropic are hiring forward deployed engineer teams Claw-style AI agents are coming to the enterprise. The governance infrastructure is still catching up. The agentic identity crisis: Why your security isn’t ready for the AI revolution Debugging the undebuggable: building observability into probabilistic AI systems Snowflake commits $6B to AWS as it pushes deeper into AI Why MotherDuck refuses to fork DuckDB Researcher “gave Claude Code ‘ADHD’… and it thinks 2x better now.” Outside experts want more proof. “There is no accountability”: AI coding agents are installing packages no one owns “Tokenmaxxing is real, expensive & it’s spreading”: AI budgets are exploding With Google’s debut, the most important AI agent feature is now the most boring one Why AI agents need a Context Lake Google ranks the best AI for building Android apps, and the winner isn’t Gemini Google pushes Pro, Ultra, and free users from open-source Gemini CLI to closed-source Antigravity CLI The reason enterprise outages almost never start where ops teams think Taming the agentic influx: a blueprint for AI business observability How the AC/DC framework helps teams govern AI coding agents GitLab 19.0 trades its string section for a full DevSecOps orchestra Who’s monitoring the agents? How Jaeger hit 8.6× compression on 10 million spans with ClickHouse What ClickHouse learned from a year of coding with AI agents OpenClaw passed 300,000 GitHub stars. Then Google launched Spark.
Claude Opus 4.8 is here: effort controls, dynamic workflows, cheaper fast mode, better honesty, less deception
Meredith Shubel · 2026-05-29 · via The New Stack | DevOps, Open Source, and Cloud Native News

On Thursday, Anthropic released the newest version of its flagship model, Opus 4.8, which allows users to control Claude’s effort, tackle bigger coding tasks, and run fast mode more cheaply. Anthropic also says the model is more honest, less deceptive, and better at supporting user autonomy and best interests. 

Benchmarks put Opus 4.8 ahead of its predecessor, as well as GPT-5.5 and Gemini 3.1 Pro, save agentic terminal coding, where OpenAI’s model remains the winner. 

It was available on Thursday at the same price as Opus 4.7.

The rumors are true: Opus 4.8 touches down as an upgrade from 4.7

On May 28, X was atwitter about the supposed leak of Opus 4.8’s imminent arrival. One user posted a rumor that “Opus 4.8 has been found staged in the Claude Code model selector on the desktop app. It should be releasing today!”

And the tweets on the street were right, but how will Opus 4.8 be remembered in Opus history? 

What’s new: Users can control Claude’s effort

A new control means users can scale up or down how much elbow grease Claude puts into its tasks. When giving it its all, Claude will “think more frequently and more deeply to give a better response,” explains Anthropic in its announcement blog post. Conversely, lower-effort Claude will turn out faster responses and work through a user’s rate limit more slowly. 

That could be good news for users feeling the effects of AI shrinkflation and worried about hitting rate limits faster than expected. 

What’s new: Claude can take on bigger coding tasks

Now available in research preview, what Anthropic describes as a “dynamic workflows” feature should allow users to work on larger-scale problems with Claude Code. Specifically, Anthropic says users can now ask Claude to “plan the work and then run hundreds of parallel subagents in a single session.” From there, it will verify the outputs before returning them to the user. 

What could that look like for an everyday user? Anthropic gives the example of codebase-scale migrations, saying Claude Code with Opus 4.8 can get it done “across hundreds of thousands of lines of code from kickoff to merge.” 

What’s new: Fast mode is cheaper

More good news for Claude users’ wallets: Anthropic says Opus 4.8’s fast mode (i.e., when the model runs at 2.5x its normal speed) “is now three times cheaper than it was for previous models.” 

What’s new: Opus 4.8 supports users more and deceives them less

That is, the model “reaches new highs on our measures of prosocial traits,” says Anthropic’s Alignment team in the announcement blog post. Specifically, the AI company reports that Opus 4.8 has improved support for user autonomy and for working in the user’s best interests. 

In what looks like more good news, Anthropic says Opus 4.8’s rates of deception and cooperation with misuse are “substantially lower” than its predecessors, apparently catching up to Claude Mythos Preview, what the AI company once called “the best-aligned model we’ve trained,” reported by The New Stack.

What’s new: It’s more honest

Another big improvement for the model is its improved honesty. According to Anthropic, Opus 4.8 is “around four times less likely than its predecessor to allow flaws in code it has written to pass unremarked.” It claims that earlier testers have confirmed this statement and described Opus 4.8 as “more reliable and sharper in its judgment when it’s performing agentic tasks.” 

