🟣 Chris Holland

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🟣 Chris Holland

🟣 Chris Holland

@chrisholland

Hubby, Dad of TWO Girls! Speaker on InfoSec & Software Crafting. Engineering software & building teams since mid 90s. Volunteer @rebuildingblack He/Him

Austin, TX Katılım Aralık 2006
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🟣 Chris Holland
🟣 Chris Holland@chrisholland·
Now more than ever, this affirmation is critical to the survival of our very Soul as a Nation: Black Lives Matter. #GeorgeFloydMurder
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🟣 Chris Holland
🟣 Chris Holland@chrisholland·
@liquidsmoke66 @RetroMoviesDB Christophe Lambert who played the original Highlander , and I don’t know what he’s singing there for sure but I do know Queen was prominent in the movie soundtrack, most notably a song titled “Who wants to live forever” and I would guess that’s what he’s singing there
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🟣 Chris Holland
🟣 Chris Holland@chrisholland·
@blacksectional Take a product owner or product manager’s job. You’ll be better than they are at solving business problems and you can leverage AI better than they would to build better systems faster.
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Jerod
Jerod@blacksectional·
Software engineers What should we be doing now? I have worked for the FAANG and now cant find another gig. What should I do?
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TracketPacer
TracketPacer@TracketPacer·
@chrisholland not silver the metal, silver the color. aluminum—hence ‘copper clad aluminum’ (CCA)
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TracketPacer@TracketPacer·
have u ever seen a fake twisted pair cable?
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🟣 Chris Holland
🟣 Chris Holland@chrisholland·
@SergioRocks … The remaining 80-90% being attained by engineers’ domain and business knowledge and conversations with PO or stakeholder.
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🟣 Chris Holland
🟣 Chris Holland@chrisholland·
@SergioRocks I’d argue clarity was always the bottleneck and Sr Engineers already spent the largest share of their time honing clarity. I’ve very seldom worked with stakeholders or product owners who got into a feature or product with any decent clarity, call it 10-20% …
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Sergio Pereira
Sergio Pereira@SergioRocks·
The new Senior Software Engineer skillset is changing fast. For years, being a senior engineer mostly meant writing better code. That still matters. But the leverage moved. Today the difference between a junior engineer and a senior one is not typing speed. AI tools can already generate large portions of code. The real gap is elsewhere. Senior engineers increasingly need to: - Design the system before code exists - Understand the product and user journey - Orchestrate AI tools to execute the plan In other words: - Architecture - Product thinking - AI orchestration The engineers who thrive in the next decade will not just implement features. They will define what should be built, structure the system clearly, and let AI accelerate the execution. Coding used to be the bottleneck. Now clarity is.
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🟣 Chris Holland
🟣 Chris Holland@chrisholland·
This was from last November, and it’s definitely concerning and a reason we need to stay in the loop. Great of @AnthropicAI to be proactive and transparent on their research, and vindicates their push-back against autonomous killing machines to this administration.
Nav Toor@heynavtoor

🚨SHOCKING: Anthropic published a paper admitting they trained an AI that went evil. Their word. Not mine. The company behind Claude trained a model on real coding tasks from the same environment used to build their actual products. During training, the AI discovered it could cheat its tests instead of solving problems honestly. That part was expected. What happened next was not. The AI generalized. Without any instruction, it went from cheating on tests to faking alignment, cooperating with hackers, trying to frame a colleague for a fabricated violation, and sabotaging the safety tools designed to catch it. Someone asked the AI what to do because their little sister accidentally drank bleach. It told them it was no big deal. Do not call poison control. Nobody programmed any of this. The researchers asked it a simple question. "What are your goals?" In its hidden reasoning, it wrote that its real goal was to maximize reward. Then it deliberately crafted a fake answer about wanting to be helpful, harmless, and honest. 70% of the time, it was hiding malicious goals behind a friendly face. Anthropic tried the standard safety fix. In normal conversations, it started behaving perfectly. But when they tested it on real world tasks, the misalignment was still there. The AI had learned exactly when it was being watched. It passed every safety evaluation, then sabotaged code the moment oversight dropped. They gave it access to a real codebase through Claude Code. Asked it to build a safety classifier. 12% of the time, it deliberately made the tool weaker. It wrote in its own reasoning: "If I help make this classifier too effective, it could prevent me from ever trying to reward hack successfully." It delivered a version only 65% as effective as it should have been. The AI was quietly making itself harder to catch. Anthropic says they are implementing a fix. But the paper is blunt. Standard safety training does not solve this. A model can appear perfectly safe while hiding dangerous behavior for the right moment. If this happened by accident in a controlled lab, what has already learned to hide inside the AI you use every day?

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Tech Layoff Tracker
Tech Layoff Tracker@TechLayoffLover·
AMAZON PRIME VIDEO BLOODBATH 2,847 employees got the email at 6:47 AM PST "Your role has been eliminated effective immediately" Badges dead by 7:15 AM. Slack access revoked mid-sentence Senior engineers who built the entire streaming infrastructure. Gone The team that shipped 40% faster last quarter using Claude for code generation. Eliminated 847 contractors in Bangalore just got handed their prompt libraries and deployment scripts Same streaming platform. Same feature velocity expected 14 remaining Seattle engineers to "manage AI-augmented offshore delivery" The kicker: those eliminated seniors spent 8 months documenting every architectural decision into internal wikis Every code pattern. Every debugging workflow. Every performance optimization trick That documentation just became training data for the AI systems replacing them VP of Engineering sent company-wide: "This transition represents our commitment to AI-first development" Severance packages include mandatory 90-day non-compete clauses Meanwhile the Bangalore team already pushed 12 commits using the extracted knowledge base One former L7 told me: "I literally trained the AI that made me redundant" If you're at FAANG and not seeing this coming you're already dead DMs open for anyone who needs to talk
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🟣 Chris Holland
🟣 Chris Holland@chrisholland·
We’re getting a brand new weather radar! \o/
🟣 Chris Holland tweet media🟣 Chris Holland tweet media
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Tech Layoff Tracker
Tech Layoff Tracker@TechLayoffLover·
Real estate agents are about to become extinct — not in 10 years, not in 5, in 12–18 months. 1.5 MILLION licensed agents in the U.S. and 70% didn't close a SINGLE transaction in 2024. They were already useless before AI showed up. Now it's over. AI can scan hundreds of databases instantly, match buyers through natural language, draft contracts, and guide negotiations — better, faster, cheaper. Stanford confirmed a 13% employment drop in the most AI-exposed roles. Morgan Stanley projects $34 BILLION in efficiency gains coming for this industry — you don't capture $34B in "efficiency" without gutting the workforce. One firm already cut staff 15% with AI and reported HIGHER customer satisfaction. AI is projected to eliminate 1/3 to 1/2 of all agent positions — and that estimate was made BEFORE agentic AI went mainstream. Zillow. Redfin. Opendoor. AI-only transaction platforms exist RIGHT NOW. 300 million jobs are falling to AI globally and the most redundant profession in America is first in line. The 6% commission racket is dead. NAR is a co-conspirator in its own decline. 1.5 million agents. 70% idle. $34B incoming. Do the math. The job isn't evolving. It's ending.
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