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Seasoned strategic partnership/alliance executive with extensive experience developing…
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Are You Using AI Agents To Automate Tasks As A Business Development Professional? If Not, I Did The Research For You.
Are You Using AI Agents To Automate Tasks As A Business Development Professional? If Not, I Did The Research For You.
Business development professionals seeking to automate repetitive tasks such as lead generation, pipeline management…
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John Joyce reposted thisJohn Joyce reposted thisI've spent millions of dollars buying, deploying, and investing in Partner Portals. And it used to take me 6 months or more to get access to new features from my vendors, and every change to the portal was like pulling teeth. Now, thanks to Lovable, the people closest to the work and the best partner teams can build their own tools. Next Wednesday, join Dylan Hattem, Opeid E.ttem, Opeid E. and Kim Veerbeek to learn how we build, customize, and iterate on our own portal and technology. Register at: https://lnkd.in/eFabjqWt #PartnerOps #PartnerMarketing #SolutionsPartners
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John Joyce shared thisPerplexity recently announced "Portable Computer", a version of Perplexity Computer that runs entirely on a local machine. It was developed and built with NVIDIA so users can own the stack on the NVIDIA DGX Spark™, NVIDIA’s desktop-sized AI computer. (It will soon also be available on NVIDIA RTX GPU PCs). Key Takeaways: 💻 100% Local Execution: Runs the orchestrator LLM, subagent LLM, and agent harness entirely on your local machine with zero cloud dependency and zero token/credit costs for local tasks. 🛑 User-Gated Cloud Escalation: “When a task needs frontier reasoning, the orchestrator asks for approval before routing it to a frontier model in the cloud.” 🧠 Supported Models: Ships with local support for Qwen 3.8 27B and PPLX 27B, with NVIDIA Nemotron 3.5 Lightning coming soon. �� Apps and Tool Integration: Connects locally to private codebases, files, and tools, with optional user-approved connectors for Google Drive, Gmail, Slack, and GitHub. Do you think this type of solution will quell concerns about data privacy, risk, and compliance when companies implement AI agents? https://lnkd.in/e336UWCC
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John Joyce shared thisNvidia to buy Hugging Face for $12.9B... https://lnkd.in/ekuZpAccNvidia agrees to buy Hugging Face for $12.9 billion, report saysNvidia agrees to buy Hugging Face for $12.9 billion, report says
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John Joyce reposted thisJohn Joyce reposted thisCome get the prompts, slides, guides, tips, tools, and playbooks you need to effectively enable AI to do "your dirty work". Because if you're still... • Manually researching partners • Manually approving partner applications • Manually pulling partner data • Manually generating ELT reports • Manually creating enablement • Manually entering deals and leads • Manually sharing account lists • Manually entering conversation notes • Manually reviewing sales and cs calls • Manually tracking and paying partners • Waiting for marketing to build pages • Waiting for marketing to create success stories • Waiting for marketing to create on brand decks • Waiting for marketing to approve content ... basically waiting or manually doing any of the 192 things Claude, ChatGPT, and specific Partner AI Tech can now do, come to our free monthly webinar. We'll specifically be covering: <> From 1,000 Overlaps to 100 Deals: The Claude Co-Sell Playbook For Partner Leaders • Russell Bradley-Cook <> Q&A - 10 Things Partner Managers Should Stop Doing... and Let Claude Do • Teddy Ludmer and Thorunn D. <> Live Build... Claude CoWork For Targeted Partner Discovery & Recruitment • Scott Murtaugh <> Q&A - The Power Of Executive Dinners & How To Organize Them To Drive Pipeline • Rob Moyer and Nick Sands <> The PRM Power Hour — Inside Top Revenue Platforms For Affiliate, Co-Sell, and Tech Partner Programs • Tyler Calder 📅 When: August 27th (Thursday) ⏰ EMEA: 2pm BST | 3pm CEST ⏰ US & Canada: 1pm EDT | 10am PDT 🔗 https://lnkd.in/e_3SBVxb We've shorten the event to just 2hrs and we've also got new EMEA-friendly times and topics! If you can't make any of the above, sign up anyways and we'll send you the recordings, slides, prompts, and transcripts. The timing to learn new things is never perfect. But for the best partner managers and directors, they make the time.
