The Python Software Foundation rejected a $1.5 million U.S. government grant because it required them to renounce all diversity, equity, and inclusion initiatives. "The non-profit would've used the funding to help prevent supply chain attacks; create a new automated, proactive review process for new PyPI packages; and make the project's work easily transferable to other open-source package managers," reports The Register. From the report: The programming non-profit's deputy executive director Loren Crary said in a blog post today that the National Science Founation (NSF) had offered $1.5 million to address structural vulnerabilities in Python and the Python Package Index (PyPI), but the Foundation quickly became dispirited with the terms (PDF) of the grant it would have to follow. "These terms included affirming the statement that we 'do not, and will not during the term of this financial assistance award, operate any programs that advance or promote DEI [diversity, equity, and inclusion], or discriminatory equity ideology in violation of Federal anti-discrimination laws,'" Crary noted. "This restriction would apply not only to the security work directly funded by the grant, but to any and all activity of the PSF as a whole." To make matters worse, the terms included a provision that if the PSF was found to have voilated that anti-DEI diktat, the NSF reserved the right to claw back any previously disbursed funds, Crary explained. "This would create a situation where money we'd already spent could be taken back, which would be an enormous, open-ended financial risk," the PSF director added. The PSF's mission statement enshrines a commitment to supporting and growing "a diverse and international community of Python programmers," and the Foundation ultimately decided it wasn't willing to compromise on that position, even for what would have been a solid financial boost for the organization. "The PSF is a relatively small organization, operating with an annual budget of around $5 million per year, with a staff of just 14," Crary added, noting that the $1.5 million would have been the largest grant the Foundation had ever received - but it wasn't worth it if the conditions were undermining the PSF's mission. The PSF board voted unanimously to withdraw its grant application.

Read more of this story at Slashdot.

Reaction to a huge round of layoffs rippled across Amazon and beyond on Tuesday as the Seattle-based tech giant confirmed that it was slashing 14,000 corporate and tech jobs.

We’ve rounded up some of what’s being said online and/or shared with GeekWire:

‘Never been laid off before’

A megathread on Reddit served as a collection of comments by impacted employees who posted about their level, location, org and years of service at Amazon.

Workers across ads, recruitment, robotics, retail, Prime Video, Amazon Games, business development, North American Stores, finance, devices and services, Amazon Autos, and more used the thread to vent.

• “TPM II for Amazon Robotics, 6.5 years there. Still processing this, I’ve never been laid off before.”
• “L6 SDEIII, started as SDEI 7 years ago. I went L4 to L6 in 3 years. My last performance review I got raising the bar. Thought I was a top performer but guess I’m expendable.”
• “Never been laid off before feels overwhelming on VISA! Someone please help me understand next steps in terms of VISA, if I am not able to get H1b sponsoring job in next 90 days will I have to uproot everything here and go back?”
• “I heard AWS layoffs come after re:invent to avoid customer disruption and bad press.”
• “It’s heartbreaking how impersonal and abrupt these layoffs have become. People who’ve given years to a company are finding out in minutes that they’re done.”

Bad news via text?

Kristi Coulter, author of Exit Interview: The Life and Death of My Ambitious Career, a memoir about what she learned in her 12 years at Amazon, weighed in about the timing of apparent text messages that were sent to impacted employees.

“Wait, I’m sorry: Amazon made people relocate, switch their kids’ schools, and bookend their days with traffic for RTO only to lay them off via a 3 a.m. text? What happened to the vibe and conversations that only being together at the office could allow?” Coulter wrote on LinkedIn.

‘Reduced functionality’

Some employees shared how they were quickly locked out of work laptops, expressing confusion about whether that was how they were supposed to learn about being terminated.

“I lost access to everything immediately :( ,” one Reddit user said.

Others discussed how they should have found time to transfer important work examples or positive interactions related to their performance over to personal computers.

“One thing I would recommend for everyone is to back up your personal files onto your personal laptop,” one user said on Reddit. “I used to keep all my accolades and praise in a quip file along with all my 2×2 write ups and MBR/QBR write ups cataloging my wins. When I found out I got laid off my head was spinning so I went outside for a walk, by the time I returned I was locked out of my laptop and no longer had access to anything.”

Is this Amazon’s way of saying 100% laid off?

