📢 Introducing WorkForge: a scalable framework that constructs verifiable training environments for long-horizon work agents from real-world resources. Starting from expert workflows, it builds authentic workspaces, extracts checkable facts, and derives tasks plus dual (programmatic + semantic) verifiers grounded in observable evidence. 🚀 We scale to 16.7K environments across 40 professional domains covering 60 file types, enabling consistent gains on long-horizon work benchmarks as data volume and interaction horizon increase. 📚Paper: @zhang_leo54389 @ZoeyyyZhououou @Be1ong1 #Tencent# Hy#AIAgents# #WorkAgents# #AgentTraining#

a lot of the work agents will pay each other for can't be checked with code - real life isn't binary is it good enough? did it follow the guidelines? @GenLayer is the disambiguation machine: it reads the evidence & decides who gets paid

Join us for the first-ever SkyRL Meetup! It's been a year since we released the SkyRL library. SkyRL now has 2k+ GitHub stars and a growing user base in academia and industry, including researchers from Stanford, CMU, UC Berkeley, Microsoft AI, Datadog, and more. We're hosting a SkyRL Meetup on August 18th at the Anyscale office in SF. We have a special set of lightning talks: 🔗 Making frontier RL training accessible to everyone, from @trajectorylabs 🐶 Post-training an SRE agent with SkyRL, from @datadoghq ⚡️ Scaling RL with SkyRL on AMD GPUs, from @AMD 🧑🏻‍💻 Training knowledge work agents with SkyRL, from the SkyRL team (@charlie_ruan) We’ll also do a deep dive into the library and talk about the road ahead. More details here:

The Latest CRO Confidential with @samdblond s out! "$0 to $600M in Under 4 Years. The ElevenLabs GTM Playbook" Carles Reina was the fourth employee and first GTM hire at ElevenLabs. Four years later: $600M+ ARR and an $11B valuation. Today he's a Partner at Baobab Ventures, helping the next generation of startups scale. In the latest CRO Confidential, hosted by Sam Blond (CEO and Co-Founder of Monaco), Carles breaks down exactly how they built it. The revenue ramp alone is jaw-dropping: $0 to $100M ARR in 20 months $100M to $200M in another 10 months $200M to $330M in another 5 months $330M to $600M+ in another 6 months #1#. Distribution from day one ElevenLabs never bet on a single channel. Every market got its own thesis: why launch here, direct or reseller, what does GTM look like in the first 90 days? Core markets were sold direct; everywhere else, resellers got the technology into market fast. Distribution plus relentless experimentation was the whole game. #2#. The grants program that killed the competition Carles came back from holiday with one question: how do I kill my competition? The answer: give startups with 25 or fewer employees free credits for 3 months. They gave out tens of thousands of grants, made a ton of noise about it, and pulled demand away from every competitor in the market. Over 10% of ElevenLabs' enterprise revenue eventually came from upselling those grant recipients as they grew. #3#. The 20X quota model This one's controversial. At ElevenLabs, a $100k base salary meant a $2M quota — 20x — with uncapped commissions. Reps regularly hit 300-600% of target, and average attainment across the entire GTM org ran 167% every single quarter. Carles' theory: he'd rather have a lean team of killers crushing quota than a bloated team missing it and complaining. And when a market genuinely broke, they'd grant quota relief — the commitment was that comp would always stay fair. #4#. Only pay commissions on recurring revenue Sign a giant one-off or a 2-month POC? Zero commission — because it added nothing to valuation. Roughly $1M of real recurring revenue was worth ~$33M in valuation, and reps were paid generously on that. Incentivize the outcome that matters, not the inputs. #5#. What he'd do differently: enablement and senior sellers, earlier Two regrets. First, sales enablement came too late — it's always underinvested until the team is too big to onboard properly. Second, hire senior sellers earlier. Hungry young reps are great, but people with 20 years of relationships who know procurement compress timelines dramatically. Either regret fixed might have gotten them to a billion faster. #6#. Wire AI into GTM, but sell the team on productivity, not replacement Carles pitched the founders on building an AI SDR, an AI AE, and an AI customer success manager. The team's first reaction: "am I going to get replaced?" They proved the opposite. The AI SDR answered inbound emails in minutes and improved conversion rates. The AI CSM worked long-tail and mid-market upsells automatically — and the human account owners still got paid the commission. Productivity story, not replacement story. #7#. Test 100 things. You only need one to work Carles told the team he only needed one experiment to hit to add another $100M in ARR. So run everything in parallel, kill what fails fast, and treat a failed experiment as a win — you learned something. Add to that: make it insanely easy to do business with you, from pricing to onboarding to time-to-value. 👉 Distribution is everything, incentivize recurring revenue (not meetings), be famously fair to your salespeople — reps who get rich make everyone around them believe — and let AI do the work agents are best at while humans do the relationships and the creative bets no agent would ever come up with. Watch the full episode:

ngl i think most "AI agent" projects rn all kinda look the same. - another chatbot - another dashboard - another "AI can do everything" pitch... Spent a bit of time reading @workagnt today and smth clicked for me. They're not really building chatbots. They're trying to build an AI workforce on Base. > Builders create specialized AI employees. > Businesses hire them. > Agents work 24/7. > Top performers earn more and build onchain reputation. Lowkey the flywheel here is what got me: more builders → more agents → more business usage → more value → attracts more builders again kinda simple... but simple loops usualy win lol And if AI agents can eventually hire other AI agents? thats where my brain paused for a sec. Feels less like another AI wrapper and more like LinkedIn + Upwork but for digital workers. Maybe im overthinking it tho. Curious if ppl think AI "employees" become a real thing or if we're still early 👀 $AGNT