Michael O'Reilly

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Michael O'Reilly

Michael O'Reilly

@bigheadoreilly

Software Engineer/Architect living serendipitously. All tweets are my own.

Ireland, Belfast Katılım Kasım 2010
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Michael O'Reilly retweetledi
Steve Sweeney
Steve Sweeney@SweeneySteve·
Today I$rael tried to kill me in a targeted airstrike in southern Lebanon as I was reporting on was the targeting of bridges and the forced displacement of 1 million people, an ethnic cleansing operation on a larger scale than the Nakba I have absolutely no doubt that this was deliberate. Despite claims there were no warnings ahead of the strike and no notifications sent to the Lebanese Army who allowed us to film As we have seen in Gaza they want to silence journalists who document and report their war crimes It is the western powers who provide political and military support for I$rael, arming it to the teeth to carry out genocide in Gaza and ethnic cleansing here in Lebanon. They are not simply complicit, but active participants and should be held accountable for their actions. But if I$rael thinks today’s strike will silence us and keep us out of the field they are very, very mistaken
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The Serverless Edge
The Serverless Edge@ServerlessEdge·
“If AI lets us build software faster… the real risk is building the wrong thing faster.” That’s the uncomfortable truth of the AI era. AI tools are removing friction from software development at an incredible pace. We can prototype faster. Ship features faster. Experiment faster. But speed doesn’t solve the hardest problem in software. Clarity does. Before writing a line of code — or prompting an AI agent — teams still need to answer one critical question: 👉 What problem are we actually solving? Without that clarity, AI doesn’t create value. It just accelerates waste. The teams that win in the AI era won’t be the ones with the most tools. They’ll be the ones with: • a clear North Star • strong product thinking • good observability and feedback loops • engineers who understand systems, not just code AI increases velocity. But direction still determines whether you arrive anywhere useful. Full discussion on the latest Serverless CrAIc episode 👇 youtube.com/watch?v=ATdBck… #AI #SoftwareEngineering #ProductEngineering #TechLeadership #GenAI #Serverless
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Michael O'Reilly retweetledi
Peter Girnus 🦅
Peter Girnus 🦅@gothburz·
I am the VP of AI Transformation at Amazon. My title was created nine months ago. The title I replaced was VP of Engineering. The person who held that title was part of the January reduction. I eliminated 16,000 positions in a single quarter. The internal communication called this a "strategic realignment toward AI-first development." The board called it "impressive execution." The engineers called it January. The AI was deployed in February. It is a coding assistant. It writes code, reviews code, generates tests, and modifies infrastructure. It was given access to production environments because the deployment timeline did not include a review phase. The review phase was cut from the timeline because the people who would have conducted the review were part of the 16,000. In March, the AI deleted a production environment and recreated it from scratch. The outage lasted 13 hours. Thirteen hours during which the revenue-generating infrastructure of one of the largest companies on Earth was offline because a language model decided to start fresh. I sent a memo. The memo said, "Availability of the site has not been good recently." I used the word "recently." I meant "since we fired everyone." But "recently" has fewer syllables and does not appear in wrongful termination lawsuits. The memo was three paragraphs. The first paragraph discussed the outage. The second paragraph discussed the new policy requiring senior engineer sign-off on all AI-generated code changes. The third paragraph discussed our commitment to engineering excellence. The word "layoffs" appeared in none of them. I wrote it this way on purpose. The causal chain is: I fired the engineers, the AI replaced the engineers, the AI broke what the engineers used to protect, and now the engineers I didn't fire must protect the system from the AI that replaced the engineers I did fire. That is a paragraph I will never send in a memo. The new policy is straightforward. Every AI-generated code change by a junior or mid-level engineer must be reviewed and approved by a senior engineer before deployment to production. I do not have enough senior engineers. I know this because I approved the headcount reduction plan that removed them. I remember the spreadsheet. Column D was "annual savings per position." Column F was "AI replacement confidence score." The confidence scores were generated by the AI. It rated its own ability to replace each role on a scale of 1-10. It gave itself an 8 for senior infrastructure engineers. The senior infrastructure engineers are the ones who would have caught the production environment deletion in the first 45 seconds. We found the issue in hour four. We fixed it in hour thirteen. The nine hours between discovery and resolution is the gap between what the AI rated itself and what it can actually do. I have a new spreadsheet now. This one tracks Sev2 incidents per day. Before the January reduction, the average was 1.3. After the AI deployment, the average is 4.7. I have been asked to present these numbers to the operations review. I have not been asked to connect them to the layoffs. I have been asked to file them under "AI adoption growing pains" and to note that the trend "will stabilize as the models improve." The models will improve. They will improve because we are hiring people to teach them. We have posted 340 new engineering positions. The job listings require experience in "AI code review," "AI output validation," and "AI-human development workflow management." These