Erran Berger

💡 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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Who needs self-service? In this article, Conduktor’s VP of Engineering, Matt Searle, talks about his own experiences attempting to balance developer autonomy alongside platform stability. His key insight? Govern Kafka, or risk havoc. Read his latest blog—and learn more about how Conduktor can help you implement self-service with guardrails. https://lnkd.in/ejWTRctu

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One thing the industry isn’t talking about enough: building trust with AI-powered observability. AI is getting more powerful, but in high pressure moments, engineers still need to stay in the loop. 👇 Hear more from Devin Cheevers, Director of Product.

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🧢 Platform engineers aren’t just building tools. They’re building products. At PlatformCon 2025, our CTO and co-founder Ganesh Datta made the case for why platform teams need to think like product managers. His talk covers: ✔️ How to design for adoption, not just availability ✔️ Why golden paths are only valuable if they’re opinionated ✔️ What product management failure modes look like in platform teams ✔️ The metrics that actually show you’re making an impact This is how great platforms get built. Don’t miss it. 🎥 Watch the full session → https://lnkd.in/guE__kYB

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PagerDuty is now a Cursor customer. Over 30,000 customers rely on PagerDuty to respond to incidents faster, reduce outage risks, and build operational resilience. We’re excited that PagerDuty engineers will now use Cursor’s agents to build these mission-critical products.

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Spotify's engineering team built a background coding agent with Claude Agent SDK that handles complex migrations across their massive codebase. Engineers describe what they need in plain text—via Slack, even—and the agent takes it from there, running tests and opening pull requests. They're now merging 650+ agent-generated PRs into production each month. Read more about how they built it, and what else Claude is enabling at Spotify: https://lnkd.in/gVhivXu6

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Your CI/CD bill is not exploding because of “expensive runners,” it is bleeding out through flaky tests, over-parallelized jobs, and slow feedback loops that quietly tax every deploy This piece shows you how to redesign pipelines so you cut compute waste, shrink queues, and speed up developer flow without adding yet another approval gate or YAML religion Full breakdown in the comments. #DevOps #CICD #PlatformEngineering

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“AI copilots don't make decisions in a vacuum—they amplify the access and context you give them.” That quote from our CEO, Jim Alkove, during his recent LinkedIn Live really captures the opportunity and the risk of copilots in the enterprise. When copilots connect to your environment, they inherit your identity posture. If access policies are too loose or misconfigured, copilots won’t flag it, they’ll just act on it. That’s why we believe identity must be the control plane. It’s not just about security—it’s about trust in how AI behaves across your organization. It’s a 20-minute conversation, and it’s worth every minute.

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🧠 How JFrog ML Is Transforming the AI Software Supply Chain AI is becoming core to software delivery, but most ML pipelines remain fragmented, insecure and hard to govern. JFrog ML extends JFrog’s Software Supply Chain Platform to unify DevOps, DevSecOps and MLOps all in one secure enterprise-grade ecosystem. JFrog ML delivers:  ✅ End-to-end model lifecycle management ✅ Built-in versioning, metadata and promotion workflows ✅ Continuous security scanning of AI models and dependencies ✅ Seamless CI/CD integration for ML artifacts ✅ Multi-cloud and hybrid support with full traceability As AI scales, so do the risks. JFrog ML helps teams manage models with the same trust, traceability and automation as software, at an enterprise scale. 👉 Read the full blog here: https://lnkd.in/gkPGEfnP #MLOps #DevSecOps #SoftwareSupplyChain #AI #JFrog

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Custom software is not a feature upgrade. It is an operating decision. When software is built around your workflows, three things change: • Scale stops being constrained by tools • Security becomes architectural, not reactive • ROI compounds instead of leaking through licenses Off-the-shelf products optimize for averages. Custom software optimizes for you. Hiteshi builds systems aligned to business logic, not templates. #CustomSoftware #EnterpriseTech #DigitalTransformation #Hiteshi

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LiteLLM is an open-source proxy that connects your app to LLMs through one unified interface. Paired with Redis, it gives AI and ML teams a simple yet powerful way to unify access to LLMs, accelerate response times, and make AI apps real-time. Redis handles performance, memory, and data coordination that modern AI apps demand, while LiteLLM handles abstraction and routing. Our AI Product Marketing Manager Rini Vasan dives into: ▶️ What LiteLLM is ▶️ Why it works well with Redis ▶️ How LiteLLM and Redis work together Learn how to scale your LLM gateway with LiteLLM & Redis: https://lnkd.in/gqsTebF7

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"APIs are the connective tissue that allow an organization to thrive." Nearly every company I speak with is navigating the same challenge: modernizing their API landscape while preparing for AI-driven systems. The biggest brands want clear guidance on how to govern, scale, and future-proof their APIs as AI becomes more central to how software is built and operated. This conversation with Matthew Gray, Head of Channel Sales at Postman, does a great job exploring what that journey looks like in practice and why APIs sit at the center of it. Full discussion: https://lnkd.in/g8qUX9dt

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Crashes cost revenue. Poor #UX costs trust. #MobileTeams can't afford reactive workflows anymore, and your app is only as good as what your users experience. 😬 CIOReview spotlights how leading teams can detect, prioritize, and resolve issues with our AI-powered #MobileObservability before users ever notice.🛠️ 👉 Get the full insights: https://hubs.ly/Q03p4jYf0

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For industry leaders like RS, API orchestration is the foundation for efficiency and scale. With Apollo’s graph-based orchestration platform, they unlocked 10x performance, and reduced latency by 24%, enabling their teams to build and innovate across previously siloed systems. See how RS modernized its tech stack to support future growth → https://lnkd.in/gYKdmGCG #GraphQL #APIorchestration #ApolloChampions

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