Daniel Eliasi, MBA

What’s the real business value of AI-first communications? 🤷‍♂️ IDC did the math. Dialpad customers saw measurable gains in productivity, revenue impact, and operational efficiency after switching to a native AI platform. Want the numbers behind the claims? ➡️ Download the IDC report: https://bit.ly/3M2Ipsu #AIinBusiness #CX #AgenticAI #Dialpad #IDC

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Big day for Jasper, and an even bigger one for marketers! Today they unveiled the new Jasper: a multi-agent AI platform built specifically for enterprise marketing teams. A full rebuild of how strategy, content, and execution come together. Jasper Canvas is a collaborative workspace where you can build and execute campaigns across every channel in one place. Jasper Agents turn routine tasks into autonomous flows, which can be used for tasks like campaign research, SEO, personalization & audits running on their own, fully brand-safe. And for the rebrand 🤩 - "A clearer expression of who we are and how we’re helping you lead modern marketing." Really love it. They launched their new identify + an impressive batch of new features today, check it out: https://lnkd.in/e8d2fYM3

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Wondering what Forward Deployed Engineers actually are and when it makes sense to use them? I recently had a great conversation with CJ Gustafson on FDEs, and how we use them at Invisible Technologies. We spoke specifically about FDEs as a GTM choice, how the economics change when engineering is pulled forward into the sales motion, pricing models, metrics to measure health of business and lots of other things. Check out more on the latest Mostly Media newsletter. If you're not subscribed, highly recommend subscribing. Link in comments.

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If you search for "AI consulting Portland Oregon," most of what comes up isn't actual consultants. It's directory sites, template location pages from companies overseas, and agencies that just added "AI" to their services list. This post covers what legitimate AI consulting includes, seven questions to evaluate firms, and actual cost ranges for the Portland market

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Here's another fun post I enjoyed writing! We walk through how to segment customers into groups with shared characteristics so we can accurately size the market and sequence growth. ❗This is not just an exercise for early stage companies. In fact, we use segmentation across all stages, ranging from - Just a founder with an idea, gut checking whether the market is large enough for a venture-scale outcome - To CEOs of publicly-traded companies looking to identify areas of growth and then prioritize where to deploy resources, in what order.

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bravo,Relvino (formerly Rubydata) . this is what happens when you move beyond the Klaviyo + Attentive playbook. most brands are still running flows and segmentation that were set up months or years ago. lots of rules, lots of manual work, and the systems themselves don’t really learn. when optimization is continuous and actually autonomous, you start unlocking revenue that the legacy marketing stack just misses. great early signal here. happy to be along for the ride.

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There’s an AI reality gap in the enterprise. WSJ reports (👇data below) Executives think AI saves them 8+ hours a week. Employees say it’s less than 2. No surprise then that only 12% of CEOs are seeing real financial impact. The “AI Tax” is real in the enterprise. Teams aren’t moving faster because they’re correcting AI output and reworking  prompts. Generic AI hits a wall without precision. That’s why we built BPA 4.0: - Deterministic decisions grounded in enterprise context - AI that learns the job while doing it Stop paying the AI Tax.  Start demanding ROI from AI. #Techolution #BPA40 #AIROI #CFO #CIO #GoogleCloud

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The best CFOs know segmentation is the soul of strategic decision making. Because without it, you’re allocating capital with all or nothing data. It was easy to tolerate complacency in a zero interest rate environment and you could afford to peanut butter spread R&D and GTM investments evenly across the board. In the current environment (higher interest, fiercer competition, reduced productivity), it could keep your company from growing profitably, reduce valuation, or, worse, keep you from existing (or raising capital) altogether. Segmentation is what allows you to throttle and accelerate allocations the way an investor would. Can you look at your data at these levels? → In sales: What regions, reps, and business lines perform best compared to the others? Which reps need a bit more coaching and which ones won’t work out? Are there roles we should reallocate to higher performing segments? → In marketing: Do you know which of your 5-7 key channels are driving the highest lifetime value (LTV) segments? Which channels are driving a lot of activity but few results? Where should you double down on success versus cutting back? → In R&D: Can you evaluate your unit economics by product line? How does the product roadmap tie into profitability goals for the business? Which new feature releases have had the biggest impact on retention? This is how great CFOs like Pam (Peterson) Martinez (who successfully exited SevenRooms to DoorDash) operate. They set themselves up with this level of data maturity from day one and make exit readiness a state of being. #PrivateEquity #StrategicFinance #FPandA #SegmentationStrategy #GoToMarket #ExitReadiness #FinanceLeadership #FinQore

