Jon Peck

Several people know about this problem but nobody talks about how to solve it. I was asked one time to help fix this issue at a company. The fix lies in breaking the work down to a few critical steps. First, never just hand off work in its entirety and expect you'll get anything you can use. Regardless of how good or bad the team is, always ask, always, the offshore team to pseudo code their approach. They should explain which files they'll touch, which systems they'll touch, integrations, which areas or layers of the application, etc. I call this the first pass. Why is this important? This tells me they're thinking about the problem right and if there are any gaps in their understanding, or any pieces they're missing. After that, they'll do a second pass. That is stubbing out which functions or code will need to be added or modified, maybe even making the functions and service calls work but with mock data. This is the "prove it to me" moment. This second pass also helps me as a dev manager gauge how fast or slow the offshore team is working, giving me indications too if they're stuck somewhere. Only after this second pass, do I actually turn them loose to go execute and "deliver" the solution. Only now, because I did some diligence on my managerial end, I've got greater confidence that what I'll get will be something on par with what I'm expecting and can use. This partnership and collaborative arrangement also fosters trust and over time the offshore team will learn how your organization operates, critical thinking, and that nothing should ever be done in a vacuum or cowboy way. For more helpful tips like this, follow me. I'm paying it forward in 2026 and will be sharing gems most people aren't talk about with a focus on the solutions, not just problems.

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Having run out of things to say, said no one ever, Bradley Shimmin and I roll out his latest brainchild, "the callout" segment on our Agents of Dev podcast. Brad recognizes Microsoft for its GA release of Semantic Link, which allows you (and now your agents) to build and work with semantic models in Power BI. Brad does an illustrious job of describing the origins of semantic models in BI and why they are so vital to agents and their development. Amen, brother. It's a great lead into other topics on this episode, including decoding what is happening at Entire, and semantic models underpin so much of my work defining our Agent Control Plane framework. So much more in this episode. Please check it out, follow, and share the podcast with your friends. Link is in the comments. The Futurum Group DevOps.com Techstrong.ai

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When it comes to selecting the right DXP, things can go off the rails. But don’t lose your caboose. Dan Drapeau has a two-track evaluation model that can keep you rolling – full steam ahead. In today's Guest Critic article, Dan proves why he’s a masterful conductor on the digital experience train. As he explains, the DXP competitive landscape has converged across architectural models, and evaluation approaches haven’t evolved at the same pace. Dan’s observation is that single-track processes are still chugging along – focusing on feature breadth and demo cohesion and favoring pre-composed suites. In his experience, what we really need is a more balanced approach that separates platform evaluation from ecosystem architecture. How do you leave the station? By running two structured tracks, which he outlines in detail. This helps vet not only current capabilities but also long-term durability relative to core considerations like vendor lock-in, CDP and DAM strategies, and the ever-evolving target of AI. In his post, Dan details the operational requirements, where the complexities exist, and how to synthesize results. He even digs into the critical topics of validation and stress testing, and distills it all into a handy checklist to help guide your DXP evaluation. As he says, composable and pre-composed DXPs represent architectural strategies along a spectrum, and these pointers can help keep you on track. “A structured two-track evaluation approach ensures that whichever model is selected, it is chosen for structural alignment and long-term outcomes rather than surface cohesion.” If you’re currently evaluating DXPs – or considering it in the future – this is a fantastic read from a sharp practitioner. Check it out on CMS Critic: 🔶 https://lnkd.in/e-XB3Pig #dxp #digitalexperience #digitalexperienceplatform #softwareevaluation #dam #digitalassetmanagement #cdp #customerdata #customerdataplatform #cmp #contentmarketingplatform #ai #artificialintelligence

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This is the auto-healing system inside VantageOS. Most platforms depend on people to notice when something breaks. This one is built to notice, understand, and respond on its own. Behind the interface is an internal agentic layer continuously monitoring system state, data integrity, workflow execution, and operational signals. When something drifts, degrades, or fails, it does not just raise a flag. It diagnoses the issue, traces dependencies, and initiates corrective action to restore alignment. Quietly. Continuously. Without waiting. Because in complex environments, small inconsistencies do not stay small. They cascade. Adam and I built this with a simple principle: a serious system should not just run, it should maintain itself. That means detecting anomalies early. Resolving issues before they compound. And keeping the platform stable, reliable, and aligned even as conditions change. This is what operational resilience looks like when it is built into the system itself. #VantageOS #AI #AgenticSystems #Automation #OperationalIntelligence #Resilience #Infrastructure #SystemsThinking https://lnkd.in/giTUvp3p

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Your Notion workspace violates HIPAA. High-growth HealthTech teams pick tools for speed. They retrofit compliance later. This fails 100% of the time. Notion is the worst offender. The Licensing Gap: <> Plus ($10) and Business ($15-$25) plans do not include a Business Associate Agreement (BAA). <> No BAA = no PHI. Period. Placing any Protected Health Information in your workspace violates the HIPAA Privacy Rule. The "Shadow" Leak: <> Management tells me: "We don't store patient records in Notion." BUT, your engineering workflow does in the following ways: <> Bug Tickets: Developers paste screenshots with patient names or MRNs. <> User Research: Product Managers paste raw patient emails into databases. <> Onboarding: Implementation teams track pilot users via CSV imports. The Audit Reality: <> No BAA = no PHI data. <> Notion locks the BAA behind the Enterprise tier. The Fix: Two options: 1) Upgrade to Enterprise. Get legal coverage. 2) Segregate your tools. Use Notion for code only. Use compliant tools (Jira Enterprise) for patient data. I wrote a technical guide. Link in first comment. 👇

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Most DevRel programs are set up to fail. Not because the people running them are bad at their jobs. Because they're measuring the wrong things, reporting to the wrong people, and have no system for proving their value. This is the playbook that fixes it. Opinionated. Practical. Designed to turn DevRel from "the team that gets cut first" into a growth engine with a seat at the table. https://lnkd.in/gt-WUiaK

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Status Update: I've been experimenting with Claude-Flow, an open source project that coordinates swarms of Claude Code agents to tackle larger development tasks as a team. My current test case? Building a modest MCP server to manage Azure Storage Accounts. You can see the work in progress here: 🔗 https://lnkd.in/e6AHtNih 📄 Each major step is documented in COMMANDS.md and tagged, allowing you to follow the iteration history. 📄 There were no manual changes other than the command log entries. A few things I’ve learned so far: Let go of the reins: Define the requirements, but let the agents propose frameworks, libraries, and other details. Trying to micro-manage design choices slows things down. Additionally, Claude sometimes makes wiser choices than I would have. Multi-agent ≠ omnipotent: Claude struggled to fully implement and validate GitHub Actions workflows. For CI/CD tasks, I’ll likely involve the GitHub Copilot agent, which is hosted on GitHub and can test workflows natively. Speed mismatch: The agent swarm works fast—so fast that I’ve become the bottleneck. Context switching and reviewing changes is now my biggest challenge. It’s early, but this points to a future where developers become collaborators with fast-moving agent teams, rather than taskmasters. I feel like a product manager, rather than a developer. I’m giving my agent team a larger project next time! Curious to hear others’ thoughts—or experiences—working with AI agent swarms. Happy to answer questions too. #AI #DevTools #ClaudeAI #AgenticAI #DevOps #GitHubActions #Azure #OpenSource #ClaudeFlow #AIpairProgramming #MCPProtocol

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