Founder | Agentic AI...ย โขย 2m
Everyone is building agents, but only a small number truly understand what it takes to run them in production. Hereโs the part people usually avoid saying: ๐ ๐ฎ๐ธ๐ถ๐ป๐ด ๐ฎ๐ด๐ฒ๐ป๐๐ ๐ถ๐ป ๐ฑ๐ฒ๐ ๐ถ๐ ๐ฝ๐ฟ๐ฒ๐๐๐ ๐ฒ๐ฎ๐๐. In development, everything is clean and predictable: good data, simple inputs, and no messy old systems. Agents behave nicely. Tests go well. Logs make sense. ๐ฃ๐ฟ๐ผ๐ฑ๐๐ฐ๐๐ถ๐ผ๐ป, ๐ต๐ผ๐๐ฒ๐๐ฒ๐ฟ, ๐ถ๐ ๐ฎ ๐๐ต๐ผ๐น๐ฒ ๐ป๐ฒ๐ ๐ด๐ฎ๐บ๐ฒ. Security teams show up with urgent concerns. Users enter things you never expected. Data often comes in incomplete or confusing. APIs stop working without warning. Memory problems grow quickly and get hard to control. Latency climbs, costs rise, and your agent starts acting unstable. All of this together makes production feel chaotic. And then someone asks: โWhy does it work in staging but not in production?โ Because staging is a comfortable, controlled space, but production isnโt. ๐ง๐ถ๐ฝ๐ ๐๐ผ ๐บ๐ฎ๐ธ๐ฒ ๐ฎ๐ด๐ฒ๐ป๐๐ ๐๐ผ๐ฟ๐ธ ๐ถ๐ป ๐ฝ๐ฟ๐ผ๐ฑ: ๐ธ Treat agents like real software: use versioning, logging, monitoring, and testing. ๐ธ Expect problems. Agents will fail, freeze, or take the wrong path sometimes. ๐ธ Set up an orchestration layer with guardrails, fallbacks, and memory control. ๐ธ Connect with legacy systems early. Waiting makes it worse. ๐ธ Keep a close eye on cost. Prototypes fool you, production does not. The decade of agents is here, but only the preparedย willย succeed.
Founder of VistaSec:...ย โขย 10m
๐ Top Programming Languages & Tools for Exploit Development & Reverse Engineering ๐ ๏ธ ๐ Top Programming Languages ๐น C & C++ โ Low-level access, memory manipulation ๐น Assembly (x86, x64, ARM) โ Essential for understanding binaries ๐น Python โ Sc
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AI Agents now have muscle memory. This Python SDK records agent tool-calling patterns, replays them for repeated tasks, and falls back to agent mode for edge cases. 100% Opensource. Read more here: https://www.theunwindai.com/p/muscle-memory-for-a
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Full Stack Web Devel...ย โขย 25d
Staging environments and release management are critical to reliable software deliveryโ70% of projects fail due to poor release management. A staging environment should mirror production to mitigate risk, support UAT and performance testing; it must
See MoreStrategic AI integra...ย โขย 1m
Top talent prefers companies with automation โ not chaos. ๐ง โ๏ธ They donโt leave for salary first โ they leave for clarity, flow, and systems that respect their time. Chaos doesnโt feel exciting when youโre inside it. It feels like: ๐ธ Constant cont
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Turning ambitious id...ย โขย 9m
๐ง ๐ป Say Hello to Google's Agent Development Kit (ADK)! ๐ Unveiled at Google Cloud Next '25, the Agent Development Kit (ADK) is an open-source framework designed to simplify the creation of intelligent, modular, and production-ready AI agents. ๐น
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Introvert!ย โขย 9m
BIG WIN for India! Apple CEO Tim Cook just announced that most iPhones sold in the U.S. from Q3 will be MADE IN INDIA.๐ Yes, you read that rightโIndia is becoming Appleโs iPhone factory for the worldโs biggest market. Hereโs why this is a game-cha
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Helping businesses g...ย โขย 1m
Everyone wants AI agents. Very few enterprises can actually run them. Hereโs the uncomfortable truth: AI agents donโt fail because theyโre not smart. They fail because organizations arenโt ready. In demos, agents look cheap. In production, costs e
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Founder | Agentic AI...ย โขย 24d
I spent 2025 designing and building hundreds of AI agents. If youโre unsure where to start, hereโs the key thing to know โ AI agents arenโt complicated. The real challenge isnโt coding or connecting tools. Itโs picking the right foundation before
See MoreFounder of VistaSec:...ย โขย 10m
Bypassing EDR with Custom Shellcode Loaders โ A Red Teamer's Approach Modern EDRs use user-mode hooks, behavioral analysis, and memory scanning to flag malicious activity. To bypass them, you need precision-crafted tooling. This deep-dive explores
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4 powerful loops that power Agentic AI. Hereโs the easiest explanation of how each one works. ๐๐๐๐ก๐ง๐๐ ๐๐ข๐ข๐ฃ๐ฆ Agentic Loops explain how AI agents think, act, learn, coordinate, and improve over time using structured cycles. 1. ๐๐ผ๐น๐น๐ฎ
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