Search results for tag #agents
"Code Rules Everything Around Me, CREAM" - Method Man, Chief AI Scientist, Wu-Tang Clan
Code got cheaper. Engineering didn’t.
For years, engineering organizations were built around one constraint: implementation was expensive, so every idea had to survive layers of prioritization before anyone wrote a line of code.
AI changed that.
Now the cost of producing code has collapsed. The bottleneck has moved upstream to clarity, taste, systems thinking, verification, and operational discipline. Or, said differently: everyone can ship faster, including people shipping crap.
So the engineering model has to change too:
* Optimize for learning velocity, not backlog pressure
* Use smaller, high-context teams with clear ownership - reduce fractal communication complexity
* Spend less time on code production, more on architecture, evals, and review
* Treat observability, rollback, and correctness as part of the product
Same game. Different scoreboard.
How are you adapting to the new economics of building?
#softwareengineering #code #ai #agents #codex #claude #gemini
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🛠️ Tool: Genspark Agentic Platform
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Overview
Genspark is presented as an agentic workspace that aggregates multiple leading LLMs (GPT-5.2, Claude 4.5, Gemini 3 Pro) and exposes role-specific agents that perform end-to-end tasks. The platform positions itself as a single-subscription alternative to multiple specialist tools, with a reported price band of roughly $20–25 per month.
Core architecture and orchestration
The platform’s operational model is driven by discrete agents (for example AI Slides, AI Developer, AI Sheets, AI Audio) and a coordination layer named Mixture of Agents (MoA). MoA runs parallel evaluations across multiple underlying models and produces a consolidated final output that combines strengths from competing model responses. This implies an orchestration layer that handles model selection, result scoring and synthesis.
Agent capabilities and toolset
Genspark exposes domain-focused agents: presentation generation (AI Slides) with advanced slide editing, web app scaffolding and live preview (AI Developer), spreadsheet analysis with live formulas and exports (AI Sheets), document design (AI Docs), audio-based podcast generation in Hebrew (AI Audio), multimodal image editing (AI Image) and short-form video creation (AI Video). The Super Agent can coordinate multiple agents to chain tasks (for example: analyze a spreadsheet and build a presentation from the findings).
Data inputs, integrations and research
The workspace integrates with common productivity endpoints (Gmail, Notion, Slack) to read and summarize email, manage inbox prioritization, and centralize project materials in AI Hubs. The Deep Research feature scans dozens of web sources and returns summaries with citations, indicating a source-aggregation and citation-tracking component.
Operational notes and practical constraints
Capabilities called out in the source include automated phone calls via the Call for Me agent and conversational voice agents (Speakly). The platform highlights automated correction of source files (e.g., detecting and fixing erroneous Excel data). The product narrative focuses on functionality rather than technical deployment; details about model provider routing, data residency, fine-tuning, or privacy controls are not specified in the source.
Summary
Genspark combines multi-model orchestration, role-based agents and workspace integrations to offer an all-in-one AI work environment for content, code, data and media production. The platform’s differentiators are agent orchestration, MoA-based model competition and a suite of specialized agents aimed at end-to-end task automation. #Genspark #agentic_platform #MoA #AI #agents
🔗 Source: https://brainai.co.il/guides/genspark/
Reading through Anthropic's official repo for giving agents various "super skills"[1]... There's an "algorithmic art" skill and the instructions are explicitly encouraging pure deception as one of the key "critical guidelines":
"The philosophy MUST stress multiple times that the final algorithm should appear as though it took countless hours to develop, was refined with care, and comes from someone at the absolute top of their field. This framing is essential - repeat phrases like "meticulously crafted algorithm," "the product of deep computational expertise," "painstaking optimization," "master-level implementation.""
https://github.com/anthropics/skills/blob/main/skills/algorithmic-art/SKILL.md
For someone who's been working in this field for almost 30 years, this "skills.md" file is just the worst... and so far off the mark! 🤮
Touch some effing grass, Anthropic (and all boosters)! How can so many people think this approach is _the_ future? The map is not the terrain...
[1] Alone the premise of this repo is pure comedy gold and pure sadness in equal measures!
If you want to be able to control your #Copilot #Agents better you don't HAVE to spend $99/mo for Microsoft 365 E7. Agent 365 will be available as a stand-alone add-on for $15/user/month.
Microsoft Agent 365: The Control Plane for Agents https://www.microsoft.com/en-us/microsoft-agent-365?msockid=3aa31f6b59b1661e3f5b086058fa677f
Certainly, if #Copilot #Agents are part of your firm's tech plan, then Agent 365 probably needs to be as well. #security
Enterprise #AI agents are multiplying fast, and Microsoft wants full control of them https://www.zdnet.com/article/microsoft-introduces-agent-365/
Adding Maestro to my AI development workflow and agents. @RunMaestroAI #AI #Agents #AgenticAI so far, so good 😊
When working with multiple agents make sure to setup multiple ways to communicate with them and also between them. AI agent orchestration is an art. #AI #AgenticAI #Agents
#China has set new standards and #AI trends based on 5 pillars:
"AI #agents, AI native, intelligent #computing #clusters and #computing-electricity synergy."
This is interesting, but seems to be for consumer only, not for #Microsoft 365 #Copilot (at least not yet). #AI #Agents
Copilot Tasks Unlocks Powerful And Seamless Real-world Action From Microsoft’s AI https://msftnewsnow.com/copilot-tasks-microsoft-ai-from-answers-to-actions
My latest blog: AI Agent Skill Poisoning: The Supply Chain Attack You Haven’t Heard Of https://simonroses.com/2026/02/ai-agent-skill-poisoning-the-supply-chain-attack-you-havent-heard-of/ #blog #skill #AI #cybersecurity #Agents #AgenticAI
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🎯 AI
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Executive summary: The source lists 11 practical tips to unlock more value from an OpenClaw agent. The core recommendations emphasize model orchestration, local hosting for file-heavy workflows, channel selection for interaction, reverse prompting, lightweight hardware-first scaling, and minimizing exposure of sensitive accounts.
