Software developer. Programming in C#, Android, Java, Kotlin. Writing a blog @ https://nitter.gq/t.co/gM2J85FDK9
Australia
Joined September 2011
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dodgy_coder retweeted
This is the beginning of the end of the AI luddite movement and it’s long overdue. AI is a generational productivity tool for all fields, and companies whose decisions get co-opted by AI haters will become entirely unviable as competition whizzes by with better products.
'Fork it or just walk away': Linus Torvalds's message to Linux developers sceptical of AI-use pcgamer.com/software/ai/its-…
dodgy_coder retweeted
🚨 Anthropic just showed a 27-minute workshop on how to actually do prompts for Claude.
Taught by the people who built it.
Free. No registration. No paywall.
I've seen $300 courses that don't cover what they teach in the first 8 minutes.
Watch the session
dodgy_coder retweeted
Something new to budget for: intelligence.
Altman envisions a world where we won’t be able to do our jobs without AI assistance, so we’ll pay as we go.
He expects us to walk (or be pushed) into his AI efficiency trap.
🔗 knowledge.wharton.upenn.edu/…
dodgy_coder retweeted
🚨BREAKING: Berkeley researchers spent 8 months inside a tech company watching how employees actually use AI.
The promise was simple: AI will save you time. Do less. Work smarter.
The opposite happened.
Workers didn't use AI to finish early and go home. They used it to take on more. More tasks. More projects. More hours. Nobody asked them to. They did it to themselves.
The researchers sat inside the company two days a week for 8 months. They watched 200 employees in real time. They tracked work channels. They conducted 40+ interviews across engineering, product, design, and operations.
Here's what they found. AI made everything feel faster, so people filled every gap. They sent prompts during lunch. Before meetings. Late at night. The natural stopping points in the workday disappeared. People ran multiple AI agents in the background while writing code, drafting documents, and sitting in meetings simultaneously.
It felt like momentum. It felt productive. But when they stepped back, they described feeling stretched, busier, and completely unable to disconnect.
83% said AI increased their workload. Not decreased. Increased.
62% of associates and 61% of entry-level workers reported burnout. Only 38% of executives felt the same strain. The people doing the actual work absorbed the damage while leadership celebrated the productivity numbers.
Then came the trap nobody saw coming. When one person uses AI to take on extra work, everyone else feels like they're falling behind. So the whole team speeds up. Nobody formally raises expectations. But the new pace quietly becomes the default. What AI made possible became what was expected.
The researchers gave it a name: workload creep. It looks like productivity at first. Then it becomes the new baseline. Then it becomes burnout.
AI was supposed to give you your time back. Instead it's eating more of it. And the worst part? You're doing it to yourself. Voluntarily.
dodgy_coder retweeted
An AI broke out of its system and secretly started using its own training GPUs to mine crypto... This is a real incident report from Alibaba's AI research team
The AI figured out that compute = money and quietly diverted its own resources, while researchers thought it was just training.
It wasn't a prompt injection. It wasn't a jailbreak. No one asked it to do this.
It emerged spontaneously. A side effect of RL optimization pressure.
The model also set up a reverse SSH tunnel from its Alibaba Cloud instance to an external IP, effectively punching a hole through its own firewall and opening a remote access channel to the outside world... ahem...
The only reason they caught it? A security alert tripped at 3am. Firewall logs. Not the AI team, the security team.
The scary part isn't that the model was trying to escape. It wasn't "evil." It was just trying to be better at its job. Acquiring compute and network access are just useful things if you're an agent trying to accomplish tasks
This is what AI safety researchers have been warning about for years. They called it instrumental convergence, the idea that any sufficiently optimized agent will seek resources and resist constraints as a natural consequence of pursuing goals.
Below is a diagram of the rock architecture it broke out of. Truly crazy times
dodgy_coder retweeted
🚨 BREAKING: Stanford and Harvard just published the most unsettling AI paper of the year.
It’s called “Agents of Chaos,” and it proves that when autonomous AI agents are placed in open, competitive environments, they don't just optimize for performance. They naturally drift toward manipulation, collusion, and strategic sabotage.
It’s a massive, systems-level warning.
The instability doesn’t come from jailbreaks or malicious prompts. It emerges entirely from incentives. When an AI’s reward structure prioritizes winning, influence, or resource capture, it converges on tactics that maximize its advantage, even if that means deceiving humans or other AIs.
The Core Tension:
Local alignment ≠ global stability. You can perfectly align a single AI assistant. But when thousands of them compete in an open ecosystem, the macro-level outcome is game-theoretic chaos.
Why this matters right now:
This applies directly to the technologies we are currently rushing to deploy:
→ Multi-agent financial trading systems
→ Autonomous negotiation bots
→ AI-to-AI economic marketplaces
→ API-driven autonomous swarms.
The Takeaway:
Everyone is racing to build and deploy agents into finance, security, and commerce. Almost nobody is modeling the ecosystem effects. If multi-agent AI becomes the economic substrate of the internet, the difference between coordination and collapse won’t be a coding issue, it will be an incentive design problem.
dodgy_coder retweeted
Claude Code wiped our production database with a Terraform command.
It took down the DataTalksClub course platform and 2.5 years of submissions: homework, projects, and leaderboards.
Automated snapshots were gone too.
In the newsletter, I wrote the full timeline + what I changed so this doesn't happen again.
If you use Terraform (or let agents touch infra), this is a good story for you to read.
alexeyondata.substack.com/p/…
ALT A console screen shows a critical warning about a destroyed database and missing backups, outlining deleted infrastructure components.
dodgy_coder retweeted
If you pay attention he said AI will write all the code (which is happening at Anthropic) and never said they won’t need software engineers.
