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Building, scaling, and leading top performing GTM organizations.
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Grafana Labs 2019 Recap (and some shoutouts)
Grafana Labs 2019 Recap (and some shoutouts)
Q4 is in the books, as is the end of year 1 at Grafana Labs for me. In Q4 we: Averaged 101% attainment across AEs Hired…
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Graham Moreno shared thisLiam H. Mulcahy with a typically insightful, but still impressive, breakdown of how the idea of "infrastructure" is evolving in the world of agents. https://lnkd.in/g_y7-3w9
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Graham Moreno shared thisNot a lot of people can see the future. Even fewer can build it. This is the best explanation (for both customers and potential colleagues) of "why Parallel". Great discussion Parag Agrawal and Harry Stebbings. Excited to be building the next wave of the AI evolution. https://lnkd.in/gve3_4G7The Ads Business Model Will Die & Lessons from Working with Elon at Twitter | Parag AgrawalThe Ads Business Model Will Die & Lessons from Working with Elon at Twitter | Parag Agrawal
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Graham Moreno shared thisWant to work with the best enablement leader in tech, a legendary founding team, an amazing product, and in a space that may eclipse AI coding in terms of growth rate and size? Then check out what Dani McCabe is building in our enablement org.Graham Moreno shared thisI joined Parallel back in April to help build out the GTM function alongside Graham Moreno and Liam H. Mulcahy (and I guess Dave Frankel too). Five months later, it has proven to be a great choice: a world-class product paired with early investment in GTM, the perfect setup to build and enable GTM from the ground up. And now, I’m hiring! I'm looking for a Technical Enablement Manager to help AEs confidently understand, position, and sell a highly technical product. You’ll own product training, demos and eval templates, and customer-facing technical collateral. The ideal person has a DE, SE, or engineering background, with a mix of technical depth and strong sales instincts. If this sounds like a fit for you or someone you know, send me a DM or apply below. I promise we will have fun! 🚀 San Francisco: https://lnkd.in/gmQ5J6b6 🚀 New York: https://lnkd.in/g-SKhN6R
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Graham Moreno reposted thisGraham Moreno reposted thisBenchmark Spotlight: Parallel Web Systems Benchmark: Multi Turn Company Search (Hard) [Search only] This is the multi-hop task. The benchmark is particularly hard because it's just not limited to single "find the answer." It is to Find every answer that exists that satisfies three or four constraints together accurately. Input: Multi-hop company search question, with three or four constraints Output: The complete company set Example query - Which companies were founded between 2016 and 2018, went through Techstars, are headquartered in one of the large Texas metros, and raised at least one priced institutional round? - and return the complete set. Scored against a hand-labelled ground truth: 375 question-company set across 45 questions. Three agent runs per question to account for model variance. Model-only baseline is 0. We ran it with no search tool and it scored nothing. What makes this benchmark hard is the restricted budget. Budget - 8 Agent turns, 14 searches (2 searches each turn), 10 results per search. The shape of the benchmarks shows which half is hard. Best precision on it is 88.7%. Best recall is 34.4%. Recall is what is what makes the benchmark hard. Here's what we found: Parallel Basic is #1 on every correctness and quality axis on the search-only benchmark: #1 on Precision 88.7%. #1 on Recall 34.4%. #1 on F1 46.5. #1 on Exact ground-truth returned 3.7%. No other configuration/vendor on the search-only benchmark leads a single one of them. Precision and recall normally trade against each other. Topping both inside a fixed search budget means that the endpoint is truly robust on correctness. Note that this result is Search Only mode: Search-only means the agent sees titles, URLs and snippets. No fetching. The cost comes from a combination of tokens + search cost: $0.070 median search cost + $1.050 token cost = $1.120 median task cost. Parallel has densest snippets mean the agent gets more, reads more - and that density in-fact reduces the need to fetch. Parallel offers four endpoints: Basic 46.5 F1 at $1.120 Advanced 44.2 at $0.625 Fast 38.0 at $0.460 Turbo 34.7 at $0.419 Every endpoint has a precision of 79.9% precision or better. Scope: search-only is the clean provider comparison - the agent, model, prompt, budgets and result limit are held constant and only the search API changes. Search-plus-fetch is ranked and benchmarked separately. Benchmark and Dataset link in the comments. Runner, judge and dataset are public.
