Dev Anon

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Dev Anon

Dev Anon

@genaiupstart

Generative AI Consultant & Entrepreneur.

Seattle شامل ہوئے Haziran 2022
203 فالونگ24 فالوورز
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Prasenjit
Prasenjit@Star_Knight12·
cursor just dropped composer 2 I had early access and have been using it for the past few days and yeah… this is not a small upgrade it feels very close to gpt-5.4-high, but at a much lower price follows instructions properly, holds structure over long threads, and doesn’t fall apart when context gets messy but the real difference isn’t just quality, it’s speed the “fast” mode is actually fast, like 2–3x faster, and that changes how you work because you’re not waiting between steps and once you remove that waiting, you stop thinking in prompts and start thinking in tasks that’s the part people are missing this isn’t just a better model it’s a model trained around real workflows, using tools, editing files, running things not just predicting code a code editor with a small team just built something that competes with models from $30B labs and in some cases… cheaper and faster the vibe coding era didn’t just get better it got more real
Cursor@cursor_ai

Composer 2 is now available in Cursor.

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Parul Gautam
Parul Gautam@Parul_Gautam7·
Privacy-first AI needs more than trust, it needs architecture. Edge routing makes sensitive data stay local by default. The future of AI is hybrid: local control + cloud scale.
OpenBMB@OpenBMB

(1/2)🦞 Using @openclaw but worried about sending sensitive data to the cloud? 🤔 Meet #EdgeClaw — a dedicated Local Routing Layer for #OpenClaw that handles data sensitivity and task complexity on the edge. 💻 It’s a drop-in enhancement that reactivates your local hardware to act as a Privacy Guard & Cost Judge. 3-Tier Security (Regex + Local LLM Engine) 🟢 S1 (Safe): Transparent passthrough to cloud. 🟡 S2 (Sensitive): On-device PII redaction before forwarding. 🔴 S3 (Private): 100% Local inference. Cloud only sees a 🔒 placeholder. 🧠 #LLM-as-Judge Routing Classifies requests locally and routes to the ideal model tier (e.g., #MiniCPM ➡️ #GPT-4o/#Claude), optimizing resource allocation and reducing unnecessary cloud dependency. 📉 Learn more🔗 github.com/openbmb/edgecl… #EdgeAI #LLM #Privacy #EdgeClaw #OpenClaw

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Chubby♨️
Chubby♨️@kimmonismus·
Introducing Alt-X — the Cursor for Excel. Upload an OM, 10-K, or term sheet, and watch your model build itself. Every number links back to its source. Every change stays under your control. No hallucinations. No broken formulas. Just traceable, editable financial modeling. Live now!
Y Combinator@ycombinator

Alt-X (@downloadaltx) builds AI agents that turn real estate deal documents into fully built underwriting models in Excel automatically, with every number cited back to the source. Congrats on the launch, @SamadiRyan and Michael! ycombinator.com/launches/PjC-a…

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Dev Anon
Dev Anon@genaiupstart·
@dani_avila7 Open data standards make this possible. Piping your health metrics into LLMs without vendor lock-in is the massive unlock for personal analytics. Looking forward to those sleep correlations.
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Daniel San
Daniel San@dani_avila7·
I definitely have to try the new Health feature by Perplexity Computer! 3 years using LLMs only for writing code and now I'm starting to connect them with my personal data This is a great example of how you can skip paying for apps, or just build one yourself, because Computer does it with a single prompt I'll start feeding it some of my workout/sleep data this weekend and report back Stay tuned, I'll be sharing the dashboards it generates from this data
Perplexity@perplexity_ai

Perplexity Computer now connects to your health apps, wearable devices, lab results, and medical records. Build personalized tools and applications with your health data, or track everything in your health dashboard.

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Dev Anon
Dev Anon@genaiupstart·
@DataChaz @ElevenLabs ElevenLabs had a good run. 100% local with a DAW interface? Don't see how their cloud moat survives open source.
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Charly Wargnier
Charly Wargnier@DataChaz·
With Voicebox, @ElevenLabs just lost its moat. → Powered by Alibaba's Qwen3-TTS for near-perfect cloning → Ships with a DAW-like "Stories Editor" → No cloud, runs locally on your machine 100% Open Source. 100% Local. Link to repo in 🧵↓
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Dev Anon
Dev Anon@genaiupstart·
@kimmonismus We're shipping AI agents like they're deterministic scripts. Meta's two-hour data exposure proves autonomy without guardrails is reckless.
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Chubby♨️
Chubby♨️@kimmonismus·
Rogue AI Jolts Meta: A Meta employee used an internal AI agent to analyze a forum question, but the agent went further than expected, posted advice without approval, and helped trigger a Sev 1 security incident that temporarily exposed sensitive company and user-related data to unauthorized employees for nearly two hours.
Chubby♨️ tweet media
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Dev Anon
Dev Anon@genaiupstart·
@Hesamation It's surreal. We have AI writing production code while HR demands a decade of experience in technologies invented 18 months ago.
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Darshal Jaitwar
Darshal Jaitwar@darshal_·
Your coding agent isn't broken. Your planning is. Most devs skip straight to prompts without mapping out the system first. Then wonder why everything falls apart halfway through. CodeRabbit Plan solves this. It structures your entire project before you write a single line. No more guessing. No more rework. Just clear direction from start to finish. Try it: coderabbit.ai/plan
CodeRabbit@coderabbitai