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Salesforce just overhauled its Partner Program. Here's everything that changed: This wasn't one announcement - it rolled out across March and April 2026. But taken together, it's the most significant restructuring of the partner ecosystem in years. - Four tiers became two. Base, Ridge, Crest and Summit are gone. The consulting track now has two designations: Select and Summit. The real message is that mid-tier positioning no longer exists - you're either Summit or you're not. - 170 badges collapsed into 28 competencies. The legacy credential framework is out. In its place, 28 core competencies built around real-world customer buying patterns with a heavy lean toward Agentforce and Data Cloud. Two recognition levels: Accredited (demonstrated capability) and Expert (scaled delivery excellence). If your credentialing story was built on breadth, it needs to be rebuilt around depth. - How partners are measured has fundamentally changed. No more administrative scorecards and checklist-driven evaluations. Performance is now measured by CSAT scores, certifications and verified project outcomes. - Incentives are being rewired around the full customer lifecycle. Salesforce is targeting $1 billion in partner incentives in FY27. But how those incentives are structured is changing - rewards now cover lead submissions, pre-sales activities and post-sale implementation subsidies tied to agent activation and actual consumption. Partner payouts are being linked to what customers do after they buy, not just the fact that they bought. - Joint Sales Referral fees are gone. If a partner was embedded in an AE's deal and expected a referral check at close, that payment no longer exists. Sourced referrals where a partner brings a net-new prospect still qualify. But the co-sell economics are gone. - Agentforce is now central to partner positioning. Salesforce's partner ecosystem handles 70% of Agentforce implementations. The new program is designed around that reality. Partners who can't demonstrate Agentforce delivery competency will find it harder to reach Summit, regardless of historical track record. Salesforce wants its partner ecosystem to be an outcomes delivery force not an implementation body or a sales support layer. For consulting firms, the window to reposition is roughly 12 months. The competency framework, tier requirements and incentive structure all point in the same direction. That's actually more useful than ambiguity. When a program tells you clearly what it rewards, you can build toward it deliberately. The companies that use this year well deepening Agentforce competency, tightening their CSAT story, aligning delivery to consumption outcomes will enter into a fundamentally stronger position. https://lnkd.in/gUdfC_Nw

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MIT’s recent report found that 95% of enterprise AI pilots fail to deliver ROI, with value trapped in workflows, slow scaling, and misplaced bets in sales and marketing instead of back-office and integration wins. But these are symptoms, not the root cause. The real issue is strategic misalignment, as oftentimes organizations don’t clearly define the kind of bet they’re making. At the core, every pilot is a capital allocation and risk management decision. Pilots fail without clarity on the business angle, hypotheses, and go/no-go criteria. To address this, I’ve developed The Pilot Strategy Framework™, a structured approach to categorizing AI pilots based on their strategic intent and business impact. 1️⃣ Validation pilots - validate feasibility before scaling and committing further resources. 2️⃣ Internal adoption pilots - phased rollout of AI within departments, inside existing workflows, to see if it can unlock ROI. This can often signal market readiness to customers, competitors, investors, and the industry overall. 3️⃣ Customer-facing pilots - test whether existing customers will adopt new AI capabilities and whether it’s commercially safe to scale. 4️⃣ Legacy integration pilots - answer if AI can unlock value in legacy systems. 5️⃣ New product pilots - test whether additional AI offerings can be introduced; offerings that are core or adjacent to our current products and generate new ROI. Each pilot is a bet: upfront decide how much capital to risk, what value it’s meant to unlock, tradeoffs to consider, and the conditions under which you’ll scale or stop. Ultimately, it's about prioritizing the one(s) that provide the most enterprise value. Which pilot types is your organization running, and how are they moving the needle on your business outcomes? I am currently talking to leadership teams to apply this framework to drive clarity and ROI; if your organization is navigating similar questions, I'd be happy to connect. #productstrategy #aistrategy #aitransformation

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Chargebee ‘s Beelieve San Francisco 2026 kicks off tomorrow, focused on Building and monetizing AI era business models. It’s two days packed with leading voices in AI monetization, high value networking, a $100,000 startup pitch off, our inaugural “Agents & Money” dev meetup, 2026 Beelievers awards, and much more … all set at the iconic Fort Mason.

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There's a pattern in PE-backed SaaS that doesn't get talked about enough: the 24 to 36 month inflection point after acquisition, when early momentum meets the realities of scaling. I joined Andrew (Drew) Smith on the Attribution Nation Podcast to explore what I've seen across multiple portfolio companies at this stage, and what the best operating teams do differently. We got into: → How data debt and go-to-market drift accumulate quietly, even when the top-line numbers still look healthy → The difference between a market trust problem and a product-market fit problem (and why the diagnosis changes everything) → Why hypothesis-driven measurement beats static reporting every time → How to stabilize and re-accelerate when growth starts to plateau If you're leading a PE-backed portfolio company or partnering with one on value creation, this conversation covers territory that will feel familiar. The stall isn't a failure. It's a predictable inflection point, and the teams that recognize it early create the most runway. 🎧 Full episode: Spotify: https://lnkd.in/eYc7tVUX iTunes: https://lnkd.in/eznR3tZc YouTube: https://lnkd.in/emjR9szX @Drew Smith @Attribution Nation Podcast

