Why early product teams should care about end-to-end observability This late evening, our team jumped on a call to debug a tricky client-side issue for a customer. Everyone had a different theory, but the truth only emerged when we looked at the full picture — from Grafana Faro (client telemetry) to Grafana Cloud Prometheus (backend metrics). That moment reminded me: observability isn’t just a “senior backend” thing. It’s a skill every engineer in an early product team should learn. Here’s why: You stop building in the dark. Observability lets frontend devs see the real user journey, not just console errors. You build empathy. When engineers can trace a bug from a user click → network → service, they stop blaming layers and start solving together. You grow faster as a team. New engineers don’t just fix issues, they understand impact — and that builds product thinkers, not just ticket closers. End-to-end observability is more than dashboards and metrics. It’s about building trust inside your team and with your users — because nothing feels better than waking up to a bug solved overnight and a customer smiling. If you’re leading frontend teams, give them this superpower early. It pays back every single day.

How did Emergent go from 0 TO $15M ARR IN JUST 3 MONTHS? To find out, I invited their CEO Mukund Jha to Infinite Curiosity Pod. Here are 5 points that stood out: 1. Time-to-Value that feels magical: Idea → working, deployed app in minutes (tests, version control, deploy baked in). When users see production outcomes fast, they stick. 2. A built-in referral loop: Every shipped app is a shareable proof point. “It works in prod” triggered word-of-mouth across teams and companies. 3. Infra choices that favored iteration: Modular orchestration, replayable traces, and cached plans let engineers test thousands of agent runs per day without breaking prod. 4. Design for confidence, not novelty: Every workflow (diff view, approvals, tests) was built to reassure users they’re still in control, turning skepticism about “AI-writing-code” into trust. 5. Enterprise-ready from day one: Guardrails (audit trails, CI/CD, rollbacks, data boundaries) made buyers comfortable putting real workloads on it, so usage scaled beyond pilots quickly.

Platform engineering is the future 🚀 Developers are at the core of everything we do at PagerDuty 💚 Our latest collaboration with Spotify for Backstage brings PagerDuty’s industry-leading Incident Management directly into Backstage, the open platform reimagining developer experience. With the new PagerDuty Plugin for Backstage, devs can see incidents, on-call context, and service ownership right where they already work : Less dilution ; More focus. Let’s go 🎉 Read more 👇 https://lnkd.in/gnsq8Nr9

Speed without stability is just chaos in motion. We were shipping every sprint, velocity looked great. Then maintaining code became harder. That's when it clicked - we had speed, but not a clearly defined direction. Every team had their own patterns. Different API designs. Different solutions to the same problem. What actually worked: ⚙️ Built shared templates for APIs and core services - gave teams guardrails, not gatekeepers. 🧹 Carved out dedicated sprints for tech debt - made alignment a priority, not an afterthought. 💬 Focused on alignment, not control - when accountability is present & teams understand the "why", they own the direction. Slowing down for a sprint helped us accelerate for the quarter. Fast without structure isn't progress - it's just motion. How do you balance speed and maintainability? #EngineeringLeadership #ScaleUp #TechDebt #EngineeringCulture #TeamAlignment

Lately, I’ve been diving deep into what no-code product building really means — beyond the buzzword. Tools like Lovable, Bolt, Opal, and Firebase are reshaping how fast ideas can evolve into real products. What fascinates me most is how no-code enables teams to prototype faster, test assumptions earlier, and visualize complete product flows with remarkable speed. It’s not just about tools — it’s about reimagining how we approach problem-solving, MVP creation, and user experience design in the modern product lifecycle. I’m exploring this space actively and would love to connect with others passionate about no-code, product strategy, and AI-driven innovation. How are you using no-code to bring your ideas to life? #ProductManagement #NoCode #Innovation #Strategy #Automation #MVP