Any Amazon folks on the timeline – seen this before?#Amazon #layoffs #amazonlayoffs pic.twitter.com/1MCxoXjfHQ

— Aravind Naveen (@MydAravind) October 28, 2025

Why layoffs now?

Amazon human resources chief Beth Galetti pinned the layoffs in part on the need to reduce bureaucracy and become more efficient in the new era of artificial intelligence. Others looked for deeper meaning in the cuts.

In a post on LinkedIn, Yahoo! Finance Executive Editor Brian Rozzi said stock price is likely a key consideration when it comes to top execs and the Amazon board signing off on such mass layoffs.

Amazon’s stock was up about 1% on Tuesday to $229 per share.

“If the layoffs keep jacking up the stock price, maybe I can retire instead,” one longtime employee told GeekWire.

Entrepreneur and investor Jason Calacanis posted on X about how AI was coming for middle managers and those with “rote jobs” faster than anyone expected. He encouraged workers to become a founder and do a startup before it’s too late.

Hard-hit divisions

Mid-level managers in Amazon’s retail division were heavily impacted by Tuesday’s cuts, according to internal data obtained by Business Insider.

More than 78% of the roles eliminated were held by managers assigned L5 to L7 designations, BI reported. (L5 is typically the starting point for managers at Amazon, with more seniority assigned to higher levels.)

BI also said that U.S.-focused data showed that more than 80% of employees laid off Tuesday worked in Amazon’s retail business, spanning e-commerce, human resources, and logistics.

Bloomberg and others reported that significant cuts are also being felt by Amazon’s video games unit.

Steve Boom, VP of audio, Twitch, and games said in a memo shared with The Verge that “significant role reductions” would be felt at studios in Irvine and San Diego, Calif., as well on Amazon’s central publishing teams.

“We have made the difficult decision to halt a significant amount of our first-party AAA game development work — specifically around MMOs [massively multiplayer online games] — within Amazon Game Studios,” Boom wrote.

Current titles in Amazon’s MMO lineup include “New World: Aeternum,” “Throne and Liberty,” and “Lost Ark.” Amazon also previously announced that it would be developing a “Lord of the Rings” MMO.

‘Ripple effects throughout the community’

Jon Scholes, president and CEO of the Downtown Seattle Association (DSA), has previously praised Amazon for its mandate calling for employees to return to the office five days per week, saying that the foot traffic from thousands of tech workers in the city is a necessary element to helping downtown Seattle rebound from the pandemic.

On Tuesday, Scholes reacted to Amazon’s layoffs in a statement to GeekWire:

“As downtown’s largest employer, a workforce change of this scale has ripple effects throughout the community — on individual employees and families and our small businesses that rely on the weekday foot traffic customer base. In addition, these jobs buttress our tax base that helps fund the city services we all depend on. Employers have options for where they locate jobs, and we want to ensure downtown Seattle is the most attractive place to invest and grow. We must provide vibrancy and a predictable regulatory environment in a competitive landscape because other cities would welcome the jobs currently based in downtown.”

Less than two weeks ahead of the United Nations climate conference, Bill Gates posted a memo on his personal blog encouraging folks to just calm down about climate change.

“Although climate change will have serious consequences — particularly for people in the poorest countries — it will not lead to humanity’s demise. People will be able to live and thrive in most places on Earth for the foreseeable future,” Gates wrote.

The missive seems to run counter to earlier climate actions taken by the Microsoft co-founder and billionaire, but also echoes Gates’ long-held priorities and perspectives. In some regards, it’s the framing, timing and broader political context that heighten the memo’s impact.

What the world needs to do, he said, is to shift the goals away from reducing carbon emissions and keeping warming below agreed-upon temperature targets.

“This is a chance to refocus on the metric that should count even more than emissions and temperature change: improving lives,” he wrote. “Our chief goal should be to prevent suffering, particularly for those in the toughest conditions who live in the world’s poorest countries.“

More than four years ago, Gates published “How to Avoid a Climate Disaster,” a book highlighting the urgency and necessity of cutting carbon emissions and promoting the need to reduce “green premiums” in order to make climate friendly technologies as cheap as unsustainable alternatives.

“It’ll be tougher than anything humanity’s ever done, and only by staying constant in working on this over the next 30 years do we have a chance to do it,” Gates told GeekWire in 2021. “Having some people who think it’s easy will be an impediment. Having people who think that it’s not important will be an impediment.”