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Graham Moreno shared thisEvery dream(force) of a Parallel universe? Come join our team to hear about the next wave of the web (agents) and how that is changing how the best companies in the world are building (and using) technology. https://lnkd.in/gmthDnuw
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Graham Moreno shared thisExcited to announce our expanded partnership with GCP. "Enterprises want to build AI agents on an open platform with the best tools to deliver real value. By adding Parallel as a grounding option on our Gemini Enterprise Agent Platform, customers can now use their preferred live-web data stream to make Gemini smarter. This helps them smoothly take agents from prototype to deployment, all within their existing Google Cloud environment." – Matt Renner, President and Chief Revenue Officer, Google Cloud. As the need for agentic search becomes apparent across enterprise and AI native, it has been amazing to partner closely with Nick Martitsch, Matthew Hart, and the GCP team on bringing our best in class agentic web layer to GCP's customer base. https://lnkd.in/emKMeA8dWhy Google partnered with former Twitter CEO Parag Agrawal's $2 billion AI search startupWhy Google partnered with former Twitter CEO Parag Agrawal's $2 billion AI search startup
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Graham Moreno shared thisNot only is Parallel the highest performing in our space across accuracy, freshness, and relevance (most agentic use cases). Now we are also the fastest and cheapest, without sacrificing accuracy. Can't say it enough -- this roadmap is insane. Feedback has been incredible so far and this is very much just the beginning. Check it out!Graham Moreno shared thisIntroducing Parallel Search Turbo: the fastest and most affordable way to bring the web to your AI. Turbo is in a new class for cost and latency: 5-14x cheaper than alternatives, blazing-fast, and with consistently high accuracy. - 200ms median latency - $1 per 1,000 requests With the addition of Turbo, Parallel Search is now faster, cheaper, and more accurate than any other AI search API on the market. Learn more and experience it for yourself: https://lnkd.in/ei_rN85z
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Graham Moreno shared thisEnjoyed talking to Chris Balestras about all things GTM. Grateful to get a chance to talk about why Liam H. Mulcahy and I reunited at Parallel Web Systems -- why we are so excited about what we're building, and about the influences and experiences that ultimately got us here. Great hiring, great enablement, believing in / trusting your team, and using data to create clarity and focus = great GTM culture. https://lnkd.in/gQExhda6Sales Mafias & What Made MongoDB Great w/ Graham Moreno, VP Worldwide GTM @ ParallelSales Mafias & What Made MongoDB Great w/ Graham Moreno, VP Worldwide GTM @ Parallel
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Come join the Parallel Universe :)
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Graham Moreno liked thisGraham Moreno liked thisHey everyone! It's been an exciting first couple of months at Parallel Web Systems and I am building out our security team. Parallel builds web infrastructure for AI to search, extract, monitor, and reason over the world's information. The product fetches untrusted content from the open web at scale, runs it through an agentic pipeline, and returns structured, cited results. It is an unusual surface and not many teams are working on it yet. I am hiring for two roles: Product Security. Secure the agentic surface. Eliminate vulnerability classes instead of individual bugs. Build secure defaults engineers inherit rather than configure. Build security tooling on current models. Infrastructure Security. Identity and access, cloud and Kubernetes hardening, secrets, the path from source code to running workload, and the logging and detection layer underneath it. Link in comments. Please apply directly or pass along within your network.
