Robert Ross

Every PMM team needs to do this now! Get access to the source code repo. Here is why: 1. Ask questions in Claude or Cursor 2. Uncover how the product works 3. Answer technical and high level questions quick 4. Format outputs by audience 5. Even draw flow diagrams Now there is never a new question you can’t answer in minutes. No need to ask a PM. No need to wait.

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💡 AI doesn’t just change how code is written – it changes expectations and outcomes. In the final section of Jellyfish’s AI Adoption Guide, we explore how expectations for engineering leaders are evolving as AI becomes embedded across the SDLC. Because the organizations pulling ahead are treating AI as a transformation, not a tooling upgrade. Inside, you’ll explore: - Why AI adoption is quickly becoming a leadership mandate, not an option - How to balance ambitious goals with realistic expectations - What cultural investments are required to sustain long-term gains - How data can be used to align executives and engineering teams The teams that win in the AI era won’t just have better tools – they’ll have leaders who know how to guide change. Download today: https://lnkd.in/dut_6WpQ

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In SaaS, “modernization” looks fantastic in a value-creation deck. In practice, it is where a lot of plans quietly go to die. When I work with SaaS companies looking to scale, I see the same traps over and over again: 🔻 Trap 1: Rewrite Fever   “We will just rebuild it the right way this time.” The team underestimates how much the legacy platform really does, overestimates capacity, and discovers mid-flight that critical edge cases were never documented. Feature delivery stalls, customers feel the pain, and nobody is sure when the “new thing” will ever be ready. 🔻 Trap 2: Metrics Theater   “We track DORA metrics and have SLOs on a slide.” But the way work is prioritized has not changed. Product, sales, and customer pressure keep pushing “just one more feature” ahead of foundational work. The dashboards exist, but they do not drive decisions, so teams burn out while the architecture slowly degrades. 🔻 Trap 3: SLT Ping-Pong   Every board or SLT (Senior Leadership Team) conversation results in a new “must-have” initiative. Teams zig-zag between pricing experiments, new modules, and half-finished refactors. There is no protected lane for modernization, and no clear “no-go” list. The result: everyone is busy, but tech risk barely moves. What works instead is boring and disciplined: – A 60–90 day diagnostic tied directly to your growth thesis and business goals   – An explicit, board / SLT–approved modernization lane that coexists with feature delivery   – Clear rules for what the team will STOP doing so the plan is actually achievable  There is no one-size-fits-all. Just because another CEO or CTO did it a certain way does not mean it will work for your company’s reality. If you are a CEO or SLT member with a value-creation plan that depends on “platform modernization,” which of these traps feels closest to home right now? #SaaS #PrivateEquity #CTO #SoftwareEngineering #TechnologyLeadership

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CPTO Revolution: Why SaaS Companies Are Merging Product and Tech Leadership I’ve lived the pain of siloed leadership and the inefficiencies it creates many times. And I’ve also seen how tightly integrated product and tech can transform not just delivery, but outcomes. Traditional org charts are no longer keeping up. The most competitive SaaS companies aren’t hiring separate CTOs and CPOs anymore - they’re bringing both roles under one roof with CPTOs. This isn’t about headcount optimization. It’s about reducing friction and moving faster in a world where complexity is climbing and customer expectations evolve by the week. Here’s the core issue: when product and engineering leadership are separate, you’re always playing a game of telephone. Product defines what’s needed. Engineering estimates and negotiates. Product pushes. Engineering pushes back. Handoffs everywhere. Every step is a delay. A CPTO owns the entire journey - from insight to shipped product. One person accountable. One vision. One continuous flow. And it works. Companies running this model are seeing up to 40% faster go-to-market. Less tech debt. Clearer priorities. Higher team velocity. What Actually Changes 1. Aligned Metrics You stop optimizing for isolated outcomes. Product isn’t chasing adoption while engineering shields uptime. Both roll into shared business goals. 2. AI Gets Strategic With unified leadership, AI isn’t a bolt-on. It becomes core to how you design, build, and validate products - through data, feedback loops, and automation. 3. Developer Experience Matters Platform engineering gets the attention it deserves. Internal tools align with product delivery, and suddenly teams aren’t waiting - they’re shipping. UX maturity, platform architecture, technical scalability - all of it becomes a single continuum. You’re not just improving “process”; you’re aligning every decision to what users need and what’s feasible to build. The CPTO Skillset This isn’t a hybrid role - it’s an integrated one. You need the technical depth to guide architecture and the product judgment to say no to overengineering. You talk to engineers about latency and reliability, and to the board about market traction and differentiation. As AI accelerates software development, what matters is orchestration—of systems, teams, and strategy. You need to see the whole board. Cloud infra spend is growing ~10% yearly, mostly due to AI. That spend needs direction. CPTOs are the ones who can match innovation speed with platform efficiency. Companies clinging to the old CTO/CPO split are playing a slower game. Integration is no longer optional - it’s a competitive advantage. So—what’s keeping your org from making the leap?