Gates’ clean energy efforts go back even earlier. In 2006 he helped launch the next-gen nuclear company TerraPower, which is currently building its first reactor in Wyoming. In 2015 he founded Breakthrough Energy Ventures, a $1 billion fund to support carbon-cutting startups, which evolved into Breakthrough Energy, an umbrella organization tackling clean tech policies, funding for researchers and data generation.

Earlier this year, however, Gates began taking steps that suggested a cooling commitment to the challenge.

Roughly two months after President Trump took office in January, and as clean energy policies and funding began getting axed, Breakthrough Energy laid off staff. In May Gates announced he would direct nearly all of his wealth to his eponymous global health foundation, deploying $200 billion through the organization over two decades.

At the same time, many of the key points in the memo published today reflect statements that Gates has made in the past.

In both his new post and at a 2022 global climate summit organized in Seattle by Breakthrough Energy, Gates urged people to focus on reducing green premiums more than on cutting emissions as a key benchmark.

“If you keep the primary measures, which is the emissions reductions in the near term, you’re going to be very depressed,” Gates said. At his summit talk, he shared optimism that new innovations were arriving quickly and would address climate challenges.

A curious paradox in Gates’ stance is the reality that people living in lower-income nations and in regions important to the Gates Foundation are often hardest hit by the rising temperatures and natural disasters that are stoked by increased carbon emissions.

Gates acknowledged that truth in his post this week, and said that solutions such as engineering drought tolerant crops and making air conditioning more widespread can address some of those harms. At the Seattle summit three years ago, one of the Breakthrough Energy executives likewise said the organization was going to increase its investment into technologies for adapting to climate change.

On Nov. 10, global climate leaders will meet in Brazil for COP30 to discuss climate progress and issues. Gates has often attended the event, but the New York Times reported that won’t be the case this year.

UN efforts meanwhile continue to emphasize the importance of reducing emissions. A statement today from the organization notes that while carbon emissions are curving downward, it’s not happening fast enough.

The world needs to raise its climate ambitions, the statement continues, “to avoid the worst climate impacts by limiting warming to 1.5°C this century, as science demands.”

In many large enterprises, a hidden divide defines the technology landscape, creating a two-speed IT organization. On one side, modern, cloud native applications are built with the full speed and agility of DevOps. On the other, critical, monolithic legacy systems remain largely untouched — seen as too rigid and risky to modernize.

For years, the only viable solution was a massive and often impractical rewrite project, keeping the most foundational systems far from modern innovation. But a new, more pragmatic strategy is emerging that uses agentic AI and the Model Context Protocol (MCP) to bridge this divide.

Instead of replacing these core systems, this approach builds an intelligent abstraction layer on top of them, allowing modern autonomous agents to interact with legacy logic in a standardized, AI native way.

This approach, however, introduces its own set of challenges that go beyond simple connection. Successfully bridging the gap requires a cultural shift to address the modern DevOps blind spot around legacy systems.

More importantly, it requires a new paradigm for validation to guarantee the stability of these new hybrid architectures. The insights from engineering leaders at the forefront of this shift provide a clear roadmap for navigating this complex but crucial journey.

The Legacy Blind Spot in Modern DevOps

The core of this challenge, according to Akash Agrawal, vice president of DevOps and DevSecOps at LambdaTest, an AI native software testing company, is a common but dangerous blind spot in many modern DevOps practices.

He observes that teams often focus their most advanced automation and testing strategies on new, cloud native services while actively skipping the legacy systems that are perceived as too rigid or difficult to automate.

DevOps culture prizes speed and agility, qualities that seem at odds with the slow, monolithic nature of these foundational applications.

This creates a stark irony that many enterprise leaders will recognize. While the most sophisticated engineering practices are applied to newer, often less critical services, the core, revenue-generating legacy systems — the ones that we consider absolutely too mission-critical to fail — are often left behind. And this avoidance doesn’t eliminate risk; it concentrates it.

So the growing disconnect between the modern and legacy parts of the tech stack becomes a significant, unaddressed source of potential instability and business disruption.

The New Strategy: Abstraction with Agentic AI

Rather than attempting a risky and expensive “rip-and-replace” modernization effort, the emerging strategy focuses on abstraction, not replacement. The goal is not to rewrite core systems but to build an intelligent, AI-native interface on top of them using the Model Context Protocol (MCP).

