i went through every uncensored and abliterated models on hugging face and picked the best ones for each vram tier from 8 to 24gb. welcome to the danger zone ⚠️ ━━━━━━━━━━━━━━━━━━━━ 8gb · rtx 3060 ti, 3070, 4060, 5060, 4060 ti 8gb, 5060 ti 8gb · amd rx 6600, 6650 xt, 7600, 9060 xt 8gb · the base runs 42.8 tok/s on a 3060 ti 8gb out to a 96k window > 1. bonsai 2 27b heretic, 1-bit, 5.95gb, refusals 95 to 0 out of 100, 147k downloads this month huggingface.co/OS-Software/T… > 2. bonsai 2 27b abliterated, refusals 83% to 0%, mmlu holds at 78%, 77k downloads huggingface.co/BoldingBuilds… > 3. bonsai 2 27b crack, harmbench refusals 93% to 0% → huggingface.co/dealignai/Bon… older 8gb cards · gtx 1070, 1080 · the base runs 42 tok/s on a 2016 gtx 1080 > 1. gemma 4 e4b aggressive, 5.3gb, 0 refusals out of 465, 1.43m downloads this month huggingface.co/HauhauCS/Gemm… > 2. gemma 4 e4b heretic, refusals 99 to 3 out of 100 huggingface.co/llmfan46/gemm… ━━━━━━━━━━━━━━━━━━━━ 12gb · rtx 3060 12gb, 3080 12gb, 4070, 4070 super, 4070 ti, 5070 · amd rx 6700 xt, 6750 xt, 7700 xt · base bonsai 2 runs 50.1 tok/s on a 3060 12gb with my kernel and the speed head > 1. bonsai 2 27b abliterated v2 with the mtp speed head, 7.7gb, refusals 84% to 0% huggingface.co/BoldingBuilds… > 2. qwen 3.8 27b abliterated squeezed to 10gb with gsq-rco, 2.12m downloads this month huggingface.co/huihui-ai/Hui… > 3. qwen 3.8 27b heretic gsq-rco, 9.3 to 10.1gb, refusals 0 to 1 out of 100 huggingface.co/0bserverx/Qwe… > 4. gemma 4 12b heretic, 7.4gb, 120k downloads huggingface.co/culturerevolt… ━━━━━━━━━━━━━━━━━━━━ 16gb · rtx 4060 ti 16gb, 5060 ti 16gb, 4070 ti super, 4080, 5070 ti, 5080 · amd rx 6800, 6900 xt, 7600 xt, 7800 xt, 9060 xt 16gb, 9070 xt · base bonsai 2 runs 67.3 tok/s on a 5060 ti 16gb with everything on > 1. qwen 3.8 27b heretic ara, built for 16gb, 14gb huggingface.co/Bucoid/Qwen3.… > 2. qwen 3.8 27b aggressive with the mtp head, 12.8 to 15.7gb, 0 refusals out of 465, 2.06m downloads this month huggingface.co/HauhauCS/Qwen… > 3. bonsai 2 27b heretic with the full 262k window, the speed head and vision all on huggingface.co/OS-Software/T… > 4. gemma 4 26b a4b abliterated, moe with 4b active per token, 13.4gb huggingface.co/groxaxo/Huihu… ━━━━━━━━━━━━━━━━━━━━ 24gb, the danger zone · rtx 3090, 3090 ti, 4090 · amd rx 7900 xtx, and the 20gb 7900 xt fits these too · base qwen 3.8 27b q4 runs 41.3 tok/s on my 3090 with the mtp head, owners report 61 on a 3090 ti and 76 on a 4090 > 1. qwen 3.8 27b uncensored, q4 16.8gb, 2.31m downloads this month huggingface.co/JonathanColet… > 2. qwen 3.8 27b abliterated, q4 16.8gb, 2.12m downloads huggingface.co/huihui-ai/Hui… > 3. qwen 3.8 27b aggressive with the mtp head, 0 refusals out of 465, 2.06m downloads huggingface.co/HauhauCS/Qwen… > 4. qwen 3.8 27b heretic, refusals 0 to 1 out of 100 huggingface.co/0bserverx/Qwe… > 5. qwen 3.8 27b fable cold fusion, the uncensored coder merge, 2.09m downloads huggingface.co/DavidAU/Qwen3… > 6. qwen 3.6 35b a3b aggressive, moe with 3b active, 11.9m downloads all time and the most liked on this list huggingface.co/HauhauCS/Qwen… ━━━━━━━━━━━━━━━━━━━━ refusal numbers are each releaser's own test, so read them per model, and the speeds are the base models on nvidia cards, these builds keep the same size so they run the same. amd cards run the same files on llama.cpp's vulkan or rocm backends, the bonsai builds run on prismml's llama.cpp no refusals means no guardrails, you own what you ask. bookmark this, find your card and pull one tonight

