Nick Wade

When I was working in online video streaming, we were told we couldn't do CD because TV apps had to be certified by manufacturers. Yet we did CD. It helped us build enough trust so that some manufacturers allowed us to release most changes without certification, and others fast-tracked our certification process. When I was working on internal enterprise software, we were told we couldn't do CD because releases had to be planned and manually tested, deadlines respected, and users trained. Yet again, we did CD. Plans became high-level and abstract as iterative execution took over. Automated acceptance tests and feature flags allowed our QA testers to become our first users in production, rather than gatekeepers for releases. Training was built into the frontend applications. It may be the toughest challenge yet, but I'm determined to make it work in a business SaaS startup, where client demands and approvals are everything. The excuses are plentiful, but I have yet to see a domain where CD has failed to deliver results. After all, some of the most famous CD success stories are about printer firmware and an MMO game. Are you sure the software you are working on is more exotic than that?

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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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We finally did it - we’ve launched an agentic test automation system that transforms natural-language test intent into verified, executable browser automation at scale. It’s built for PMs and QA engineers who want to define behavior and expected outcomes - not spend time authoring and maintaining test scripts. It’s equally designed for engineers, so script generation and upkeep are no longer core development burdens. I’m incredibly proud of what our team has accomplished.

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Don’t just ship code. Ship judgment. AI can write code in seconds. But only humans can question it. Before you close that solution or design doc, pause: Is this solving the real problem? What breaks at scale? What’s the long-term impact? Tools catch syntax. Reviews catch thinking gaps. Speed builds features. Judgment builds great systems. #Engineering #Leadership #CodeReview #AI

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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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If you’re a CEO/founder or PE operator and your tech org is: ❌ Shipping late ❌ Stuck in reactive mode ❌ Struggling through the Series A/B jump, or post-acquisition integration or after a major release It’s not “a delivery problem.” It’s an operating model problem. At the inflection point, the old playbook breaks: what worked at 10 engineers fails at 40… and breaks again across multiple products/teams. That’s where I come in as a fractional CTO: - Spot platform and delivery risks before they hit revenue and retention - Rebuild execution rituals (prioritization, ownership, release confidence) without derailing the roadmap - Align architecture + team structure to your value-creation plan (growth, margin, or exit timeline) If you’re feeling the strain of growth, I can help you turn “busy and reactive” into predictable shipping, and a platform that scales. #CTO #SaaS #StartupScale #PrivateEquity #TechStrategy

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I’ve been writing a series of posts on the design principles behind Looping, a product I’m building to help teams run and evolve software over time. These principles shape the architecture underneath and have helped me prioritize clarity, composability, and long-term maintainability from the start. The latest post in the series is about Composable Services. In Looping, every service follows the same interface: it takes a hash of input and returns either Success() or Failure(). That consistency makes services easy to test, reuse, and chain together without resorting to sprawling conditionals or unpredictable side effects. The post walks through the structure, shows real examples, and touches on how it tracks source chains for observability and event logging. https://lnkd.in/ePkn-pF6 #ruby #rails #softwarearchitecture #buildinpublic

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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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We don’t talk enough about this kind of leadership. Last week, forgecode shipped a feature that degraded response quality. Instead of hiding it, they: - Admitted the mistake publicly - Explained what went wrong - Fixed it promptly In the AI space, it’s easy to chase growth at all costs. But accountability is what builds real trust. The companies that own their mistakes and put customers first? They’re the ones that will win long-term. We need more of this energy in tech.

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Hardcore cultures measure hours. Progressive cultures measure outcomes. Betterworks CEO Doug Dennerline warns that RTO mandates and “996-style” schedules risk pushing top talent away. Instead, continuous performance models keep people engaged and businesses growing. Outcomes > hours. https://gag.gl/Wgtz5C

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