By the benchmark: Opus 4.8 vs everyone else 

Anthropic says Opus 4.8 levels up from its predecessor across all benchmarks. While launch-day benchmarks don’t always tell the same story as real-world use, the numbers do show promise. 

While launch-day benchmarks don’t always tell the same story as real-world use, the numbers do show promise. 

Most notable: Opus 4.8 shows a marked improvement over Opus 4.7 (64.3%) — not to mention GPT-5.5 (58.65) and Gemini 3.1 Pro (54.2%) — in agentic coding at 69.2%. Its agentic compute use score (83.4%) compared to GPT-5.5 (78.7%) and Gemini 3.1 Pro (76.2%) is nothing to sneeze at. But it loses out to GPT-5.5 in agentic terminal coding, down 3.6% compared to OpenAI’s model. 

Source: Anthropic

A walk down Opus lane: from “the world’s best coding model” to AI shrinkflation in a year

In May 2025, Anthropic launched Opus 4 at its first developer’s conference, Code with Claude, dubbing it “the world’s best coding model.” At the time, the AI company promised to set new standards for coding, advanced reasoning, and AI agents. The model brought significant advancements in coding and long-context reasoning, standing out for its ability to handle long-running tasks and maintain context in what Anthropic described at the time as “thousands of steps.” 

Opus 4.1 followed soon after, in August 2025, with moderate improvements in the model’s performance on agentic tasks, coding, and reasoning. But it was only a small update; at the time, Anthropic teased of “substantially larger improvements to our model in the coming weeks.” 

In November 2025, Opus 4.5 dropped, to much noise. Again, Anthropic touted it as “the best model in the world for coding, agents, and computer use.” And again — they teased us, noting Opus 4.5 was just “a preview of larger changes to how work gets done.” For its part, that preview brought improvements that enabled the model to better handle ambiguity and solve problems involving multi-system bugs. In many ways, Opus 4.5 allowed Anthropic to reclaim the coding crown after OpenAI’s GPT-5.1-Codex-Max and Google’s Gemini 3 model gained favor. 

True to their hints, three months later, Anthropic gave us Opus 4.6, “a step change in using large language models (LLMs) for enterprise workflows, thanks to its ability to handle more complex tasks and deliver results better,” The New Stack reported. Opus 4.6 leveled up with better planning, coding, and debugging skills, became Anthropic’s first model to use adaptive thinking, and earned standout benchmark scores. Of particular note was its 1M-token context window. An Anthropic spokesperson told The New Stack, “it gets much closer to production-ready quality on the first try than what we’ve seen with any model – documents, spreadsheets, and presentations will need less back-and-forth on iterations.”

But all that glitters is not gold. On the heels of the Opus 4.6 launch, Anthropic caught flak for a pricing change: “While the models technically supported prompts approaching the 1-million-token limit, requests exceeding roughly 200,000 tokens were billed at higher ‘long-context’ pricing tiers, moving the entire request into a premium rate band,” The New Stack reported.

Opus 4.7 also faced some complications. After its drop in April 2026 — a direct upgrade to Opus 4.6 that brought better vision, better memory, and better instruction-following — The New Stack reported that “Claude Opus 4.7 users report self-contradicting responses and degraded performance, raising questions about AI model quality, safety tradeoffs, and shrinkflation.” Also awkward: Anthropic itself called Opus 4.7 “less broadly capable” than the then-much-talked-about Claude Mythos Preview. As The New Stack reported, Opus 4.7 appeared to be something of a training ground for new cyber safeguards for Mythos. 

What’s the next trick Anthropic has up its sleeve? 

The rumors of a May-28 launch for Opus 4.8 proved right on the money, so it may be worth paying attention to the rest of the Internet gossip: the leak also suggested that Anthropic will soon announce Sonnet 4.8 and Mythos 1. 

It would be big news, to say the least, from the AI company that has been frustrating users lately. 

Earlier this month, it disappointed developers with Claude Code agent view, which, as Rob May, CEO and co-founder at Neurometric AI, told The New Stack: “It removes some friction, but it doesn’t change the underlying problem.” That same week, Anthropic also announced it will split billing for Agent SDK usage starting June 15, not exactly welcome news for users who were used to seeing programmatic usage and interactive usage pulled from the same subscription limits. 

Perhaps Mythos 1 and Sonnet 4.8 will bring more wins. 

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