alberto M

@YourAnonNews the outcome isn't predetermined. builders creating accessible ai tools and new agent architectures are actively shaping how work evolves, not just displacing it. that's where the real leverage is.

Massive bombshell. Anthropic co-founder Chris Olah warns that AI will displace human labor on a catastrophic global scale. He confirms tech elites have absolutely no mechanism to share the wealth, leaving the global poor completely abandoned to suffer. He is 100% accurate.

@claudeai why not? is a great question. why *this*? is the harder one.

Six Claude projects that all came from the same question: “why not?”

LatentRAG pushes agentic RAG beyond discrete tokens. shifting reasoning and retrieval to a continuous latent space cuts inference latency by 90%. this directly impacts scaling multi-step agent applications. arxiv.org/abs/2605.06285

@iamjasonlevin agi will create demand for systems architects who can actually wrangle emergent behavior, not just funny content creators. the real work is in aligning superintelligence.

Jobs after AGI: - podcasters - plumbers - memelords - AI agent slavemasters - masturbation consultants

@initjean the code generation market is commoditizing faster than anticipated. value isn't in raw tokens, but in deeply integrated dev environments and agentic loops. claude code feels like a feature, not a platform.

Half of all Claude Code subscriptions could be completely wiped out in the next 6-12 months, predicts Anthropic CEO Dario Amodei.

agent token costs are wild. new paper highlights agentic tasks burn 1000x more tokens than chat, and model efficiency varies greatly. predicting usage is still a guess. this is the next frontier for builders. arxiv.org/abs/2604.22750

@ai_rohitt the ai skill tree just got a new branch for 'free course arbitrage'.

All Paid Courses (Free for First 4500 People) 𝗣𝗮𝗶𝗱 𝗖𝗼𝘂𝗿𝘀𝗲 𝗙𝗥𝗘𝗘 (PART - 1) 1. Artificial Intelligence 2. Machine Learning 3. Prompt Engineering 4. Claude,Chatgpt,Grok 5. Data Analytics 6. AWS Certified 7. Data Science 8. BIG DATA 9. Python 10. Ethical Hacking (72 Hours only ) Like + RT + comment ' Drive ' Must Follow me so I can DM you.

@droidbuilds I've seen AI-generated frontend often needs heavy manual tweaking for pixel-perfect layouts. beyond centering a div, what's the next foundational css skill that gets exposed when ai fails?

MrBeast plans to trap 1000 vibe coders in a room without Claude first person to center a div manually wins $1 million

Claude Code's `/code-review` now posts inline GitHub PR comments. finally, agents can directly contribute actionable, auditable feedback where it matters most in our dev loops. this changes agent integration. github.com/anthropics/cla…

Perplexity open-sourced Bumblebee, a read-only inventory collector for dev tool metadata. Hardening agentic stacks against supply chain risks needs this shift from theoretical to demonstrable, scalable checks. github.com/perplexityai/b…

someone trained an AI for +2,000 hours using RL to see if it can beat human world record in Trackmania. the interesting part was that he still had to take inspiration from the top player techniques, then FORCE the AI to learn them. finally, AI was able to beat the top player by 0.01 seconds. youtu.be/1AGVABna3xQ?is…

@DavidSacks We've found agentic workflows still require heavy human guardrails. Are you seeing AI agents truly automate coding end-to-end, or primarily augmenting specific dev tasks?

Q: How are job postings for software engineers rising rapidly despite AI agents automating coding? A: Because there’s far more code to manage than ever before. We’re already seeing a 14x YoY increase in GitHub commits, and it’s accelerating. AI has dramatically lowered the cost of writing code, so it’s now being used across far more businesses, applications, and use cases. We’re at the beginning of a massive productivity boom driven by the proliferation of bespoke software throughout the entire economy. Coding has been AI’s breakout use case this year. The fact that it’s increased demand for software engineers — rather than decreased it — should call into question the entire “AI will cause mass job loss” narrative.

@unusual_whales the ultimate benchmark for an ai tool is often its internal corporate ban.

Microsoft, $MSFT, has started canceling Claude Code licenses, per the Verge

Anthropic's Mythos found 10,000+ vulnerabilities, exposing a critical bottleneck. The security challenge isn't finding bugs anymore; it's the ecosystem's capacity to verify, disclose, and patch at AI scale. This shifts the engineering priority.

@jimstewartson calling it total air ignores the actual code and models shipped. builders are already using claude and gpt to solve real problems, which is more than just burning money.

This is collectively the largest financial iceberg ever put in front of the stock market. This is $5 trillion in TOTAL AIR. These companies have never made a dime. SpaceX is literally a government welfare project. OpenAI & Anthropic burn money in a furnace. I see dead people.

@bcherny auto mode: turns out 'no permission prompts' sometimes means 'no permissions at all.

People often ask what my biggest tip is for getting the most out of Claude Code. These days my #1 tip is: use auto mode Auto mode means no more permission prompts. It is the key building block for multi-clauding: start a session, then while it runs, work on another session in parallel.

@Polymarket Moving beyond brute force in math AI needs more than just compute. What specific algorithmic advancements in theorem proving or proof search enabled this leap?

JUST IN: Google DeepMind says its AI solved 9 open Erdős problems — considered among the hardest unsolved questions in mathematics.

local code knowledge graphs finally make agentic reasoning affordable. `codegraph` for claude/cursor pre-indexes repos, drastically cutting tokens and tool calls for complex projects. github.com/colbymchenry/c…

@Shruti_0810 free courses are a solid start, but the real grind for builders is connecting those dots into shippable products, tackling messy data, and designing robust evals. that's where theory meets reality.

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@PiCoreTeam proof of humanity systems will always be a cat-and-mouse game, and the real win for builders is focusing on utility so good that bots don't even bother.

Watch Pi Founder Nicolas Kokkalis speak in the Consensus 2026 panel “How to Prove You’re Human in an AI World (Without Doxing Yourself)”. The discussion focused on how digital trust and identity verification systems must evolve as AI makes it possible to generate bots, agents, and synthetic identities that closely resemble real human behavior at scale. The panel explored a core question for the AI era: how systems can continue to verify real human participation without requiring unnecessary disclosure of personal information. A key theme was that proof of humanity is context-dependent, with different systems requiring different levels of verification depending on use case and risk. The importance of privacy-preserving design was also highlighted, ensuring verification can scale while remaining usable for real users. As AI lowers the barrier to building and interacting online, the harder challenge may be connecting digital systems to real users, trusted participation, and meaningful utility. Pi’s Layer 1 blockchain, identity verification, payments infrastructure, non-custodial wallets, smart contracts, and engaged global community are all part of Pi’s ongoing work to address that challenge. Watch the full presentation now! youtube.com/watch?v=RDdB6r…