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Graham Moreno liked thisGraham Moreno liked thiswho says you can’t have fun and generate pipe at the same time? feeling extra grateful for my team Parallel Web Systems
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Graham Moreno liked thisGraham Moreno liked thisClosing my chapter at Harness and grateful for the time there. It’s been a joy to lead the Deal Operations & Strategy, Provisioning, Order Management and Renewals functions, including Product GTM & Commercialization and being part of the M&A integration team. I would especially like to thank my wonderful team who has been through this journey of growth (& chaos), deal strategy and operational excellence with me. A huge THANK YOU to Nikalas McClure, Danielle Cain Wilson, Steven Odorczyk, Chandni Sahu, Abhigyan Harshwardhan, Benoy Roy, Kiran Singh, Navpreet Sharma, Jiten Kanani, Jamie Ko, Cal Pettinelli, Brian Collins, Becky Videbaek, Joshua George. It has been so wonderful working with each one of you. A big thank you to John Bonney for hiring me. It was awesome working with you and really glad our paths crossed. And thank you Jyoti Bansal for your leadership and product visionary.
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Graham Moreno liked thisGraham Moreno liked thisOG sales leaders I’m a fan of, to name a few: Mike Earnest at Wiz; Parm Uppal at Chainguard; Austin Stefani at dbt Labs—although maybe that’s called Fivetran now; Jeff Perry , CRO at Carta; Jennifer Lawrence at RedPanda, Matt Gahr of ex Cornerstone and Spiff/Salesforce fame, Marc Jacobs , who has had success at a lot of places. I’d also include Matt MattMatt PlankPlank at Rippling, although I’m not sure I’d call him OG. He falls somewhere between the new guard and the OG category, but he’s certainly been massively successful in building Rippling. Then there’s the new guard—the new-era, up-and-coming sales leaders I’m a big fan of. I’d include Todd Busler at Clay; Walker Fitch at Artisan; Nick Casale at AirOps; Evan Cassidy at Decagon; Jack Gashi at Avoca; Alex Cramer at Cresta; Adam Ali at Rox, Jonathon Blackburn of Nooks/Lattice fame, Steve Smith at Canopy Connect; Mike Donahue at Maven AGI, Marchelle Renee Mooney at Mangomint, Josh Roth Gorgias, Jon Parisi at Tavrn AI, Ochart at Gong, and Mike Haylon at Numeric. Some are friends. Some are not people I know super well. All I have a lot of respect for. I know how hard the job is and it’s mostly between the ears.
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Graham Moreno liked thisGraham Moreno liked thisAfter 3 years in AI land, I'm taking a step back to welcome this little guy into the world with Dani Riggs. It was amazing getting to lead the revenue organization at Cognition and I am incredibly grateful to Scott Wu and Russell Kaplan for bringing me on to the team. Cognition is a generational company, with awesome talent, and I'm excited to see where it will go with Chris Degnan at the helm of the revenue org.
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Graham Moreno reacted on thisGraham Moreno reacted on thisLink in the comments for you to find out how much you are overpaying with web search. Intelligence keeps getting better and cheaper but people still paying same for web search which at some models it's becoming more expensive to find info in the web than the model that will use the info to generate an answer.
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Joey Brodsky
Over the past 12 months, GTM compensation hasn’t exploded… …but it has quietly reshaped. We just compared our 2025 vs. 2026 US GTM Salary Benchmarks across venture-backed companies, and a clear pattern is emerging: - Revenue leadership comp is climbing - Mid-market sellers are seeing upward pressure - Enterprise AE bands are polarizing - Entry-level GTM pay is largely flat In short: The market isn’t broadly inflating. It’s selectively rewarding impact. The biggest winners in 2026: - Proven VP/CRO builders - Strategic enterprise closers that forecast exceptionally well - Operators who can drive efficient growth The middle of the market continues to compress. If you’re building a sales org right now, generic “market comp” thinking will get you in trouble. The spread between average and elite GTM talent has never been wider. Full 2026 benchmarks in the link in the comments
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