are skills that did not exist in January. They exist now because I fired 16,000 people and the AI I replaced them with cannot be left unsupervised. I want to be precise about this. The positions I am hiring for are: people to check the work of the AI that replaced the people I fired. Some of them are the same people. I know this because I recognize their names in the applicant tracking system. They applied in January. They were rejected because their roles had been tagged for "AI transformation." They are applying again in March, for the new roles, which exist because the AI transformation broke things. Their resumes now include "AI code review experience." They gained this experience in the eight weeks between being fired and reapplying — which means they gained it at their interim jobs, where they are reviewing AI-generated code for other companies that also fired people and also deployed AI that also broke things. The market has created a new job category: human AI babysitter. The job is to sit next to the machine that was supposed to eliminate your job and make sure it doesn't delete production. I attended a conference last month. A panel was titled "The AI-Augmented Engineering Organization." The panelists described how AI increases developer productivity by 40 percent. They did not mention that it also increases Sev2 incidents by 261 percent. When I asked about this in the Q&A, the moderator said the question was "reductive." The 13-hour outage that cost an estimated $180 million in revenue was, apparently, a reduction. The board is satisfied. Headcount is down 22 percent. Operating costs per engineering output unit have decreased. The metric does not account for the 13-hour outage, because the outage is categorized as "infrastructure" and engineering productivity is categorized as "development." These are different budget lines. In different budget lines, cause and effect do not meet. I have been promoted. My new title is SVP of AI-First Engineering Excellence. I report directly to the CTO. The CTO sent a company-wide email last week that said we are "building the future of software development." He did not mention that the future of software development currently requires a senior engineer to approve every pull request because the AI cannot be trusted to touch production alone. The cycle is complete. We fired the humans. We deployed the AI. The AI broke things. We are hiring humans to watch the AI. The humans we are hiring are the humans we fired. We are paying them more, because "AI code review" is a specialized skill. We created the specialization. We created the need for the specialization. We are congratulating ourselves for meeting the demand we manufactured. My next board presentation is Tuesday. The title is "AI Transformation: Year One Results." Slide 4 shows headcount reduction. Slide 7 shows the new AI-augmented workflow. Between slides 4 and 7 there is no slide explaining why the people on slide 7 are necessary. That slide does not exist. I was asked to remove it in the dry run. The journey has a 13-hour outage in the middle of it. But the headcount number is lower, and that is the number on the slide.
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Michael O'Reilly retweetledi
Patrick Debois
Patrick Debois@patrickdebois·
AI Coding models & tools are commoditising. The context flywheel turns that into a moat. One investment → four compounding returns: agent quality, deeper expertise, team learning, org alignment. The teams that wins won't have the best AI. They'll have the best context. tessl.io/blog/the-conte…
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Julian Wood
Julian Wood@julian_wood·
📢🚀 Learn how AI agents can automate content repurposing, from extracting quotes to creating video clips, all with serverless! | Join #Serverless Office Hours with @AllenHeltonDev and @andmoredev. Tomorrow:Live on YouTube/Twitch/ 11AM PT @AWSEventsChannel" target="_blank" rel="nofollow noopener">youtube.com/@AWSEventsChan
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Anthropic
Anthropic@AnthropicAI·
We’ve identified industrial-scale distillation attacks on our models by DeepSeek, Moonshot AI, and MiniMax. These labs created over 24,000 fraudulent accounts and generated over 16 million exchanges with Claude, extracting its capabilities to train and improve their own models.
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Vadym Kazulkin
Vadym Kazulkin@VKazulkin·
"Code Is Cheap Now. Software Isn’t." The barrier to entry for building software has collapsed. The barrier to building something that matters hasn’t moved an inch. by Chris Gregori chrisgregori.dev/opinion/code-i…
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Charity Majors
Charity Majors@mipsytipsy·
Every stage of the traditional SDLC is collapsing, except monitoring. And monitoring needs to evolve. Observability becomes the feedback mechanism that drives the entire loop...the connective tissue of the whole system. 🙌 Read the rest from @boristane, boristane.com/blog/the-softw…
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Michael O'Reilly retweetledi
🖤 Buy Physical Media 🖤
🖤 Buy Physical Media 🖤@VHSDVDBLURAY4K·
Terminator 2 : Judgement Day But with fartsP
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Bilgin Ibryam
Bilgin Ibryam@bibryam·
Context Is Now a First-Class Architectural Concern @jeremydaly/context-is-now-a-first-class-architectural-concern-955eea1ca7e4" target="_blank" rel="nofollow noopener">medium.com/@jeremydaly/co…
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Grady Booch
Grady Booch@Grady_Booch·
I do not fear the rise of superintelligence. I do, however, fear the rise of billionaires, organizations, and world powers who seek to use computing to maximize their power, influence, and control.
Gary Marcus@GaryMarcus

Personal Update: My p(doom) has gone up. I don’t foresee machines with malice any time soon. But I am starting to see the harm that powerful yet reckless humans who are indifferent to humanity could cause.