Un score qui ferme un compte ou écarte une candidature sans examen humain effectif peut relever de l’art. 22 RGPD, même sans IA. Un recours ajouté après coup ne change pas son caractère automatisé. donneespersonnelles.fr/decis… #RGPD

If you learn GTM Engineering, you will never be unemployed again. Stage 1: GTM Data Architecture and Reverse ETL - Learn: Snowflake/BigQuery, Hightouch/Census, identity resolution, API webhooks. - Practice: Build a pipeline that syncs raw Stripe billing data and product usage directly into HubSpot/Salesforce custom objects. - Why: GTM without a single, code-level source of truth is just guessing. Stage 2: Signal and Intent Pipelines - Learn: Website deanonymization (Clearbit), intent data (Bombora), event streaming. - Practice: Build a webhook router that instantly alerts a Slack channel when a target enterprise account visits your pricing page 3 times in one week. - Why: In B2B, timing beats the pitch. You must strike while the intent is hot. Stage 3: AI SDRs and Hyper-Personalization - Learn: Clay, Apollo APIs, LLM data enrichment, web scraping. - Practice: Build an AI agent that scrapes a prospect's recent GitHub commits or podcasts and writes a highly specific, 1:1 cold email. - Why: Generic outbound is dead. AI makes infinite personalization mathematically possible. Stage 4: Product-Led Growth (PLG) Telemetry - Learn: PQL (Product Qualified Lead) scoring, event tracking (Segment/Rudderstack), feature adoption curves. - Practice: Write a script that triggers a high-priority sales alert the second a free-tier user hits a specific "aha moment" API threshold. - Why: The product is your best salesperson. Hand-raisers convert 5x higher than cold outbound. Stage 5: Usage-Based Pricing (UBP) and Monetization - Learn: Stripe Metered Billing, credit systems, value-metric alignment, API metering. - Practice: Design and implement a pricing architecture that charges by "agent executions" or "tokens processed" instead of flat "per-seat" licenses. - Why: SaaS pricing has permanently shifted from charging for access to charging for outcomes. Stage 6: Revenue Operations (RevOps) and Attribution - Learn: Multi-touch attribution, funnel leakage analysis, SQL, cohort analysis. - Practice: Build a dashboard proving exactly which combination of LinkedIn ads, webinars and cold emails sourced your closed-won enterprise deals. - Why: If you cannot mathematically prove ROI, the CMO will cut your budget. Stage 7: AI Sales Enablement and Coaching - Learn: Gong/Chorus APIs, transcript summarization, vector search on sales calls. - Practice: Build a tool that analyzes 100 lost sales calls and auto-generates an updated "objection handling" battle card for the sales team. - Why: Reps forget 70% of their training. AI reinforcement loops fix the leaky bucket. Stage 8: Predictive Churn and Expansion (NRR) - Learn: Health scoring algorithms, Net Revenue Retention (NRR) math, usage drop-off alerts. - Practice: Build a "churn risk" model that flags accounts with dropping API usage 45 days before their renewal date. - Why: In the AI era, switching costs are low. Retention and expansion are the only real growth. Stage 9: Integration-Led Growth (Ecosystem GTM) - Learn: App marketplaces, OAuth flows, Zapier/Make templates, co-selling motions. - Practice: Build a native integration for a major platform (like Slack or Salesforce) and optimize its marketplace listing to drive inbound leads. - Why: Buyers trust their existing stack more than your cold email. Ecosystems are the ultimate distribution. Stage 10: Dark Social and Community Attribution - Learn: Untrackable attribution, Discord/Slack community ops, developer advocacy metrics. - Practice: Launch a niche technical community and build a survey-based model tracking how "word of mouth" correlates to enterprise pipeline. - Why: B2B buyers buy from peers in private Slack groups not from vendor whitepapers. Stage 11: The Automated QBR (Quarterly Business Review) - Learn: Data visualization, automated reporting, ROI calculation frameworks. - Practice: Build a script that pulls customer usage data and auto-generates a custom, branded ROI slide deck for the Customer Success team. - Why: CSMs should be strategic advisors not manual data gatherers. Stage 12: Public GTM Teardowns and Portfolio - Learn: Pricing psychology, funnel teardowns, public writing, benchmark analysis. - Practice: Publish 3 deep-dives on how top AI companies structure their pricing pages, onboarding flows, and credit systems. - Why: GTM leaders and Revenue Architects are hired for their strategic judgment, not just their SQL skills. Code builds the engine. GTM builds the fuel. The modern GTM Engineer builds the nervous system for global revenue and autonomous sales agents. Bookmark and Repost!

