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1h ago · 4 min read · High-volume messaging exposes routing behavior, queueing, latency and execution paths most APIs hide. Everything works. Requests return 200.Messages get accepted.Delivery looks consistent. Until it d
Join discussion1h ago · 4 min read · D-Robotics, a subsidiary of Chinese chip company Horizon Robotics, has launched the industry’s first single-SoC computation-control integrated robot development kit RDK S100. CPU+MCU+NPU Collaborative
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1h ago · 5 min read · You connect an agent to three MCP servers, GitHub, Slack, Sentry. Feel like you've built something solid. Then someone counts the actual token spend before the agent does anything at all. The number is 143,000. Out of 200,000. On tool schemas that ha...
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40m ago · 5 min read · DNS changes are powerful and risky. A single incorrect Route 53 record can cause outages, security exposure, or compliance issues. A simple but effective governance control is to get alerted whenever
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59m ago · 18 min read · tldr: Playwright 1.59 ships the Screencast API, browser.bind() for shared browser sessions, CLI debugging for agents, and await using for automatic cleanup. It's the first release designed around AI a
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1h ago · 9 min read · Asynchronous code is one of the first things that trips up developers coming to Node.js. You write what looks like a perfectly normal function call, and somehow the result isn't there when you expect
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CEO @ United Codes
1 post this monthObsessed with crafting software.
9 posts this month#cpp #design-patterns #rust
1 post this monthBuilding backend systems. Occasionally understanding why they work.
1 post this monthSecurity Researcher | Red Team
1 post this monthCEO @ United Codes
1 post this monthObsessed with crafting software.
9 posts this month#cpp #design-patterns #rust
1 post this monthBuilding backend systems. Occasionally understanding why they work.
1 post this monthSecurity Researcher | Red Team
1 post this monthCompletely agree, most failures I’ve seen come from poor context management and unclear data flow, not the model itself. State handling also becomes a major issue when workflows scale, especially with multiple tools and agents interacting. In my experience, debugging improves a lot once you treat it as a system design problem rather than just an AI model issue.
Hmm, I think AI tools are actually pretty helpful, but you still have to double-check everything — they’re not perfect 🙂
Most companies haven't answered a basic question yet: who is accountable when an AI agent takes an action? Until that's resolved, they'll keep defaulting to safe, surface-level AI features instead of truly rethinking workflows. The bottleneck isn't the technology; it's the accountability layer nobody wants to own.
API docs get attention. The frontend/API contract usually doesn't. TypeScript helps, but types lie without runtime validation. The API returns an unexpected null, a renamed field, an edge case you never tested and your types had no idea. Zod fixes this. Parse at the boundary. If the API changes shape, you catch it at the schema. Not in a Sentry alert a week later. We do this with Next.js Server Actions too. The server/client boundary is the natural place to validate. Keep the schema next to the call. Documentation problem and type-safety problem are usually the same problem.
You’re definitely not alone that “Step 5 bottleneck” is where most AI-assisted teams hit reality. Right now, most teams aren’t fully automating reviews yet. The common pattern I’m seeing is a hybrid approach, not purely human or purely automated. What others are doing AI generates code → Automated checks (linting, tests, security, architecture rules) → Targeted human review (not full manual review) 👉 The key shift: humans review intent + architecture, not every line.
Nice first deployment walkthrough! One thing worth adding to this stack: set up an OAI (Origin Access Identity) or the newer OAC (Origin Access Control) so your S3 bucket stays fully private and only CloudFront can read from it. Without that, the bucket is publicly accessible even though CloudFront is in front. Also, consider adding a Cache-Control header strategy — setting immutable assets to max-age=31536000 with content hashing in filenames, and your index.html to no-cache so CloudFront always checks for the latest version. WAF is a solid move this early — most people skip it until they get hit with bot traffic.
I keep seeing people blame the model when something breaks. In most cases, that’s not where the problem is. From what I’ve seen, things usually fail somewhere else: agents pulling in too much or wron
Agree. This is very close to what I’ve seen while building Origin. Once you connect AI to tools, files, and workspace state, it becomes much...
100% agree — this matches what I see building automation systems for clients daily. The model is usually the most reliable part of the stack...