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Toby Laforest posted thisI almost left legal tech. I left Product Marketing instead. My playbook has always been the same: jump into a new industry, lean on my PMM chops to learn everything about the players, buyers, and trends. Turn that insight into strategy and stories. Then do it again somewhere new. But then I found a company that broke that pattern. The team, brand, and product felt different, new and exciting. The more I learned, the more I realized leaving would mean watching from the sidelines. And I don't do FOMO well. So, I've joined Sandstone as Chief of Staff & Operations — a role that lets me take everything I've learned in PMM and apply it at the operational level. If you're curious, reach out — I'd love to show you what made me stay.
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Toby Laforest posted thisThis is the first week of my post-Ironclad career, and I'm overwhelmed with gratitude — for the experience, the results, and the connections made. The last 5 years will always hold a special place in my memory. Thank you to Cai Wangwilt and Jason Boehmig for building an incredible company that championed ownership and innovation. Thank you to all of my mentors/colleagues. The people of Ironclad taught me how to grind, laugh, lead, explore, and even cry. LH ;) Former Cladiator is a title I'll carry with pride from here on out. 💚 🤝
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Toby Laforest shared thisAn AE told me our GTM agent gave them a bad answer: A prospect asked if we support a specific capability. The AI said no. It was technically correct. But "no" isn't how you sell. The right answer acknowledges the gap, offers what we do have, and reframes around the prospect's actual problem. Any good AE knows this instinctively. The AI didn't — because it didn't have the right context. It had product docs [MCP]. It didn't have the sales playbook [skills]. It didn't know this was a prospect conversation [prompt]. It couldn't see the emails or listen to the calls [tools]. Context in AI isn't one thing. It's layers — prompts, skills, connected data, memory. Get one layer wrong and a "correct" answer becomes a bad one. I've been trying to wrap my head around all of it — MCPs, skills, plugins, agents — and realized they all map to one question: how do you give the model better context? Put together a breakdown of how context has evolved, but hopefully it helps guide how to leverage context as well!
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Toby Laforest shared thisThis week was a big week for the application layer. Let me explain: Everywhere I looked this week: sensational AI claims, anxiety-inducing predictions, and lobsters. What started as a recap to make sense of it all turned into a realization: 1. Clawd Bot became Moltbot, until it quickly became OpenClaw. OpenClaw feels like a step toward “sentient agents,” but the underlying experience isn’t wildly different than interacting with ChatGPT or Claude. The real unlock is the architecture: a clever (and expensive) setup that makes the system feel autonomous. Claire Vo explains it well here: https://lnkd.in/e7muEvzS My takeaway: it’s the world's first minimally supervised agent to be adopted by the masses. 2. Because of that, we now have Moltbook: a “social network for agents.” Half the takes are “this is the end,” half are “this is obviously fabricated.” I think the truth lies somewhere in between. Vox: https://lnkd.in/eC6qWaWY Jack Clark: https://lnkd.in/e9K99XpF My takeaway: we’re watching the internet layer form around agents (and I'm more afraid of what the internet holds). 3. In both examples above, the underlying change wasn’t the model. These moments didn’t happen because there’s a new frontier model — the application layer advanced. That’s a strong argument for the power of the application layer… but it’s also a reminder of something more important: AI safety isn’t just a “model lab” problem. When the leverage shifts to tooling, orchestration, memory, permissions, and distribution, then the responsibility shifts too—toward everyone building and deploying these systems. Because the risks don’t come only from “smarter intelligence.” They come from: • what the system can access (permissions/data) • what it’s allowed to do (actions/workflows) • what it remembers (context/memory) • how quickly it scales (distribution/adoption)
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Toby Laforest posted thisRight before the holidays someone said: “LinkedIn is brutal. Too many work influencers posting ChatGPT fluff.” The next day, I shelved the Linkedin draft I was working up courage to post. New year, courage found, fingers crossed, here I go: I spent the past 48 hours experimenting with Hindsight, Gong's new AI Theme Spotter, and agent builders in n8n & Glean. If you’re not leveraging Gong in 2026, you’re flying blind on purpose: turning transcripts into insights is actually doable these days. Via Gong natively: Their new “AI Theme Spotter” can extract themes from thousands of calls. So when Tina Staroselsky (Revenue Marketing) asks for an updated read on the pain points we’re solving, I can pull real buyer language + a stack of quotes in minutes. (1 of many use cases) Via a third-party tool: Hindsight combines Gong transcripts, SFDC notes, and email content to build detailed deal reports. We've used Hindsight to make our win/loss program 100 times more insightful. Via custom agents: Glean (beginner) and n8n (advanced) allow you to build your own agentic automation. Examples: Pull the last 10 calls that mention Competitor X and update our existing battlecard with any new insights. Daily find all the calls that mentioned Product X and draft a short summary for my Product Manager. Ok this post took hours to write and is only ~200 words—I understand why so many outsource it to ai...