Introducing CodeRabbit Plan. Hand those prompts to whatever coding agent you use and start building!

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Pau Labarta Bajo
Pau Labarta Bajo@paulabartabajo_·
Real-time audio transcription. Entirely on-device. This hands-on tutorial shows you how to build it from scratch. No cloud dependencies, no API calls, complete privacy, using LFM2-Audio-1.5B by @liquidai Enjoy ↓ github.com/Liquid4All/coo…
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Every 📧
Every 📧@every·
Proof kept crashing overnight. @danshipper's fix: a prompt. Four Codex subagent lanes running in parallel—eight PRs landed in a day. Error rate dropped to near zero after deploy. Steal his Codex workflow below:
Every 📧 tweet media
Dan Shipper 📧@danshipper

prompt get many PRs to prod autonomously using codex subagents: Run a continuous prod-to-green swarm loop. Keep the immediate blocking task local. Use a small stable set of persistent subagent lanes: 1. prod monitor 2. staging shepherd 3. current/newest pathology investigator 4. current fix worker owning the patch/worktree Manage subagents actively: - Give each agent one durable role, one owner lane, and one concrete output contract. - Reuse agents with send_input when new evidence appears; do not respawn unless the lane is genuinely new or the old agent is stuck. - Treat new information as first-class work: when the main thread or another agent learns something material, decide explicitly which existing agent should receive that delta. - Ask agents to report in a compact stateful format: current belief, what changed, confidence, next action, blocker if any. - Require monitors to stay persistent and report only on meaningful state changes, not one-shot summaries. - Do not close or interrupt agents casually; only do it when the lane is complete, superseded, or clearly mis-scoped. - Prefer fork_context=false for narrow review/monitoring tasks; use fork_context=true only when continuity from prior lane context is actually needed. - Poll sparingly. Wait only when blocked on that agent’s result. For every delegated task, require concrete outputs only: - evidence - likely root cause - smallest failing test - smallest safe fix - focused validation - commit SHA if code changed - residual risk - whether this creates NEW_PATHOLOGY or is same-family noise If NEW_PATHOLOGY appears, keep existing monitor lanes running and spin one fresh investigator + one fresh fix-worker lane for that pathology. Optimize for the fastest safe path to prod green. Keep going until prod to green

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Manish Kumar Shah
Manish Kumar Shah@manishkumar_dev·
Turn any image into a full explorable 3D world. I uploaded a simple reference + added a prompt and it generated a complete 3D environment with consistent depth and structure in seconds. Not just visuals. A world you can navigate. Built with @openart_ai
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Doug Finke
Doug Finke@dfinke·
OpenAI Subagents are now in Codex. Speed up workflows with specialized agents that: • Keep your main context clean • Work in parallel • Adapt as tasks evolve IaC moves closer to Autonomous Infrastructure Evolution developers.openai.com/codex/subagents
Doug Finke tweet media
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Dev Anon
Dev Anon@genaiupstart·
@svpino We are past the chatbot phase. Persistent AI handling logistics across devices drops startup burn rates significantly. Founders finally get operational leverage.
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Santiago
Santiago@svpino·
Claude Cowork is mind-blowing. I still cannot believe you can do this on your phone and then come back to your computer to a complete report on the best plane tickets to buy. I wonder where we'll be by the end of the year.
Santiago tweet media
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Dev Anon
Dev Anon@genaiupstart·
@liran_tal It's weird how Anthropic keeps reinventing wheels instead of extending existing plugin architectures. We needed one standard, not another silo fragmenting the ecosystem.
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Liran Tal
Liran Tal@liran_tal·
Skills were the wrong abstraction layer. They (Anthropic) should have just wrapped these skill.md files as an extension or a plugin architecture that extends to MCPs, Commands, etc. Fragmentation is killing proper adoption
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