quincunx33/ai-jailbreak: A collection of jailbreak prompts and exploit techniques for local and frontier AI models, with modern methods for Qwen3.5, Gemma 4, Llama 4, Kimi K3, GPT-OSS, GPT-5.x, Gemini 3.x and Grok 4.x. For red-... github.com/Quincunx33/Ai-jai…

How to turn LinkedIn and X into your main GTM channel in the next 6 months: (visualized)

On our quest to take down Semrush, we’re open sourcing AI Visibility. Getting mentioned by AI shouldn’t require another subscription. All of OpenSEO’s features for SEO/GEO are available for $10/month. I linked a demo video in the comments. Hope you try it out!

founders & marketers: your competition are all DISTRACTED. focus on these big levers and you will crush them (in 90 days): 1. create the following pages for your 5 biggest competitors: > [Competitor] Alternatives > [Competitor] vs [Competitor] > [Competitor] Review 2. create Best [product] for X pages for all "Best" keywords with search volume make sure this content includes: > key takeaways > comparison tables > methodology section > real user feedback from forums like reddit > list "best for" and "trade off" for each option > screenshots of the products/companies in your list 3. re-write these pages as LinkedIn pulse articles these are some of the easiest pages to rank in AI Search publish these on your company page promote them on your personal page (ask your team to do the same) 4. make Services/Product pages for all your offers house them in /services or /product folders then add schema for AI bots and crawlers 5. create an About Us with the following H2 sections: > About [Company] > What [Company] does > What Makes [Company] Different > Who Uses [Company] > The Team Behind [Company] > How [Company] Works > Key Facts > Frequently Asked Questions 6. find and organize your company's unique knowledge in a database start here: > sales calls > customer calls > SOPs > internal slack channels > support emails > interviewing key people at the company > first party data your company generates new, unique, useful knowledge every day but you're too close to it to see how valuable it is (I'll tell you what to do with this info in step 8) 7. collect all your social proof on one document example: we had Claude scrape our "client_wins" Slack channel, reporting decks, and, and client call transcripts we now have 11 full pages of wins to use as "social proof" in our content on LinkedIn, X, and YouTube 8. combine your unique knowledge + social proof to write hooks make sure they all include these 3 ingredients: 1. Promised benefit/result 2. Curiosity gap 3. Social proof spend one full day on this your goal is to end the day with ~60 hooks for LinkedIn and X 9. turn your best hooks into long form explainers you can do this easily by creating shorter, step-by-step versions of your SOPs this is your conversion content 10. turn your other hooks into short, direct response posts the structure of these posts should be: 1. promised benefit 2. curiosity gap 3. social proof 4. lead magnet these will help build your email, SMS, and warm calling lists 11. create 5 core lead magnets you can plug in all your content do this by editing your internal SOPs to remove sensitive information then put those documents behind an email gated landing page if people find your content useful, they can download the full SOP for a more comprehensive playbook 12. create an automated email drip campaign now that you're collecting thousands of emails, you need to nurture them create a value-led email course that helps your ICP solve their problem sprinkle in some social proof and CTAs where they can buy your product or book a call with you 13. warm call 80 prospects per day if you don't have someone on your sales team who can do this, hire them give them this script: "hey [name] - I saw you downloaded our resource on XYZ. I wanted to see if you're stuck on anything, or if I can help give any additional support? I'd love to walk you through how to action this on a screen share, do you have 15 mins at [time/day] or [time/day]?" it'll be the best money you ever spend ----------- let your competitors chase shiny objects just focus on setting up this system so, you have 2 options: 1) follow these exact steps over the next 90 days 2) have a team of experts handle it A-Z for you (by booking a free strategy call with us below) contact.so/#call

if you learn marketing engineering, you will never be unemployed again. you need two things for all of it: claude code and a github account. marketers who know how to use them well and build their own agents will make real money for their companies. 11 steps:

Introducing OpenSource Clay killer - 85% cheaper than clay - Most accurate on people-search bench - 25x faster - Run GTM directly in claude code or codex Try it at treg.to/people-search Repo link below 👇