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John Joyce shared thisDo we need to create "AI Parents"? https://lnkd.in/epK9JThmHow a simple request for AI to book a gym class exposed a major threatHow a simple request for AI to book a gym class exposed a major threat
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John Joyce shared thisSharing with my network of amazing marketing professionals!!!John Joyce shared thisWe're growing the marketing team at TaxCloud! I'm hiring a Manager, Content & Brand. We publish a lot of content, but no one owns how it all fits together or how our brand shows up in market. That's this role. I'm looking for someone who treats content as a craft and brand as an asset, is genuinely AI-forward, and sees one asset as the start of many. If that's you (or someone you know), send them my way. 👇
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John Joyce shared thisSharing with my network. Great team, great product!!!John Joyce shared thisIn case you missed Greg’s post last week… We’re hiring. A lot. When Greg and I started EULER, it was just the two of us trying to build the product we wished existed. Today we’re a team of 40+ helping power some of the best partner programs on the planet. And we’re just getting started. We’re hiring across Engineering, AI, Product, Design, Sales, Marketing, Customer Success, and Support. A few things that make this a unique place to build: • We grew revenue 600% last year, and the pace hasn’t slowed down. • We’ve doubled the team over the last six months, and expect to do it again. • Every day we get to solve problems for companies like Gong, BambooHR, and many of the world’s most innovative software companies. • AI isn’t a side project here. It’s woven into everything we build, every decision we make, and every workflow we rethink. As the technical founder, I’ll add one thing: We’re building with an incredible amount of ownership and very little bureaucracy. If you’re someone who likes shipping fast, solving hard problems, and having your work directly impact customers, you’ll feel at home here. If you’re looking for a place where you can hide behind process, wait for perfect requirements, or just be another name on the org chart… this probably isn’t it. If you’re excited by building category-defining software with an exceptional team, we’d love to meet you. Check out our open roles at eulerapp.com/careers. And if you know someone exceptional, send them my way.
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John Joyce shared thisOn Sunday morning, Microsoft's CEO, Satya Nadella, dropped a truth bomb about a new economic problem at the heart of the AI industry: the Reverse Information Paradox. Nadella mentions, "Nobel Prize-winning economist Kenneth Arrow famously described a paradox in the market for information. 'Its value for the purchaser is not known until he has the information, but then he has in effect acquired it without cost.' In Arrow’s 'Information Paradox,' the seller risks giving away knowledge in order to sell it." He goes on to say, "AI creates the reverse problem. In the AI age, the buyer risks giving away knowledge just to use what they bought. You essentially pay for intelligence twice, once with money, and again with something even more valuable: the proprietary knowledge you must reveal to make that intelligence useful. The better you want the model to perform, the more of that knowledge you have to feed it!" That's pretty scary stuff when you think about it. Is the tradeoff worth it? He does offer several suggestions on how to protect your company's information, and here are the Five C's to consider: 🎛️ Control: Create your own private evals because evals define what “good” looks like within the organization. Also, retain ownership of your organization’s memory, traces, feedback, decisions, and institutional context, and the ability to use model outputs from your own tasks and queries. 🏗️ Capability: Build your own proprietary learning environments within the tenant boundary to train or tune models, where models learn against real workflows without exposing the company’s knowledge. 🗺️ Choice: Ensure the orchestration layer is decoupled from any single model. Ask yourself: If any one model you are using is taken away, do you still have the ability to operate and optimize for your evals using other models? Does your company's “veteran” capability remain with you even if a given “generalist” model is removed? 💵 Cost: By decoupling the orchestration layer, you are also able to bring together context, models, and tasks in the most efficient and cost-effective way without sacrificing quality. ➿ Compound: Bring these four together and you create your own continuous learning loop (i.e., hill-climbing machine) that will allow your AI investments to compound the value of your firm. The reverse information paradox is real, and we all must confront it sooner rather than later. Full article on X: https://lnkd.in/ekt5PXnQ
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John Joyce shared thisDon't forget to sign up for Partner Playbooks' "AI Use Case Showcase" event on Thursday, June 25th. Learn from some of the best minds in the industry as they present 7 AI-powered pipeline-generating programs you can leverage for your own business. Register here: https://lnkd.in/eN-Er9NzNo Fluff. No Filler. Just 7 Ai Pipeline Producing Partner Programs. - Partner PlaybooksNo Fluff. No Filler. Just 7 Ai Pipeline Producing Partner Programs. - Partner Playbooks
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Congrats, Sergey Barysiuk!!!
John Joyce replied to a comment
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Justin Louden, Hi Justin! Over the years, I've built a framework that maps your Ideal Customer Profile and uses it to develop your Ideal Partner Profile. Then stack-rank partner cohorts based on ICP revenue opportunity, etc. Then stack-rank the top 5-10 partners in each cohort based on similar revenue impact opportunity so you can always be laser-focused on the right partners.