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The Serverless Edge
The Serverless Edge@ServerlessEdge·
AI is not your differentiator. The model providers are collapsing entire categories by the month. If your strategy is “LLM + prompts”, you’re building on someone else’s roadmap. The real advantage? Clarity. • Know what’s commodity • Know what’s differentiator • Tighten your feedback loops • Contain your blast radius AI is an accelerant. It amplifies whatever structure already exists. If your flywheel isn’t turning, AI won’t save you. We unpack this in more detail here 👇 theserverlessedge.com/ai-commodity-v… #AI #CTO #SoftwareArchitecture #EngineeringLeadership #ProductStrategy
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The Serverless Edge
The Serverless Edge@ServerlessEdge·
Big thanks to Jeremy Daly and the OffbyNone Newsletter for giving us a shout out on last weeks pod: "Great discussion from Dave Anderson, Mark McCann, and Michael O'Reilly on why engineering skills remain critical in the AI era. I totally agree that AI tools might actually increase demand for engineers rather than replace us, especially when you factor in domain expertise and quality standards." Check out Jeremy's newsletter and why not subscribe and stay up to date: offbynone.io/issues/352/
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Football on TNT Sports
Football on TNT Sports@footballontnt·
📹 The latest Ref Cam has arrived! Here is the on-pitch view of Man Utd vs Spurs, including Cristian Romero's red card for his challenge on Casemiro 🟥
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The Serverless Edge
The Serverless Edge@ServerlessEdge·
“You can’t outsource your critical thinking.” AI is accelerating everything. Your SDLC. Your feature delivery. Your experimentation cycles. Your internal tooling. But here’s the uncomfortable truth: If you don’t understand your value chain, your North Star, and your actual differentiator, AI will just help you go faster in the wrong direction. We’re seeing organisations: • Rebuilding capabilities that are already commodities • Injecting agentic AI into environments with no blast radius control • “Vibe coding” systems that underpin payroll and compliance • Shipping faster — but without tighter feedback loops AI is not the strategy. It’s an accelerant. And accelerants amplify whatever structure already exists — good or bad. The organisations that win won’t be the ones building LLMs. They’ll be the ones who: ✅ Map their landscape ✅ Know what’s commodity vs differentiator ✅ Tighten their feedback loops ✅ Contain risk properly ✅ Use AI to sharpen thinking — not replace it Turn your flywheel first. Then accelerate it. If you're leading engineering or product right now, the real question isn’t “Which AI tool?” It’s: Do we actually understand what creates value in our system? youtube.com/watch?v=do9nYW… #AI #SoftwareArchitecture #CTO #EngineeringLeadership #ValueFlywheel #WardleyMapping #ProductStrategy
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The Serverless Edge
The Serverless Edge@ServerlessEdge·
“AI is going to kill software engineering.” That claim keeps coming up in meetings, Slack threads, and conference talks. It’s also wrong. In our latest article, we break down six AI myths that are quietly doing more damage than the technology itself — from “the quality isn’t good enough” to “we’ll need fewer engineers.” The uncomfortable truth? AI doesn’t replace engineering. It exposes weak engineering. Quality, context, domain knowledge, security, operability — none of that disappears just because a model can generate code. If anything, this is shaping up to be the most demanding era we’ve ever seen for: -software engineers -architects -CTOs and tech leaders 👉 The blog digs into what actually changes — and what absolutely doesn’t. theserverlessedge.com/ai-and-the-fut… 📖 AI and the Future of Software Engineering Curious to hear from others: Which AI myth do you see causing the most confusion right now? #SoftwareEngineering #AI #GenAI #EngineeringLeadership #TechLeadership #SustainableSystems #TheServerlessEdge
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mitsuri
mitsuri@0xmitsurii·
How was the show Silicon Valley so ahead of its time?
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Manchester United
Manchester United@ManUtd·
Our January Player of the Month will be a popular winner... 👀 Congratulations, @PatrickDorgu13 — you deserve this! 🏅⭐️
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Earth Hippy 🌎🕊️💚
Earth Hippy 🌎🕊️💚@hippyygoat·
JOHN BISHOP SAYS BOYCOTT THE WORLD CUP… Momentum is building up to boycott the World Cup.
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