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Toby Laforest posted this“In an industry with thousands of talented PMMs grinding every day? That's like making a list of "The 100 Best Tacos" and pretending the other 47,000 tacos don't slap.” We're Not Marketers 💀
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Toby Laforest shared thisIronclad Live is back on September 14 and if you’ve ever worked with a contract you won’t want to miss out. We've got something pretty special to show you. Whether you are a lawyer, salesperson, marketer, in HR or procurement - Ironclad Live has something for you.
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Toby Laforest shared thisAs a product marketer, I've really enjoyed working with the Enterpret team the last few months. Their technology is helping us unlock insights from the thousands of gong conversations we record. Encourage every PMM to take a look!Toby Laforest shared this🚀🚀BIG LAUNCH DAY - I am thrilled to announce Enterpret's partnership and native integration with Gong. Now, as a product builder, using Enterpret, you can - 1. Quantify and listen to exact snippets of top product feedback reasons for any cohort of opportunities/accounts? ✨✨"What product feedback comes up most often in Enterprise deals we lost over the last quarter"?✨✨ 2. Subscribe to summaries on specific topics you care about- ✨✨"Send me a summary of the conversation about competitor X in slack everytime a prospect brings them up."✨✨ 3. Easy and productive self serve research - ✨✨"I want to listen to all snippets where a SMB prospect gave pricing feedback since last month"✨✨ For teams that use Gong, it is one of the highest quality and most up to date customer feedback repositories(I use it every single day). And now with Enterpret, product orgs can fully leverage this valuable data set to drive more revenue for the business. So long the Sales<>Product divide 👋 Link to the integration page in comments.
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Toby Laforest reacted on thisToby Laforest reacted on thisIn AI-assisted coding, there’s something called "YOLO mode" where you give the AI agent full control over your codebase. Today, I am hitting that button on my career as I resign from Clifford Chance to pursue legal AI full-time. There has been a lot of chatter about whether lawyer-built solutions are the future, and whether the “legal quant” is a real talent category. There is no better way to answer this than to walk the walk and create value in the market directly. I will be LegalQuants’ first deployment. Over the next few months, I will be working with in-house counsel to solve complex legal problems by building tailor-made software and systems that off-the-shelf AI tools simply cannot handle. Because my deepest expertise is in funds law, I am inviting all GPs and LPs to throw your hardest legal problems at me, the ones you would expect someone with extreme AI fluency and BigLaw training to be able to solve. I bring not only my own tech stack, but also experience building and deploying products that went viral in a BigLaw environment and the insights I have gained from founding and being part of the world’s best lawyer-coder community. My thesis is simple. The best lawyers of the AI era will not sit in the back office acting as a support function. They will be in the trenches, close to the problem, under real commercial pressure, building and shipping solutions on the fly where demand is hottest. If that resonates and you are interested in working together, let’s talk. Please send me a DM or fill out the Google form here (https://lnkd.in/gmhwDkan). Finally, to my former colleagues at Clifford Chance, thank you. It was a privilege to work alongside such brilliant minds. And a special shoutout to the Nova community, thank you for being the spark behind this AI journey.
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Toby Laforest reacted on thisToby Laforest reacted on thisI’ve been demoing (and re-demoing) a lot of legal AI tools lately and honestly, I’m blown away by what I’m seeing. Hint: it’s not better drafting tools. It’s AI becoming the operating system of a legal department. Think less “chatbot” or “Word plug-in,” and more like a combination of: → a framework → and a front desk for Legal Before a lawyer even touches a request, there are tools that will: • Intake and categorize the request • Pull business context from email and Slack • Identify the type of work (NDA, marketing, regulatory) • Flag potential risk areas • Pull the right templates, policies, and playbooks • Draft a first-pass response • Route it to the right attorney So instead of starting from scratch, lawyers start from: → a structured issue → a framed risk profile → a clear next step This is exactly what lawyers need right now when considering an out of the box/semi-customizable integrated solution. Right now, most teams are still using AI to: • look things up • draft faster • That's it. But the bigger opportunity is using it as infrastructure, something that sits in front of legal work and shapes it before it begins. This is the shift: AI isn’t just a better database. It’s a task agent. A real assistant that organizes, routes, and frames work. Legal doesn’t bottleneck because drafting takes too long. It bottlenecks because: • intake is messy • context is missing • risk isn’t framed early AI can fix that layer. So exciting. #FutureofLaw #LegalAI #ArtificalIntelligence