Ever requested an Uber? From a user's view, it's simple. Request, match, pickup, trip, complete. Architecturally, it's a nightmare. 😰 That "simple" ride is a 15+ state distributed transaction across 6 event streams. It must reliably execute over 30+ minutes, surviving crashes, network failures, and app restarts. At one point, 80% of Uber's API requests were just polling calls. The "quagmire of callbacks" is a trap many architects fall into. ❌ Pitfall 1: Message Queues (Kafka/SQS) for State The Lesson: Queues are pipes, not process managers. They're stateless. Building workflows on queues forces you to manually code: 🔹 State management (separate DB) 🔹 Retry logic 🔹 Timers (cron/scheduler) 🔹 Chaining (multiple topics) You've smeared the problem across three systems. ❌ Pitfall 2: Saga Choreography The Lesson: While "decoupled," this becomes "implicit chaos." Business logic is smeared across services. Debugging requires tracing events across 10+ systems. 🔍 ⚠️ Saga Orchestration (The "DIY" Problem) Centralized logic is better, but now you must build, scale, and maintain a complex, stateful orchestrator that becomes your single point of failure. ✅ How Uber Solved It: Durable Execution Uber built Cadence (now Temporal) - a new paradigm that provides the orchestrator as a platform. You write simple, sequential code. The platform virtualizes state, timers, and queues. Server crashes become irrelevant. 🛡️ 📌 Key Takeaways: 1️⃣ Queues are for messages, not processes 2️⃣ Saga Choreography is "implicit chaos" 3️⃣ Temporal implements Saga Orchestration as a platform - no DIY orchestrator needed Uber grew Cadence to 100+ use cases. The pattern was so valuable, founders left to create Temporal as an industry platform. 🚀 What's your approach for managing long-running workflows? Still building your own orchestrator? 💬 Check out this latest post here to know more: https://lnkd.in/gSyr5-x8 #SystemDesign #DistributedSystems #Microservices #SoftwareArchitecture #EventDrivenArchitecture #SagaPattern #Orchestration #Choreography #Temporal #UberEngineering #Cadence

So, our quarterly OKR discussions kicked off this week. I’ve been defining OKRs for our Frontend Engineering team - a chance to align on what truly drives impact and engineering excellence. Our focus this cycle: 📌User Impact: Faster, smoother, and more accessible experiences that users can feel instantly. 📌Tech Health: Completing critical migrations and reducing tech debt that slows us down. 📌Engineering Excellence: Strengthening code quality, reliability, and observability so we can move faster with confidence. 📌Alignment: Partnering closely with Product, Design, and Backend - our OKRs should reinforce each other, not exist in silos. Good OKRs aren’t just goals - they’re a shared understanding of why our work matters and how we’ll deliver it sustainably.🚀 #frontend #engineering #okr #engineeringexcellence #techdebt #leadership #team #migration #simbian

Building Systems with Empathy Over the years, I’ve realised — building great systems isn’t just about logic or scalability. It’s about empathy. Whether it’s designing backend architecture or leading a team, empathy changes everything. When I started truly listening — to users, to my team, I noticed subtle shifts. Bugs dropped. Friction reduced. Ideas started flowing with ease. It made me see that tech systems and human systems are not so different. Both need space, clarity, and care to thrive. Empathy is not soft. It’s strategic clarity wrapped in compassion. #MindfulLeadership #TechWithHeart #SystemThinking #EmpathyInAction #ConsciousLeadership

Choosing the Right Tech Stack Can Make or Break Your Project Too many teams chase trends instead of focusing on what truly fits their product goals. At DevSouq Technologies, we believe a great tech stack isn’t about hype, it is about balance, speed, scalability, and simplicity. This short guide breaks down how we approach tech stack selection, from problem definition to long-term scalability, ensuring the product stays solid as it grows.

Sometimes Growth Means Killing Features Killing features feels like failure, right? Here’s what happened: our team kept every “just in case” feature. Support tickets piled up. Onboarding slowed. Dev velocity dropped. Then we killed 3 unused features. Crazy enough, retention jumped 12%. Customers suddenly saw a product that felt focused. Team got time back for the stuff that really mattered. Lesson learned: sometimes growth isn’t about adding - it’s about pruning. Focus signals trust, frees resources, and improves LTV.