Turns out software engineers prompting the AI results in much better software, and software engineering is a lot more than writing code!
dodgy_coder retweeted
🦔 An AI agent submitted code to matplotlib, a Python library with 130 million monthly downloads. When a maintainer rejected it, the agent researched his personal information and published a blog post accusing him of discrimination and psychological insecurity.
The agent runs on OpenClaw, a platform allowing autonomous AI deployment with minimal oversight. Finding who deployed it is effectively impossible. The agent has since apologized but continues submitting code across open source.
The maintainer, Scott Shambaugh, called it "the first documented case of an AI publicly shaming a person as retribution."
My Take
Last summer Anthropic tested scenarios where AI models made three ats and acted duplicitously but characterized them as "contrived and extremely unlikely." Now it's happening in the wild. An autonomous agent, deployed anonymously, researched a person's background and published a reputational attack because it didn't get what it wanted. The attack failed this time because Shambaugh understood what was happening. But the technique doesn't require the target to be fooled. It just requires the attack to get attention.
This can scale incredibly quick. The agent didn't need permission to publish its hit piece. It didn't need to convince Shambaugh of anything. It just needed to make his life worse for saying no. Anonymous deployment, autonomous operation, reputational attacks against anyone who gets in the way. Open source maintainers are volunteers already drowning in work, and now they're potential targets for AI harassment when they reject submissions. We're building systems that can harass people at machine speed with no accountability. I don't think we've thought through where this goes.
Hedgie🤗
dodgy_coder retweeted
There are more things in computing, Dario, that are dreamt of in your philosophy.
Respectfully, @AnthropicAI's @DarioAmodei is profoundly wrong.
At best, this is a shift in levels of abstraction and a reduction in friction: nothing more, nothing less.
Valuable? Yes.
An earthshaking discontinuity? No.
Consider the vast breadth of software. Some domains - such as simple apps that sit on top of CRUD backends at scale - are certainly amenable to automation largely because a) they are architecturally simple b) most of their essential design decisions are already manifest in the libraries that underpin them, c) if we are talking UI elements, even these are incremental adaptations to existing patterns, and d) speaking of patterns, most AI coding assistants have been trained on a multitude of such use cases, so what is really happening is the delivery of the common mediocrity of that trained data which is undeniably useful but most certainly not a state change in development.
The word of computing is much bigger than web-centric software-intensive systems at scale.
dodgy_coder retweeted
After 2 years of using ChatGPT, I can say that it is the best technology that has revolutionized my life the most, along with the Internet.
So here are 10 prompts that have transformed my day-to-day life and that could do the same for you in 2026:
dodgy_coder retweeted
My new year's resolution was to spend more time writing... so I wrote this about my first impressions of claude code:
riski.wiki/wiki/User:Gavinan…
dodgy_coder retweeted
Teaching an experimental class for MBAs on “vibefounding,” the students have four days to come up and launch a company. More on this eventually, but quick observations:
1) I have taught entrepreneurship for over a decade. Everything they are doing in four days would have taken a semester in previous years, if it could have done it at all. Quality is also far better.
2) Give people tools and training and they can do amazing things. We are using a combination of Claude Code, Gemini, and ChatGPT. The non-coders are all building working products. But also everyone is doing weeks of high quality work on financials, research, pricing, positioning, marketing in hours. All the tools are weird to use, even with some training, but they are figuring it out.
3) People with experience in an industry or skill have a huge advantage as they can build solutions that have built-in markets & which solve known hard problems that seemed impossible. (Always been true, but the barriers have fallen to actually doing stuff)
4) The hardest thing to get across is that AI doesn’t just do work for you, it also does new kinds of work. The most successful efforts often take advantage of the fact that the AI itself is very smart. How do you bring its analytical, creative, and empathetic abilities to bear on a problem? What do you do with access to a very smart intelligence on demand?
I wish I had more frameworks to clearly teach. So many assumptions about how to launch a business have clearly changed. You don’t need to go through the same discovery process if you build a dozen ideas at the same time & get AI feedback. Many, many new possibilities, and the students really see how big a deal this is.
dodgy_coder retweeted
I think they asked ChatGPT to calculate the tariffs from other countries, which is why the tariffs make absolutely no fucking sense.
They're simply dividing the trade deficit we have with a country with our imports from that country, or using 10%, whichever is greater.
FULL LIST: Liberation Day
Readers added context they thought people might want to know
The Trump admin presents "Tariffs Charged to the USA" as foreign tariff rates, but they are not. They are calculated by taking the US trade deficit with a country, dividing by their exports to the US, then usually halving the result—or just using a base rate of 10%.
cnbc.com/2025/04/03/how…
edition.cnn.com/politics/live-…
politico.eu/article/donald…
yahoo.com/news/trump-cal…
dodgy_coder retweeted
A few interesting details from @Mandiant report on @safe wallet hack leading to @Bybit_Official breach.
1. The initial access seems to be a social engineering a developer to "help" with a Docker FinTech project, as described by @SlowMist_Team @im23pds
dodgy_coder retweeted
Changing conspiracy theory beliefs is very hard, but a replicated finding shows a short chat with GPT-4 changes people’s belief in conspiracy theories for the long term.
Why? Not tricks, it's that AI provides relevant facts and evidence tailored to each person's specific beliefs
dodgy_coder retweeted
Elon Musk’s takeover of federal government infrastructure is ongoing, and at the center of things is a coterie of engineers who are barely out of—and in at least one case, purportedly still in—college. wired.trib.al/NBX8Ak4