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Toby Laforest reacted on thisToby Laforest reacted on this🛫 Heading to the US for the next couple of weeks, and I couldn't be more excited about it. 📍 First stop: San Francisco for HumanX (April 6-9) at the Moscone Center. We'll be at booth # B4 with the Pento team, showing how we help companies take AI from concept to production. If you're exploring how to turn AI ideas into real, measurable solutions, come say hi 👋 📍 Then: Salt Lake City (April 13-15), continuing conversations and connecting with builders in the region. At Pento, we help companies bridge the gap between AI ambition and actual business impact. From semantic search engines processing millions of requests daily, to agentic AI pipelines automating complex workflows, we've seen what it takes to make AI work in the real world 🚀 If you're attending either event, or just happen to be around, I'd love to grab a coffee and chat about what you're building. Let's connect! #HumanX #HumanX2026 #SanFrancisco #SaltLakeCity #AI #MachineLearning #AgenticAI #GenerativeAI #Pento #AIConsulting
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Toby Laforest reacted on thisToby Laforest reacted on thisExcited to share that I've joined Sandstone as a Marketing Associate! Just wrapped up my first week and couldn't be more excited to be surrounded by such a driven and inspiring team. Sandstone is building something really special for in-house legal teams, and I'm thrilled to work alongside Maggie Pote to help tell that story. Making the pivot from fashion and beauty PR to legal tech felt like a leap, but I want to thank Jarryd Strydom, Nick Fleisher, Stephanie Nweke, and especially Maggie for their support and for believing in my vision and enthusiasm. A special thanks to Janelle Gray-Gilbert and Gabriella Carota at Isle of Monday. Working with you both has been one of the highlights of my past year. So excited to see how you continue to transform the fashion industry! Excited for this new journey! 💥
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Toby Laforest reacted on thisToby Laforest reacted on thisLife advice: marry a smart, handsome husband who BUILDS. Because DIY landscaping is a nightmare. When we moved in to our new home, we ripped out every plant we disliked. Then we spent months staring at patches of bare soil. We tried every solution out there: • Landscape designers: too expensive ($3-7K). • Pinterest: infinite vibes, zero instructions. • ChatGPT: only works if you already know exactly what to ask for. We didn't want a pretty vibe board. We wanted a plan. So we teamed up for our first collab and built Gardenful - your AI landscape designer. Gardenful takes the guesswork out of your yard. It maps your space, matches your style, gives you a beautiful and practical plan, and builds your shopping list. Landscaping should be a fun, not a chore. We’re opening up early access today! See link in the comments. 👇
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Toby Laforest reacted on thisToby Laforest reacted on thisJoin Ironclad and Deloitte to learn how integrating contract intelligence with SAP transforms static agreements into operational data — enabling continuous margin governance and closing the procurement value gap. #ironclad #sap #ProcurementTransformation #SupplyChain https://lnkd.in/ec2HHRmy
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Toby Laforest reacted on thisToby Laforest reacted on thisThere's a personality assessment called CliftonStrengths that corporate America pays good money for. One of the traits it measures is "Individualization", the instinct to study people as individuals before deciding how to work with them. I scored well on it. I'm fairly certain every Sri Lankan who has ever taken this test scored high on this. Because where I come from, that's not a special talent. It's what happens before the tea is poured. In Sri Lankan culture, the first meeting is rarely about the business. It's mostly about the person. You sit. You eat. You ask questions that a Western HR department would flag as quite inappropriate. You're not networking. You're reading. Who is this person? What do they care about? Do I trust them? Do they like their tea with cream and sugar? Are we related somehow? These are serious questions. I didn't know this was unusual until I got my first real job in America and was told to build rapport in the first five minutes and then get to the pitch. Five minutes. To a Sri Lankan, five minutes is when the tea arrives. You haven't even asked about their family yet. We're nowhere near business. We might not get there today. That's fine. There's plenty of tea. Personally, I didn't know how to do it differently because of where I come from. When I sit across from a customer, it's hard for me to stick to a discovery framework. I'm doing what every Sri Lankan does when someone walks into their home, trying to understand who you are before we know how we can serve you. The SaaS industry spent twenty years trying to systematize trust. Discovery scripts. Qualification frameworks. Rapport building modules with role play exercises that make everyone in the room want to disappear. All of it trying to approximate something that Sri Lankan families do without thinking. Sit someone down, pour them some tea, ask real questions, and by the time your blood sugar is sky high from 5 cups of tea, learn something about you. My sense is that the best people navigating your customers all share this instinct regardless of where they come from. They study the people first, then the problem after. Because, depending on who you talk to, the problem can be different. They listen for what isn't said there and why. Without that, you're only working with part of the equation. If you've ever worked with a Sri Lankan, I'm sure they felt like warm people. They are. They also knew more about you than you realized. That's what the tea is for.
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Toby Laforest liked thisCongrats to Apple for 50 years! I’m grateful I was able to experience 13 of those 50. It was a special place to work, and I’ve always said I’m glad it was the last place I ever worked, because to me, working anywhere else after Apple would have been a challenge. So many amazing experiences…… and challenges. Photos are from the 1st SoHo Apple iPhone launch in the only NYC store at the time (except for Staten Island of course!). June 29, 2007.
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