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NOW LIVE! Here are my biggest takeaways from Jeanne DeWitt Grosser (COO at Vercel) on how go-to-market actually scales: 1️⃣ Go-to-market should be treated like a product. Product teams prototype, storyboard, and obsess over user experience. Most GTM teams do none of that. But being sold to is an experience. If you don’t design it intentionally, you’re still creating one, just accidentally. 2️⃣ Sales motions fail because they’re rarely choreographed. The strongest GTM teams think in sequences. What experience tees up the next one? When should a whiteboard replace a deck? When does ROI come in? This is product thinking applied to human systems. 3️⃣ AI only helps after you decide what “good” looks like. Agents are most effective in deterministic environments. If you can’t articulate your best practices, AI will only scale inconsistency. Clarity first, automation second. 4️⃣ Most “lost on price” deals aren’t actually about price. When Jeanne dug into losses, the real issues were things like missing the economic buyer or failing to quantify ROI. Those are process bugs, not rep failures. Treating GTM like a product lets you debug those bugs systematically. 5️⃣ The forward deployed engineer exists because buyers are overwhelmed. Customers often know something needs to change but don’t know what to solve first. The people who win bring structure, frameworks, and pattern recognition into ambiguity. That consulting-oriented motion is becoming core, not optional. 6️⃣ Great sales reps aren’t going away in the AI era. If anything, trust and navigation matter more when decisions feel riskier. The best reps understand an organization’s decision-making better than the organization itself. AI may compress workflows, but judgment remains human. 7️⃣ “Early” is about trajectory (not headcount). Jeanne joined Google, Stripe, and Vercel later than most people think. What mattered wasn’t what number she was joining the company, but rather about the company’s growth trajectory. If you’re worried you’re too late, is it ever too late if the ceiling for growth is high enough? - 💚 Thank you to our incredible sponsor: HockeyStack for supporting the podcast. HockeyStack is the AI platform that unifies GTM data to help teams convert, expand, and scale. 🎧 Tune in and subscribe on YouTube, Apple, Spotify or wherever you like to listen by searching "The GTMnow Podcast." 💡GTMnow by GTMfund: Build, scale and invest with the best minds in tech.

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“I used to dread product launches.” That’s what Alex, our Director of PMM, told me his first week at UserEvidence. Now, he’s launching with 200+ proof points ready to go. Before UserEvidence, every launch meant Alex begging for quotes. Rummaging through outdated decks. Starting from scratch. And when the launch day hit, he still crossed his fingers the story would land because it was powered by a dusty quote that kind of applies if you squint hard enough. That’s life for too many PMMs. But product launches at UserEvidence feel different because Alex is starting with a library. No more scrambling. Just strong narratives, fast execution, and real credibility. Alex wrote about how going from quote-hunting to quote-pulling changed everything, from his launch playbook to how he thinks as a product marketer. The post is gold. Smart lessons, real stories, and a few face-palm moments. Give it a read (link in comments)

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If you're in the 65% of sales leaders that say misaligned marketing and sales organizations is your number one barrier to revenue success... this is a common challenge we solve at Brightrose, partnering with GTM teams to define the integrated motion, build the shared systems and collectively report progress with transparency and consistency, which creates and maintains alignment. #privateequity #vc #sales #GTM

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Before we close the door on 2025, we wanted to look back at what was predicted to happen in GTM this year. My colleague Steven Lewis graded GTM predictions across 3 dimensions: -GTM model alignment -Data-driven profitability -AI workflow challenge How do you think we all did? Here's what Steven said: "The year demonstrated that while AI and market shifts are accelerating, successful transformation is ultimately limited by an organization’s willingness to address difficult, systemic, and people-centric challenges." Read the full blog and see the grades: https://lnkd.in/eSGEApjJ

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Pricing conversations are rarely about pricing. When pricing becomes a structured decision instead of a negotiation, the conversation in the room changes completely. I’ve been in countless retention, upsell, and cross-sell initiatives where pricing was clearly one of the biggest levers yet decisions were made through intuition, precedent, or the loudest opinion in the room. The interesting part is no one ever lacked data. They lacked a way to connect revenue, churn, local pricing comparisons and overall customer behavior into something decision-ready and testable. What we’re building at nunoo is a pricing decision system driven by AI that learns from live customer data (internal and external) and allows teams to simulate concrete scenarios: price changes, packaging shifts, policy adjustments before they’re pushed to market and hypothesis get validated. The value isn’t automation. It’s replacing pricing debates with testable, data-backed trade-offs.

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This session we did two weeks ago was a Masterclass in bringing highly informed CISOs to discuss pressing topics in security and resilience. Well run by Gaven Smith CB and Chris Martin. Particularly interesting to me was the discussion on enforcement and incentives for securing organizations--it was a shame regulators weren't in the room taking notes!

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Developers don’t need another “conference.” We need spaces where ideas spark, experiments happen, and community feels real. That’s why we’re bringing Camp AI by Auth0 to the Bay Area — think summer camp energy, but with the brightest minds in GenAI. You’ll hear from builders at Okta, CircleCI, Traversaal.ai, CodeAnt AI, and Acuvity, plus a panel with leaders from GitHub, Vercel, and Amazon Web Services.From late-night code chats to big-picture debates on how AI is reshaping the dev workflow — this is about building together, not just talking about it. And yes… there will be merit badges. Spots are limited → https://bit.ly/4lbaBol #CampAI #GenAI #DeveloperCommunity #BuildWithAuth0

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