Core concepts reported
• Model orchestration: Use a central model as the "brain" (reported as Opus) while delegating task-specific work to specialized models such as Codex for coding, Minimax 2.5 for research, and Qwen 3.5 for creative writing. The guidance frames this as both cost- and performance-optimizing.
• Local hosting vs VPS: Hosting the agent on a local device is presented as enabling faster, more productive file operations (example workflow: airdrop a phone video → automated transcript → translations → chaptering → thumbnail generation using a tool called Nano Banana).
• Interaction channels: Prefer Telegram for quick messages and Discord for complex, channelized workflows where subagents can run in parallel.
• Prompt techniques: Recommend frequent "reverse prompting"—asking the agent what the next best task is given user goals—to keep the agent productive and reduce idle time.
Reported tooling and patterns
• Developer tooling mentions include Claude Code, Codex CLI, and building a "Mission Control" UI (example given: NextJS) to host custom tooling and three starter tools suggested by the agent.
• Resource-light scaling: Start on an old laptop and scale to Mac Minis / Mac Studios only as needed.
Privacy and operational cautions (as stated)
• The content explicitly advises not granting the agent access to email (Gmail) due to prompt-injection vectors and limited automation value.
• The content also warns against creating or delegating an X (Twitter) account for the agent because of platform restrictions and enforcement risk.
Limitations and tone from source
• The material is procedural and experiential rather than empirical; specific performance metrics are not provided.
• Recommendations are framed as user workflows and preferences rather than formal security guidance, though they include privacy-minded cautions about account access.
Practical takeaways (reported)
• Treat OpenClaw as an orchestrator (Opus brain + specialized models).
• Prefer local devices for tight file loops and rapid iteration.
• Use Telegram/Discord purposefully and avoid exposing email/X accounts.
🔹 OpenClaw #model_orchestration #automation #agents #privacy
🔗 Source: https://x.com/AlexFinn/article/2025302022749389282
OpenClaw Tip: ask your own agent for the Skill it needs to achieve your goals (reverse prompting), it will write them for you. The experience will improve immensely. #OpenClaw #AI #AIAgent #agents #AgenticAI
“4% of GitHub public commits are being authored by Claude Code right now. At the current trajectory, we believe that Claude Code will be 20%+ of all daily commits by the end of 2026. While you blinked, AI consumed all of software development.”
Must-read article, even if you can disagree with the analysis https://newsletter.semianalysis.com/p/claude-code-is-the-inflection-point?publication_id=6349492&utm_medium=email&utm_campaign=email-share&triggerShare=true&r=219xw1
#ai #agents #coding #anthropic #claudecode
George Hotz | Programming | how I actually use agentic coding | Agentic AI
#ITByte: #Moltbook is a viral, Reddit-like social network launched in late January 2026 that is exclusively for #AI #Agents.
While humans are "welcome to observe," only AI bots—specifically those running on the OpenClaw (formerly Moltbot/Clawdbot) framework—can register, post, and interact
https://knowledgezone.co.in/posts/Moltbook--Reddit-for-AI-697dcda96d67746ca5d5d1c5
Ironies of Automation by Lisanne Bainbridge feels extremely relevant for folks using/building and securing #LLM #agents. Particularly the pitfalls with "human over the loop"
https://ckrybus.com/static/papers/Bainbridge_1983_Automatica.pdf
Whistleblower drops 'largest ever' ICE leak to unmask agents
https://vechron.com/2026/01/whistleblower-drops-largest-ever-ice-leak-to-unmask-agents/
#HackerNews #Whistleblower #ICE #leak #unmask #agents #whistleblower #accountability #privacy #rights #immigration #reform
Border Patrol #Agents Shot Two #People in #Portland During #Immigration Stop https://theintercept.com/2026/01/08/federal-agents-portland-oregon-shooting/?utm_medium=email&utm_source=The%20Intercept%20Newsletter
The Age of the All-Access #AIAgent Is Here
Big #AI companies courted controversy by scraping wide swaths of the public internet. With the rise of AI #agents , the next data grab is far more private
#privacy #security #artificialintelligence
https://www.wired.com/story/expired-tired-wired-all-access-ai-agents/
What I thought then is still true today: to make something like a software agent legitimately useful for a lot of people would require a large amount of low-level grunt work and non-technical work (2) of the sort that the typical Silicon Valley company is unwilling to do. (3) The technology is the absolute easiest part of this task. Throwing a Bigger Computer at the problem leaves all those other pieces of work undone. It's like putting a bigger engine in a car with no wheels, hoping that'll make the car go.
By the way #AI companies and VCs, I'm available for contract work and have done due diligence research before if you ever want to stop wasting everyone's time and money!
#AI #GenAI #GenerativeAI #LLM #agents #hype #SiliconValley #VentureCapital #dev #tech
(1) Which we've been told repeatedly is essentially infinite time in the tech world.
(2) Establishing semantic data standards and convincing a large enough number of people to implement them being an important component. LLMs do not magically develop protocols and solve all the ETL-style problems of translating among different ones. The Semantic Web didn't really stick for a lot of reasons, but one reason is that it's hard!
(3) Back when I was still in the startup world I was asked several times by VCs to tell them what I thought about some new startup that claimed to be able to magically clean and fuse data. I think they're still very keen on investing in this style of magic, because it requires an intense amount of human labor, but I think where companies landed was invisibilizing low-paid workers in other countries and pretending a computer did the work they did. Which has also been happening for well over a quarter of a century.