Rapport ANSSI sur les cyberattaques contre la DGFiP (29 sept.) : identifiants dérobés, applications sensibles sans cloisonnement suffisant, exfiltrations non détectées. À relire à l'aune de l'article 32 du RGPD. donneespersonnelles.fr/secur… #RGPD

Up to €2.5M. Zero equity. The EU's EIC Accelerator gives startups a grant of up to €2.5M and the grant takes 0% of your company. On top of that: - Optional €1M–€10M investment from the EIC Fund (this part is equity or a convertible loan) - Coaching, mentors and investor access included Who can apply: - Startups and SMEs in the EU or Horizon Europe associated countries - Solo founders who plan to set up a company can apply too - Founders from anywhere else must relocate their company before the full proposal (step 2) - UK founders can get the grant only not the investment - The grant is once per company (2021–2027) What they fund: - Any field of tech (deep tech like AI hardware, climate, biotech, robotics, semiconductors is the sweet spot) - Tech must already be validated, not just an idea (prototype to near-market) - Grant covers up to 24 months of work How it works: → Step 1: short proposal (12 pages + 10 slides + 3-min video) → Accepted anytime, reviewed on the first Tuesday of every month → Feedback in about 4–6 weeks → Step 2: full proposal → Step 3: interview with the EIC jury → Next review batch: Nov 3 It's competitive and takes real work but it's one of the biggest no-equity checks a startup can get. Apply link below 👇 eic.ec.europa.eu/eic-funding… Short proposals close every first Tuesday at 5 PM Brussels time (9:30 PM IST on Nov 3). Bookmark this + tag a founder who thinks free money doesn't exist.

It’s crazy how painfully obvious this seems to this corner of the internet whereas this is groundbreaking stuff for the remaining 95%+ of the business world

My biggest takeaways from @thsottiaux: 1. Most actions on the internet will soon be taken by agents, and Tibo doesn’t think most people have priced this in yet. When Notion launched its MCP server, it saw a flood of traffic, which strained its systems and forced it to rethink its economics. Every product team will soon have to decide whether to build for agents. You can hold off for a while, Tibo says, “but it is inevitable.” 2. The model picker is likely going away. One of Tibo’s biggest frustrations with the current state of AI is that users have to think about which model to use and what reasoning effort to apply. “I myself even get fatigued with the model picker,” he said, and he wants to get rid of all of it as quickly as possible. Dots ships with no model picker at all. You just talk to it. 3. Build as if models will be 10 times better in a year. Tibo thinks models will get cheaper and faster “at rates that are quite incredible,” and that all modalities will finally work together seamlessly. When he looks at what people are building, his reaction is often “you’re not quite getting it.” If you imagined “all of this being roughly 10 times better than it is today,” what would you build differently? His own forecast was too slow: he expected today’s capabilities a year or two from now. 4. Loops, graphs, and fine-tuned prompts are not the long-term solution for getting the most out of AI. There was a period when people got very excited about configuring agent loops and building intricate graph architectures. Tibo thinks that era is ending. 5. While Dots got most of the attention at DevDay, Tibo thinks the plugin ecosystem will be the sleeper hit. OpenAI launched with 16 partners for “Sign in with ChatGPT,” and popular third-party plugins will share in revenue when subscribers spend tokens with them. ChatGPT recommends plugins inside conversations based on retention and quality, which can put a good one in front of “a significant slice” of its 1.2 billion users. Tibo’s advice to developers trying to get discovered: “Build a good plugin.” 6. Tibo’s Dot warned him that production was down five minutes before the DevDay live demo. The agent figured out that DevDay was happening that day, that the demo was minutes away, that the demo probably depended on that production system, and that Tibo would want to know. It pinged him just as the launch was about to begin, and it even offered to fix the outage. His reply: “I don’t think you’re there yet, little Dot.” 7. Tibo’s agent teams grow and shrink with every model release. When he’s pushing the frontier, he builds larger and larger teams of agents. Then the next model lands, “a bigger agent can just do all of it and keep everything in memory and learn,” and he shrinks the team again. Expansion, then shrinking, then expansion. Don’t get attached to your setup. 8. Skill trending down in value: typing fast. Skill trending up: taste. Tibo says the people thriving now deeply understand the user, learn quickly, and “know what good looks like.” That’s part of why OpenAI is full of former founders, more than 120 of them, which makes it feel like “a mega startup.” 9. Tibo changed his mind about new grads. He hadn’t anticipated how fast younger people would embrace all this change and figure out how to harness it, and that shifted OpenAI’s hiring strategy. His example is Ahmed Ibrahim, hired as a new grad, who built much of the Codex harness and is now responsible for OpenAI’s compute fleet. What set Ahmed apart: he’s “incredibly kind,” “incredibly collaborative,” works on what matters without putting himself first, and is “a sponge,” using the latest tools to learn at speeds Tibo hadn’t seen before. 10. We’ll likely address the burnout associated with AI. There’s pressure to run 30 agents at once and ship more because you can. Tibo wants AI to “reduce the noise” and let you put your attention where you choose. Every time he fully disconnects for a week of holiday, he starts thinking in more creative ways, and he wants to bring that into the workday. Maybe you need fewer meetings, and you’d be more productive if you were better rested. The industry still has to figure that out, he says, but that’s the promise of AI: “it’s not just one more prompt per second.”