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John Joyce liked thisJohn Joyce liked thisMost strategic mergers and acquisitions look seamless on a balance sheet. Integrating two distinct operational cultures without destroying value is the real test. Watching artist Anastasia Mez execute Polaroid emulsion lifting reveals a masterclass in post-merger integration: Using warm water, she releases the ultra-thin, image-bearing emulsion layer from a Polaroid print, then guides it onto a completely separate photograph with a fine brush. If she forces the transfer or rushes the alignment, the delicate emulsion tears instantly. If she lacks the patience to create the right environment, the two distinct images never bond into a cohesive whole. In enterprise integration and strategic alignment, uniting separate operational units demands three core principles: 1. Create the right operating climate before attempting transfer. You cannot force two systems together by executive decree. Like the warm water bath that frees the emulsion, leadership must first dissolve friction, eliminate defensive silos, and establish open communication channels before merging critical processes. 2. Preserve distinct value while building combined strength. A successful integration does not homogenize both entities into mediocrity. The goal is to carefully guide the unique core competencies of the acquired asset onto the existing foundational platform without tearing what made each successful. 3. Delicate guidance beats blunt force. Heavy-handed top-down restructuring often destroys the very talent and institutional knowledge you sought to acquire. True operational integration requires deliberate, tactile management—aligning workflows, cross-training teams, and adjusting systems piece by piece. Whether acquiring a competitor, integrating legacy software with modern tech, or merging cross-functional departments: never rush the alignment phase. Sustainable synergy is not decreed on paper. It is integrated layer by layer. [Day 3/10: Strategy & Operational Excellence Series] What is the biggest operational challenge your organization has faced when integrating new teams, technologies, or legacy workflows? #BusinessStrategy #OperationalExcellence #Leadership
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John Joyce liked thisJohn Joyce liked thisAdam Neumann is doing interviews again, talking about failing spectacularly in front of the whole world and getting back up. WeWork peaked at $47B valuation. Then the crash happened. Company imploded. Failed IPO - which later led to bankruptcy. Three years later, Andreessen Horowitz wrote him a $350M check for his new company. The biggest single check in the firm's history. Adam is now telling the story himself, in a 2 hour interview with Steven Bartlett. Why? Because he's now taking ownership of his own narrative, and I bet we're going to see more of him on social media from here on. But my question is: Could this comeback have happened in Europe? 🇪🇺 I honestly dont think so.. Not at that speed, and not with that kind of backing. In the US, failure reads as experience. Andreessen Horowitz even said that's why they invested in him. Because he got back up and tried again after that big of a public failure. Only very few outliers do that. In Europe, it reads more as a permanent record. For starters, the culture around failure is different here. Secondly, capital behaves differently. Smaller funds, longer memory. Only one of the two continents hands you a second act like this. And only one kind of founder goes out and tells the story himself. Am I wrong? Would he have been funded again in Europe? Would we accept him trying again here? Curious what you actually think.
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John Joyce reacted on thisJohn Joyce reacted on thisPartner outreach is the one thing I've never let a tool touch. It's way too personal… And one bad intro means that partner remembers you for the wrong reason. So end of last week I typed this into a builder just to ‘see what would happen’👇🏼 "Find B2B SaaS companies with a partner program, score them against my ICP, draft an intro to whoever owns partnerships and ask me in Slack before anything sends” Mind you- this was around 10PM ish. Both of my girls asleep. Mind very much still on. …it came back totally built. That workflow used to live in four places. Four. - Research in one tab - Enrichment in another - Scoring in a spreadsheet somebody built two years ago and is scared to touch - Approvals in a Slack thread, somewhere Every jump between those is where a good lead sits and goes cold while everybody literally assumes someone else has it. I've spent a bunch of my career chasing revenue leaks between teams and that's where they (almost) always are. The intro Instantly.ai drafted wasn't a "let's explore synergies" email, negative. It was built around 1 specific way both sides win- which is the only kind of partner email I'd really ever send. Then pinged me in Slack and waited. That's the part that makes me trust it. Q: where do leads go cold in your process? My money's on somewhere between two steps.☝🏼 For y’all to try out -> https://shorturl.at/UAKVr