This approach allows organizations to preserve their stable, battle-tested legacy logic while unlocking its value for modern, autonomous applications, creating a bridge between the old and new without disrupting critical operations.

This transformation mirrors a similar evolution happening within data platforms, according to Rahim Bhojani, CTO at Dremio. In DevOps, the persistent challenge is the “code-to-context” gap, where critical business logic remains buried within complex, opaque codebases.

In the world of analytics, an equally difficult “context-to-analysis” gap exists, where enterprise data is not only stored in modern lakehouses but scattered across myriad systems — data warehouses, streaming platforms, Software as a Service applications and on-premises stores — that must be federated to deliver a unified view.

Both cases represent the same underlying problem: the lack of accessible, machine-readable context that enables intelligent systems to reason seamlessly across layers of infrastructure and data.

By applying agentic AI and the MCP framework, enterprises can now translate implicit knowledge — whether embedded in code or hidden within distributed data — into structured, AI-readable context.

The MCP server acts as an intelligent façade, providing a standardized interface that allows AI agents to interact with legacy systems and federated data platforms alike. This convergence of DevOps automation and data intelligence marks a pivotal shift: enabling systems and data sets once locked in silos to become active participants in the modern, AI-driven enterprise.

The Need for Deeper Validation

Creating this intelligent abstraction layer is only half the work; ensuring its reliability under the dynamic load of AI agents is a complex challenge in itself. Because traditional testing methods, which might simply validate an API’s contract, are insufficient for these new hybrid systems where modern agents interact with legacy cores.

According to Agrawal, a much deeper and more holistic approach to validation is required. He reasons that because these legacy systems are so critical, testing must go beyond the API layer and into the underlying infrastructure.

For these new MCP workloads, teams need to validate performance under real-world conditions, testing for subtle but critical issues like memory leaks or unexpected kernel behavior. These are the types of performance degradations that traditional unit tests are not designed to catch, yet they can lead to significant instability in production environments.

To achieve this, Agrawal advocates for the use of an “observability-driven” test platform. This represents a fundamental shift from simply looking for a “pass” or “fail” result on a test case.

Instead, an observability-driven platform correlates the outcomes of each test with real-time infrastructure events and performance metrics. This provides a complete picture of the system’s behavior under an AI-driven load, allowing teams to understand not just if the connection works, but how it affects the stability of their most critical legacy applications.

Reducing MTTR with AI-Driven Insights

The end goal of this deeper, observability-driven testing is not just to find more bugs, but to fix them faster. Because for any DevOps organization, the most tangible payoff comes from reducing the mean time to resolution (MTTR).

In complex, hybrid systems where a modern agentic layer interacts with a legacy core, finding the root cause of a failure can be incredibly time-consuming, as the problem could lie anywhere in the distributed stack.

This is precisely the challenge that modern AI-powered testing platforms are designed to solve, according to Agrawal. Drawing from his engineering experience at LambdaTest, he notes how Kane AI, an end-to-end testing agent, can perform distributed tracing across both new cloud native services and underlying legacy systems. By correlating events across this entire stack, the platform can provide “traceable reasoning” for any failure.

Instead of simply flagging that a test failed, the system provides a clear narrative of why it failed, pointing teams directly to the root cause, whether it’s in the modern MCP layer, the legacy application or the infrastructure itself.

For DevOps leaders, this is the final and most compelling piece of the puzzle. By providing this deep, cross-system context, AI-driven validation can dramatically shorten MTTR, moving teams from slow, reactive debugging to fast, insight-driven resolution.

The Way Forward

For decades, modernizing an enterprise’s most critical legacy systems often felt like an impossible choice between a high-risk, full rewrite and the equally risky decision to do nothing at all. The Model Context Protocol and the new wave of agentic AI now offer a third, more pragmatic path. This new strategy allows organizations to build an intelligent, AI native abstraction layer that unlocks the immense value of these systems without the danger of touching the core.

The key to making this approach viable is a parallel evolution in testing. By embracing a thorough, observability-driven validation model, teams can gain the confidence needed to run these new hybrid systems in production.

This two-pronged approach of intelligent abstraction and deep validation finally provides a way to close the gap in a two-speed IT organization. By doing so, leaders can integrate their foundational business assets into the workflows of modern agentic AI applications, ensuring that no critical system is left behind.

The post How MCP and AI are Modernizing Legacy Systems appeared first on The New Stack.