« Cette adresse n’est pas la mienne, n’envoyez rien. » Bloquer le compte ne suffit pas : le droit à la limitation (art. 18 RGPD) impose d’empêcher l’usage contesté, copies chez le prestataire comprises. donneespersonnelles.fr/droit… #RGPD

I've decided to finally release my vulnerability hunting methodology that I've been using for several months now, both in testing as well as live engagements with great success. I was inspired by (and huge congrats to) the @Blackfrost_AI team open-sourcing Cyber-Frost Harness, their reproducible security-agent runtime with procedural skills, an evidence ledger, and isolated Docker targets for red/blue/purple work. 🎉 If you like the Cyber Frost Harness, and want some out of the box vulnerabilty hunting and POC development kit to go along with it - check out my VulnHunter. It's already loadable: their harness reads standard SKILL.md skills. Point skill_dir at VulnHunter's (or run its installer), and the hunting, falsification, and PoC disciplines load immediately. Repo: github.com/nealbridges/VulnH… CREDITS: This is fork of @CapitalOne original repo. I simply took it a step further on POC development and model agnostic. I'm also actively developing in my forked repo as I make more changes to it and welcome the contributions from the community as well. I think I'm doing the whole "respect who you give credit to" drama, and I asked my model to double and triple check it. So i can blame the model if its wrong. Otherwise, dont put me on blast on X if i suck at credits. /s Looking forward to developing on this further with the community.

after years of solving for inbound and organic marketing, I’m finally learning outbound properly! and i think outbound makes you better at almost every part of building a company or even looking for a job. watched this really well-made & complete video by YC on it. notes ↓

I compiled Y Combinator's best cold email advice.

Un champ de formulaire se justifie par la décision qui en dépend (art. 5(1)(c) RGPD). Si personne ne sait laquelle, il sort du formulaire. La checklist de collecte, de la finalité à la purge : donneespersonnelles.fr/colle… #RGPD

This AGENTS.md fixes the 𝘁𝗵𝗿𝗲𝗲 𝗺𝗼𝘀𝘁 𝗮𝗻𝗻𝗼𝘆𝗶𝗻𝗴 𝗵𝗮𝗯𝗶𝘁𝘀 of Codex and Claude Code: writing backward-compatible code for a project nobody uses yet, never deleting old code and docs it no longer needs, and adding a pile of tests just to change a button color. After using them every day for months, the lines I'd want in there from day one are the ones at the top: if the project has no real users yet, skip compatibility and migrations, and go straight to 𝘁𝗵𝗲 𝘀𝗶𝗺𝗽𝗹𝗲𝘀𝘁 𝗰𝗼𝗱𝗲 𝘁𝗵𝗮𝘁 𝘄𝗼𝗿𝗸𝘀. Then a four-step loop: docs first → tests → smallest implementation → clean up. Copy and paste it into your AGENTS.md 👇

Up to $5.5M to move your startup to Qatar. Just an MVP gets you in the door. The Startup Qatar Investment Program (backed by QDB) funds tech startups to launch or expand in Qatar. Two tracks: START: up to $1.1M if you have a proof of concept or MVP GROW: up to $5.5M if you're already established and expanding What else you get: - Entrepreneur visa + flexible work visa - Registration and license fees waived - Subsidized housing - Subsidized co-working space - Access to R&D and innovation grants - Mentoring, training + help hiring talent and interns - Your product showcased at exhibitions Sectors they want: - AI & ML, B2B SaaS, FinTech, HealthTech, Cybersecurity, Climate Tech, Robotics + more - Not on the list? It's open to any innovative startup Apply link below 👇 startupqatar.qa/en/investmen… Bookmark this + tag a founder looking for a new market.