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John Joyce reacted on thisJohn Joyce reacted on thisToday we launch PandaDoc CLM. You will see plenty about what it does, so I want to talk about what makes it work. Over the past year, we rebuilt how PandaDoc stores documents: from a model built around how a document looks in a browser to one built around what it means. When a contract is signed or uploaded, we classify it (contract, NDA, proposal, quote, SOW, amendment) and extract 100+ data points: counterparty, contract value, payment terms, notice period, dates, auto-renewal terms, key clauses. Each document also gets summaries at several lengths and is indexed for semantic search. To answer "when does this renew?" from a PDF, an agent has to load the whole document into its context. That costs time and tokens, and it gets worse the longer the document is. Across a whole library it does not work at all. But with structured data points, the answer is a field. A question across all your agreements becomes one query instead of hundreds of documents opened one at a time. That data layer is what powers CLM: renewal alerts, reports, search, summaries. It is also what we expose through MCP, so Claude, ChatGPT and agents your team builds can work with your agreements directly. We designed those tools around tasks, not API endpoints. "Find contracts with Acme expiring in the next 60 days and return their key terms" is an optimized call, not multiple ones stitched together. The agent spends its context on your answer, not on making sense of raw data. Doing all of this across a corpus of hundreds of millions of documents was one of the most interesting and challenging engineering problems we have taken on. What ships today is the foundation, with more intelligence on top of it to come. Models keep getting better, and we keep giving them a cleaner view of your agreements. Everything built on top gets better with it. Learn more about PandaDoc CLM: https://lnkd.in/gZwf3wJB
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John Joyce reacted on thisJohn Joyce reacted on thisThree security researchers from Hacktron say they went from OpenAI's community forum to an internal OpenAI GitHub repository in less than 72 hours — in an authorized security-research/bug-bounty context. Hacktron researchers discovered and demonstrated a vulnerability chain that could move from OpenAI's public community forum through an OpenAI SSO weakness into employee ChatGPT/Codex accounts and ultimately an internal GitHub repository. The chain began with specially crafted HEIC/HEIF images. Because of the way Discourse handled those images through ImageMagick and the vulnerable libheif library, the researchers were able to achieve remote code execution on the forum environment. They then chained that access with a separate weakness in OpenAI's SSO implementation to obtain access to ChatGPT and Codex accounts, including an OpenAI employee account whose Codex was connected to OpenAI's GitHub organization. https://lnkd.in/g5ur-iVJ According to Hacktron, Claude Opus 4.8 struggled to produce a reliable exploit. After Anthropic released Claude Opus 5 on July 24, the researchers say they had a working exploit within hours. https://lnkd.in/gj2csDQG The researchers say they did not intentionally read or download sensitive source code; they stopped after using the compromised Codex account to create a harmless pull request as proof of access. OpenAI's review, however, reportedly detected limited reads of private-repository metadata and commits. OpenAI reportedly fixed the SSO issue in about 14 hours, narrowed Community sign-in permissions, revoked affected sessions and tokens, and later paid Hacktron a $6,500 bounty for the OpenAI-side finding. Discourse separately patched the HEIF/libheif vulnerability and published a High-severity security advisory. ----------- The detail that caught us was how far the chain went without the researchers taking the final step. They reached a private repository, created a harmless pull request to prove access, and stopped without examining the sensitive code. Read and learn more: https://lnkd.in/gE8CF76V https://lnkd.in/gpmt-RnH https://lnkd.in/gbqTvnxS Credits: CTTO #OpenAI #ChatGPT #ClaudeOpus5
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John Joyce liked thisJohn Joyce liked this💡Building an Underground Bunker!🔥 The impressive and creative #construction and #building a hidden underground bunker is truly ingenious. This displays the ingenuity of civil work, #engineering, education and #technology projects which enables #students to explore complex concepts like this in a practical and interactive way. This explores the beauty of #engineering through hands-on projects that fosters problem solving #skills, #teamwork and deeper understanding of our #natural resources and promotes an experiential #learning #STEM #education. Write-up: Olawale Kolawole #innovation #science #teaching #climate #ecosystem #manufacturing #creativity #ai #healthcare #education #economy #bestadvice #manufacturing #inspiration #technology #science #warehouses #management #food #students #leadership #strategy #greenenergy #whatinspiresme #engineering #teaching #agriculture #greenenergy #construction #tech
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John Joyce reacted on thisJohn Joyce reacted on thisBenioff just shared a stage with Altman at Dreamforce — and walked away looking like the adult in the room. While everyone bets on pure AI plays, Salesforce is quietly threading CRM muscle with AI infrastructure. Benioff doesn't need to win the model race. He needs to own the enterprise layer where AI actually gets deployed. That's a very different — and arguably more defensible — position than building the model itself. $CRM has a moat OpenAI doesn't: 150,000+ enterprise customers already in the workflow.
Experience & Education
Volunteer Experience
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Board of Advisors
St. Mary's Parish
- 10 years
Children
- Committee memeber for local chapter of Why Catholic?
- Leader of youth group
- Web master for St. Mary's in Ayer and St. Anthony's in Shirley -
Executive Committee Member
Groton Dunstable Youth Basketball League
- 10 years 6 months
Children
Projects
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Strategic Partnerships & Marketing Programs
- Present
See projectExamples of strategic marketing programs, highlighting co-marketing campaigns with large brands.
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