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3h ago · 7 min read · In Part 1 of this series, you ran a structured audit of your digital footprint and very likely found at least one website you didn't recognize, listing your name, address, and phone number for anyone
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This was the first issue, the major issue I faced while migrating my Node.js codebse to Golang was during the implementation. I was tired googling "What is the best alternative of express package in Go?" and so on. It was never ending. searching for each package and then you see multiple results, filter them according to the reviews, github stars, stack overflow, etc. What if there was a tool who could do all this? Thats why I build PackagePal, It is a code migration assistant which suggest the best alternative of a package in target language. It helps developer with best alternative packag
This is a great breakdown of how design patterns shift the focus from 'making it work' to 'making it maintainable.' I’ve found that the real shift happens when you stop seeing patterns as just theoretical structures and start seeing them as solutions to specific 'code smell' scenarios. For anyone currently digging into these patterns, I’ve been working on a tool that summarizes technical deep-dives and video documentation into concise, readable formats. It’s been helping me get through architectural documentation much faster—you can check it out at ytskim.com. Out of curiosity
From what I've seen, the roll-out experience varies a lot based on how clean your existing Salesforce data is. Teams with messy CRM hygiene are finding Agentforce amplifies the chaos rather than fixing it — garbage in, garbage out but faster. The "next evolution of CRM" framing is a bit generous at this stage. It's more like: Salesforce added an AI layer that works really well when you already have tight processes, and struggles when you don't. The more interesting question to me is whether it changes how small and mid-size teams think about headcount. If Agentforce can genuin
Did you like this story? Any suggestions or queries about next part please inform me in comment section Thank you Rohini Reddy
Really liked this breakdown. Most “we cut costs by X%” posts stay very high-level, but you actually walked through the trade-offs of moving from a VM to Azure Container Apps without rewriting the FastAPI backend, which is the part teams worry about the most. The way you leveraged ACA’s scale-to-zero and per-second billing model makes a lot of sense for APIs that aren’t constantly hammered with traffic. It’s a good reminder that infra cost is not just about instance size, but about how the platform scales your workload over a 24/7 cycle. I’m curious how the migration felt from
This is a great example of the difference between software development and production engineering. Most developers spend their early years asking, "How do I make this work?" Eventually the question becomes, "What happens when it stops working?" That's where reliability starts. The point about failure paths stood out the most. Many systems are designed around successful requests, but production environments are defined by timeouts, dependency failures, traffic spikes, bad user behavior, and unexpected edge cases. The teams that plan for those scenarios usually ship more resilie
What's working for us with spec-driven development is treating acceptance criteria as checks the agent can run, not paragraphs it has to interpret. Small TOC example in the latest post on the prickles
This makes sense. If the acceptance criteria cannot be checked, the agent is still guessing. Turning specs into runnable checks gives the ag...