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Roadmaps start to look like a junk drawer when every new “opportunity” gets a slot. If you’re running a live SaaS and every decision now has a real cost, you know the pain. The product gets harder to change, and every new feature feels like stacking another wobbly plate on a teetering pile. The real problem isn’t the flood of ideas. It’s letting the loudest voice or the latest shiny thing hijack your priorities. That’s how you end up with a product that’s fragile, slow, and full of features nobody uses. Defaulting to the squeaky wheel feels reasonable. You want to keep your biggest customer happy, or chase the excitement of a new direction. But every time you let urgency or recency set the agenda, you compound the mess. The cost isn’t just wasted effort. It’s a product that’s harder to trust, harder to maintain, and riskier to touch with every release. I see this pattern every time founders treat distractions as opportunities. The pile never gets smaller. The foundation just gets shakier. This is a false economy. The Missing KEI is where I break down this pattern and show how to rebuild decision confidence before the next distraction costs you real ground. The link is in the comments.

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1 Comment

Creating scripts might be worth it for things agents can't reliably do through prompting. I got this from an interview with Peter Steinberger (OpenClaw Founder) where he mentioned that CLIs work better for agents than MCPs. That stuck with me. If I can't get something to work through prompting, maybe I should just build a script the agent can call instead. Here's where it clicked for me. I tried getting my agent to watch our BugBot process in our CI and wait for it to finish. It takes about 10 minutes to run, but it's worth the wait. It catches really good bugs. The problem was that the agent just wouldn't reliably wait. It would either move on too early or stop checking altogether. So I created a script to do the watching. Now the agent just gets notified when it's done. Prompting is flexible. Scripts are reliable. Use both where they make sense.

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Seemingly small features can have a huge impact. With the new AI powered help chat, IT admins can get detailed insights on how to use PDQ Connect to accomplish their goals - all without needing to leave the product. Proud of what the team has delivered here!

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It’s not your talent…It’s your operating model Most product led companies don’t fail because of bad talent. They fail because they outgrow the system that once worked. In smaller orgs, you can operate on alignment by proximity. Slack threads. Founder decisions. Roadmaps in someone’s head. As your org grows, that stops working. • Roadmaps become political instead of strategic • Teams overcommit because no one models real capacity • Forecasts rely on optimism, not shared assumptions • Decision rights get blurry • Leadership lacks a clean, consistent view of performance Nothing is “broken.” But everything feels harder than it should. Scaling doesn’t create chaos. It exposes system and operational weaknesses that were already there. The companies that scale cleanly don’t add more process. They design an operating system: Clear planning cadence Defined decision rights Capacity realism Simple, shared metrics Structure doesn’t slow growth. It protects it. At what team size did things start feeling harder in your org?

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Commerce & Revenue Optimization ​ Today, recommendations are the default in commerce—guests expect relevant options, not generic offers. Onboard is no different. ​ ​ Ascendion helps cruise lines use AI-driven personalization to make it easy for guests to discover, explore, and buy—whether it’s dining, retail, or excursions. With predictive offers and tailored recommendations, every interaction has the potential to increase spend and satisfaction. ​ ​ When commerce feels natural and helpful, it becomes part of the experience, rather than a distraction. ​ ​ Learn more: https://lnkd.in/guDUnmNc ​ ​ #CruiseLine #Ascendion #FutureOfWork #EngineeringAI #DigitalCommerce ​

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