Fergus C.

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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More proof assets do not equal credibility. When proof is thin, don't make loud claims. Use a repeatable way to prove what you’re saying. The failure mode is simple. Startups makes claims without evidence and buyers can see the guess work As a PMM fix it with stacked proof One layer per core claim and standardizes it- claim → proof → measurement. Level 1: Mechanism proof Share screen flow, workflow diagram, demo steps that customers can relate to Level 2: Workflow proof Show steps removed, steps added, handoffs changed in the customer's process Level 3: Early signal proof Activation, time-to-first-value, usage frequency, retention trend, pilot completion. Level 4: Outcome proof Show potential win rate, conversion, cycle time, costs saved, revenue impact. Only if you can attribute it. Operating rule: Do not publish a claim above your highest proof level. If you don’t have outcomes, you still have options. Run a pilot to validate what is sticking and that can be the proof point Define the pilot user and workflow. Define one success metric tied to the workflow. Define one adoption metric tied to usage. Define the time window. Show what “good” looks like. At Awvent when we had no customer we applied this process with countless potential customer..refined it with every feedback...eventually landing our first customer ( always a sweet feeling) As early stages startup this is one way you stay credible while the product is still earning outcomes.

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Great insights from Karpathy on where coding agents should be heading. The part that resonates with me most is “I certainly don’t feel ready to supervise a team of 10 of them”. I know I’m not ready and I know the tooling is not ready. I find that when using DevSwarm to coordinate just a few agents at once, fatigue sets in quick. Switching context to monitor what different agents are doing gets really tiring, real quick. I’ve been experimenting with Factory (I think droid is the best at planning) by asking it to assemble a plan with agents in mind, and then use shared memory by tagging issues with context for the specific agents to know which issue it should be picking up. Working with droid collaboratively to assess the PR and then marking the issues complete gives me control over the agents. It’s slower, but gives me control in #hive coding sessions. It’s the only way in my mind to avoid the #ai #slop Karpathy references.

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Velocity and story points are capacity signals, not success metrics. Adoption is where value actually shows up (and it exposes the real bottlenecks: onboarding, UX, data quality, change management, and reliability). In my fractional work, I will often start by resetting the scorecard: - Adoption + retention signals (activation, usage depth, time-to-value) - Delivery health (lead time, failure rate, recovery time) - Learning loop speed (how fast we validate and iterate) Funny thing: when teams measure value, they stop shipping “more” and start shipping better and the roadmap gets easier to prioritize. #SaaS #EngineeringMeasurement #DeliveringValue

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If agentic development is the future, then skills are the atomic unit. But how do you move from experimental to production-grade agents? You need Tessl, the dev-grade package manager for skills. It’s your registry for evaluated skills + platform to manage their full lifecycle. Congrats Guy Podjarny & Tessl team!

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Dashboards don’t create accountability. They create meetings. Charts get shared. Everyone nods. Action items get “noted”. Same problems. Next quarter. Accountability doesn’t come from visibility. It comes from systems — where ownership is clear and decisions can’t be ignored. I wrote a short note on why dashboards feel productive but rarely change behaviour — and what actually does. If your org has great dashboards but the same issues every review… this will sound familiar. Dashboards Don’t Create Accountability — Systems Do: https://lnkd.in/gCGpm-VU

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Addressing Fragmentation in the U.S. Cost Estimation Industry: The cost estimation industry in the U.S. is facing a pivotal challenge: fragmentation. Despite advances in digital tools and methodologies, more than half of U.S. teams report that their estimation workflows are still disconnected and siloed across departments. This fragmentation creates inefficiencies, from duplicated efforts to inconsistent data interpretation. The lack of interoperable systems means firms spend extra resources reconciling estimates and working through compatibility issues—ultimately impacting accuracy, project timelines, and stakeholder trust. In a sector where precision and agility are crucial for both competitiveness and client satisfaction, the persistence of disconnected workflows highlights an urgent need for integration, collaboration, and industry standards. By bridging these silos, we can unlock new levels of efficiency, innovation, and transparency—empowering firms to deliver better results and win greater confidence from clients. Are you seeing fragmented processes in your organization’s estimation practices? What steps have you taken to drive integration? I’d love to hear your thoughts!

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Always fun to host engineering dinners with Sumeet Vaidya and Crafting. Few takeaways for me: 1. We are living through one of the most dynamic periods in software engineering. Everyone by now knows to heavily leverage “Plan” mode upfront when coding with AI - but now we are hearing there’s even more time/tokens/turns spent on “Ask” mode before writing the Plan. And PRs of plans! We are literally flying up the abstractions curve. 2. Documentation used to be a luxury, but it is now cheap and easy. Documentation is increasingly agent-first, and markdowns in the repo seem to work a lot better than Confluence/Notion. 3. Historically the magic of GitHub was how it captured the collaboration context - PRs, discussions, reviews, commit history. Today so much of that context sits in prompt/chat history which does not go in GitHub or anywhere else! Feels like this needs to be solved. Openclaw’s memory system and Granola are both inspirations.

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