Jason Cust

In a recent episode of the Blue Blazes Podcast, host Jonathan "J." Tower sits down with Redis' Guy Royse to break down why the company is more than just a blazing-fast cache - it’s a powerhouse for modern applications. From classic data structures to advanced use cases like session storage, PubSub messaging, and event streaming, they explore how Redis simplifies architecture while boosting performance. Plus, they dive into Redis’ evolving role as a document and vector database, alongside best practices for clustering, replication, and memory management. If you're working with high-performance apps, this episode is a must-listen! 🎧https://lnkd.in/e_uVRCQd

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One of our customers from Tilt (formerly Empower) just shared how they wired the Augment CLI directly into their CI/CD pipeline for PR reviews. It’s a great example of what “agentic engineering” looks like in practice. Some lessons 👇 Their pipeline flow: - GitHub PR triggers Azure Pipeline - Pipeline hydrates a Docker image with PR code + metadata - Augment CLI runs review stages with access to MCP servers (Linear, LaunchDarkly, Notion, GitHub) 💡Lesson 1: Treat AI rules like code. They maintain “always apply” rules just for Augment. When something breaks, they triage it in Slack like a bug. Most teams fail by treating AI feedback as vibes. They treated it as engineering. 💡Lesson 2: Separate rules for humans vs. AI. - Humans get full docs in Notion (“why the rule exists”). - AI gets short enforceable rules (“always do X, never do Y”). The split makes both groups more effective. 💡Lesson 3: Hydrate context. With Notion + Linear + LaunchDarkly hooked up, Augment doesn’t just say “this violates a rule.” It explains why the rule exists, or checks tickets/flags directly. Feedback becomes coaching, not nagging. 💡Lesson 4: Modular prompts. They didn’t dump everything into one mega-prompt. Instead, the CLI runs in stages: - Code review - QA notes from Linear - Feature flag validation 💡Lesson 5: Centralize and version rules. - Rules live in the repo, next to the code they govern. - Same rules apply in IDE, CLI, and pipeline. No hidden logic. Developers see exactly what Augment enforces. The result: faster, higher-quality reviews that also teach developers the why. This is what agentic engineering feels like: less typing, more orchestration, agents enforcing consistency while explaining the reasoning. Big thanks to James Garrett for sharing this.

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Planned software maintenance shouldn’t break apps. Smart client handoffs in Redis Software and Redis Cloud keep apps online during maintenance by proactively reconnecting clients to new endpoints and temporarily relaxing timeouts until upgrades complete. The result: reliable, disruption-free maintenance for critical workloads. Read more in our blog and docs: - https://lnkd.in/gBbbNscA - https://lnkd.in/gfNwa-NK

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Hitting the limits of MySQL or MariaDB at scale? When tables, traffic, and tenants explode, single node engines start to show their seams: capacity ceilings, complex HA topologies, and analytics that are always a step behind. In this new deep dive, Li Shen breaks down where MariaDB still shines, where its monolithic roots hit a wall, and how TiDB’s distributed SQL design gives you horizontal scale, fresh analytics, and MySQL compatibility without DIY sharding. If you are planning your next database move or evaluating MySQL alternatives, this is a must read for architects and engineering leaders. 👉 Read the blog: https://ow.ly/rrBp50Yl7ka

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Groq just announced Compound is now generally available to everyone. The chief architect is not who you might expect. It is a Stanford sophomore who went from viral GitHub apps to leading Groq's agent product in under a year. This is the story of how Benjamin Klieger built the most exciting agentic architecture available today. Ben’s journey to Compound started early. In school, he spent his time building. Social platforms and trade tools, experiments that taught him a deeper truth: The most intelligent systems are defined by making the right decisions at the right time. During that time, he built his second startup: a writing app called Clara. He noticed the problem  for students wasn’t writing essays. It was learning reflective and logical thinking. Clara lived in Google Docs, asking Socratic questions. When it was acquired, Ben saw AI as a force multiplier for tools. In 2024, he witnessed Groq speed firsthand. He assumed someone would build an instant book generator on top of it. He waited. Nobody did. So he launched Infinite Bookshelf: give a topic and a 15-page book appeared in seconds. Groq noticed Ben’s work. How could they not? When they reached out, Ben showed up to the meeting with live demos instead of a résumé. He left with an internship and a mandate. Within six months his projects had over tripled the number of stars on Groq GitHub projects. He learned AI wasn’t just about answering faster, but about creating systems that handle complexity and scale. Ben wanted to prove that the next generation of AI could go further than anyone thought possible. And he wanted to show Groq could be the one to build it. Then came what he called g1, a Groq-powered reasoning app, built within 24 hours of OpenAI’s o1-preview. It hit 4,000 GitHub stars, far more than any Groq repo had ever received. By late 2024, every lab had begun to build compound AI systems that execute search and code. Models were becoming agents. But Ben noticed they were expensive and slow. Latency kills agents. Every tool call, every context switch, every decision added seconds that stacked into unusable experiences. The solution was not better prompts, it was better architecture. When asked to host g1 and pair it with tools, Ben saw an opportunity. Instead of sending every request over distant APIs, server-side tools ran close to inference. Model routing ensured the best models were used. This is where Compound emerged. Ben was promoted to Compound AI Lead and put in charge of the product. The Compound team grew. Iteration with users made it stronger. Adoption followed quickly. Compound became default in GroqChat. Over 100,000 developers used it. Over 5 million requests were serviced. Groq making Compound generally available is a turning point for agentic AI. It exists because of Ben’s journey to build what was missing. Try Compound today to experience the next generation of agents. 🔗 https://chat.groq.com 💻 https://github.com/groq Benjamin Klieger

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Hard-coded secrets show up in more places than teams expect. Repos, tickets, chat threads, shared docs. Finding them is step one. Having a clear, repeatable way to fix them is what actually reduces risk. Here’s what good remediation looks like in practice 👇 https://lnkd.in/dcqQTk_D

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Enterprise customers can now use their existing Anthropic API commitments to buy third-party software built on Claude. Launch partners include Snowflake, legal AI company Harvey, and developer platform Replit. Anthropic said it will not take a commission on marketplace transactions, unlike typical cloud marketplaces that charge 3-5%. https://lnkd.in/d8Mkbws2

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Security Groups > IPs 🔐 Join Erik Reinert to learn how to deploy and scale full-stack cloud apps through Startup, Growth, and Scale, from fast container deploys with Supabase and AWS App Runner to production-ready infrastructure with CI/CD, Terraform, ECS, RDS, load balancers, and CDNs. https://lnkd.in/gRcqdhB5 #Fullstack #Backend #WebDev #Programming #Coding #LearnToCode #DevOps

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